IMS Health RWE AccessPoint Vol. 5, Issue 10 by IMS Health RWE Solutions & HEOR publications library

VOlUmE 5, ISSUE 10 • mAY 2015

AccessPoint News, views and insights from leading international RWE experts

The RWE Ecosystem An environment that nurtures real-world success

Accelerating R&D eﬃciency Streamlining and strengthening HEOR and drug safety Elevating healthcare and commercial performance Empowering sustainable transformational advancements 100% of surveyed IDNs in the US use RWD but 55% need 55% support to do more with it

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

INSIGHTS “RWE potential TITLE must beHEADING managed as an ecosystem where companies tap innovative technology and analytics to access, analyze, report and visualize the data that creates value for decision making.”

Jon Resnick Vice President and General Manager Real-World Evidence Solutions, IMS Health Jresnick@imshealth.com

Introducing the concept of the RWE Ecosystem where all the components of RWE come together to help stakeholders across the organization ﬁnally realize its potential.

Welcome Welcome to a special edition of AccessPoint, introducing the concept of the RWE Ecosystem where all the components of RWE come together to help stakeholders across the organization finally realize its potential.

RWE has ‘grown up’ in the domain of HEOR, pharmacoepidemiology and drug safety, supporting discreet research questions, one at a time. The explosion of real-world data (RWD) has expanded our ability to understand patients, treatment paradigms and outcomes, with benefits for R&D through commercialization. But this potential must be managed as an ecosystem where RWD platforms have the right breadth and depth and where companies tap innovative technology and analytics to access, analyze, report and visualize the data that creates value for decision making.

We have explored the RWE Ecosystem through four stakeholder lenses:

•

• AccessPoint is published twice yearly by the ImS Health Real-World Evidence (RWE) Solutions team. VOlUmE 5, ISSUE 10. PUblISHED mAY 2015. ImS HEAlTH 210 Pentonville Road, london N1 9JY, UK Tel: +44 (0) 20 3075 4800 • www.imshealth.com/rwe RWEinfo@imshealth.com

R&D colleagues. We show how investment in using RWE and applying advanced analytics brings potential to realize significant savings through an enhanced, more efficient study process and improved ability to find patients for clinical research. We also include a perspective from a guest contributor who reflects on bringing RWE to the R&D department of an international biotech, as well as case study examples of how other companies are prioritizing R&D efforts through RWE.

HEOR, pharmacoepidemiology & drug safety researchers. We consider how secondary data sources are ensuring product safety more efficiently through streamlined drug utilization studies. We explore the potential of social media as an untapped source for early signal detection. And we look beyond the US market to consider data linkage efforts globally, with an example of how this approach can successfully address complex questions in health outcomes and epidemiology.

Commercial & market access teams. We focus on RWE as a support for decision making and its role as a pivotal catalyst for collaborations with Integrated Delivery Networks (IDNs), with insights into their current use of RWE to inform a future process. We also highlight learnings from organizations that have successfully leveraged RWE for more accurate forecasting and planning as well as improved pricing and market access. And a discussion on HTAs sheds light on how these decisions might require more tailored RWE. RWE platform developers. RWE leaders are building branded platforms to elevate the importance of a consistent, robust evidence base. We offer insights into assembling the appropriate datasets and leveraging the platform throughout the organization. The T-shaped data principle provides a valuable framework for considering RWD acquisition trade-offs. And given the technical considerations for using this data, we outline the unique complications and implications of coding.

At IMS Health, we are committed to providing insights to help advance health and improve patient outcomes across all care settings globally. We hope you find this magazine particularly useful in your RWE journey.

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

VOlUmE 5, ISSUE 10 • mAY 2015

AccessPoint Research & Development Realizing RCT eﬃciencies using RWD How EMR powers clinical trial processes and outcomes Expanding clinical trials leveraging RWD Smoothing RWE assimilation into clinical development

8 14 17 20

HEOR, Pharmacoepidemiology & Drug Safety Why RWD is key for multi-country DUS The untapped potential of social media Primary care EMR identiﬁes drug safety signals Answering complex epidemiology questions by linking RWD

25 29 33 36

Commercial & market Access Capturing a window of opportunity for IDN collaboration Is HTA convergence achievable in Europe? Using RWE to size complex markets for product valuation

39 43 48

RWE Platform Developers Secrets of building eﬀective evidence platforms Guiding RWD portfolios with T-shaped data Cracking the curse of RWD codes Accessing the right RWD for your evidence strategy

54 58 62 66

NEWS

PROJECT FOCUS

2 STAKEHOLDERS UNITE TO STRENGTHEN RWE IMPACT

CARDIOVASCULAR DISEASE Improving clinical trial operations

ORPHAN DISEASE Innovatively expanding an RCT

MULTI-SITE CARE SETTINGS Meeting complex research needs

3 FORUM EXPLORES NEW WAYS TO DEMONSTRATE VALUE 4 EXPANDED CABABILITIES BROADEN RWE OPTIONS 5 EXTENDED RWE PLATFORM ACCELERATES INSIGHTS 6 HEALTHCARE SPENDING REACHES NEW THRESHOLDS 7 INTRODUCING THE RWE ECOSYSTEM

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NEWS RWE LEADERSHIP SYMPOSIUM US leadership symposium marks significant step forward in collaborative efforts to accelerate RWE engagement and impact

IMS Health and JHU unite key stakeholders to realize vision for RWE Payers use RWE in decision making but they New direction for actionable solutions recognize challenges to using it more expansively The symposium culminated in a discussion of solutions, and routinely. The output from a recent leadership including six identified by participants during the meeting. symposium, involving pharma, academic and payer Solutions were divided into four main areas on a spectrum participants, provides a new set of actionable from increasing awareness of current RWE activities through solutions for overcoming these hurdles. collaborations where payers and pharma alike would have

IMS Health and the Johns Hopkins Center for Drug Safety and Effectiveness recently co-hosted a unique US leadership symposium on RWE in Baltimore, MD.1 The event formed part of a wider program of ongoing IMS Health initiatives to understand the use of RWE by payers and Integrated Delivery Networks (IDNs) in the USA. These activities include:

• • • •

Research on more than 100 known cases of RWE application in payer decisions Survey with 70 US payers and IDNs

Symposium on “Bridging the real-world evidence divide with payers and IDNs: Making pharma a true collaborator in evidence” at the ISPOR 20th Annual International Meeting in Philadelphia in May, 2015

IMS Health White Paper exploring “Why Pharma needs to work differently with payers and IDNs on RWE” capturing learnings to date from our research

Exploring the use of RWE in US reimbursement decisions

The JHU-IMS Health “RWE Leadership Symposium: Realizing the full potential of RWE to support pricing and reimbursement decisions” aimed to bring together healthcare leaders representing different parts of the industry. Its goal was to find solutions that would enable all stakeholders to use RWE more consistently to inform reimbursement coverage decisions in the USA.

Approximately 40 leaders from payer/managed care, pharmaceutical manufacturers, academia and IMS Health participated in the closed-door dialogue. The ambition was to make this effort different than previous initiatives in this area. The focus needed to be on solutions.

The event’s agenda included payer and academic presentations on the current use of RWE and barriers to using it more broadly. Dr. Lou Garrison, Professor and Associate Director, Pharmaceutical Outcomes Research and Policy Program, Department of Pharmacy, University of Washington in Seattle, had previously chaired the related ISPOR efforts on this topic and moderated the session. A Q&A approach facilitated frank discussion around hurdles to overcome, such as trust in the RWE presented as well as concerns about what information is not shared with payers. Lack of resources and skills and challenges accessing data were also flagged. 1 2

something at stake. Specifically, the four topics were (A) Increased transparency/awareness building, (B) Standard setting, (C) Collaborations on generating RWE and (D) Collaborations on specific applications. Figure 1: Symposium participants showed an interest in real solutions

Increased transparency/ awareness building

Collaborations on generating RWE

More dialogue

Collaborating to apply RWE broadly

Standard setting

D Collaborations on specific applications

* Bubble size represents participant interest

A vote was taken to determine the solutions considered most interesting to pursue (Figure 1). Overall, there was a strong desire to provide clarity on what RWE can be trusted to use for decision making. One of the highest rated ideas involved a process for rating or approving proposed RWE protocols and conducted studies ̶ a suggestion that would solve several of the identified barriers by creating a trusted, objective third party to validate the RWE while leaving recipients the freedom to apply those insights and evidence generators to frame the questions they want to pursue.

The symposium successfully elevated the topic in broader policy debates around RWE. For example, it resulted in a scientific manuscript, accepted by the Journal of Managed Care & Specialty Pharmacy and currently in press2 that explores a certification process that could be used to strengthen the confidence of all parties in the quality of RWE. For further information or to request copies of publications capturing our RWE payer research findings, please email Marla Kessler at Mkessler@imshealth.com

Real-world evidence leadership symposium: Realizing the full potential of RWE to support pricing and reimbursement decisions. Jointly sponsored by Johns Hopkins Center for Drug Safety and Effectiveness and IMS Health, 4 November, 2014, Baltimore MD.

Segal JB, Kallich JD, Oppenheim ER, Garrison LP Jr, Iqbal U, Kessler M, Alexander GC. Using certification to promote uptake of real-world evidence by payers. Journal of Managed Care & Specialty Pharmacy. In Press.

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

NEWS IMSCG MARKET ACCESS CONFERENCE

IMS Consulting Group holds its 12th Annual Market Access Conference

Pricing & Market Access and brand specialists consider new ways to demonstrate ‘value’ IMS Consulting Group (IMSCG), IMS Health’s life • sciences strategy consultancy, held its 12th Annual US Market Access Conference on 12-13 March, 2015 in New York.

With over 200 clients in attendance, representing more than 40 companies, the conference addressed some of the key trends related to the US and global pharmaceutical landscape and implications for commercial and market access strategies. These trends covered the increase in ‘expensive’ oncology regimens, evolution of ‘value-based’ pricing by European payers for innovative therapies, and the shift in US decision makers to stakeholders, including Integrated Delivery Networks (IDNs). Interestingly, RWE was often cited as a key part of the solution for many of the identified challenges.

As in previous years, the conference speakers included thought leaders from industry, government, the media and Wall Street.

•

Key conference themes included:

•

How companies can better define and capture the value of innovation. Globally, payers are attempting to balance clinical priorities with budget realities. Topics considered how payers define value as the incremental benefits in relation to cost of product, and how to optimally frame engagement with them to articulate that; how pharma can optimize the commercial opportunity for new therapies in an increasingly complex environment; and what kind of funding models and supporting evidence are needed to maintain innovation and ensure patient access.

Evaluating and engaging with new models and stakeholders. Speakers shared lessons learned on how to market to physicians in a highly managed environment, the growing influence of IDNs, and implications for the go-to-market model. They considered how pharma engagement with IDNs is at a tipping point as IDN influence grows and yet companies question their ability to capture value through IDN outreach. Requirements for future success were explored.

Market drivers and signposts for change. The discussion included how the rising cost of cancer care is leading both payers and providers to move away from the traditional fee-for-service model; global tendering changes and impact on brands; US healthcare exchanges and the impact on patient decisions relative to commercial insurance; and how IDNs and payers are actually using RWE, revealing big differences in managed care and IDN actions and behaviors.

•

Dr. Farzad Mostashari, CEO of Aledade, delivered the keynote address, discussing his overall perspective on the changing face of healthcare. Dr. Mostashari co-founded Aledade to help primary care doctors form accountable care organizations (ACOs). He is also a Visiting Fellow at the Brookings Institute in Washington DC, where he focuses on payment reform and delivery system transformation.

Dr. Mark Schoenebaum, Senior Managing Director, Head of Evercore ISI’s Health Care Research Team and Evercore ISI’s Biotechnology & Pharmaceuticals/Major Analyst, shared his perspectives on Biopharma. Dr. Schoenebaum has been ranked Institutional Investor #1 biotechnology analyst for the past 10 consecutive years and has been the #1 pharmaceuticals analyst for two straight years (having first initiated on the pharmaceuticals space three years ago).

Dr. Steve Miller, Senior Vice President and Chief Medical Officer of Express Scripts and Peter Wickersham, PRIME Therapeutics’ Senior Vice President of Integrated Care and Specialty, participated in a ‘crossfire’ discussion on how business models will evolve over the next several years with PBMs responding to increasing costs in specialty care, biosimilars launching and new stakeholders such as IDNs emerging.

Throughout the year, the IMSCG team will also hold Market Access Conferences for clients in Europe and Asia. For further information or to discuss the presentation content, please email Jennifer Hillyer at JHillyer@imscg.com

Leading RWE collaboration: Participants at the JHU-IMS Health RWE Leadership Symposium in Baltimore (left and centre) and at the IMS Consulting Group’s 12th Annual Market Access Conference in New York (right).

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NEWS BROADER RWE OPTIONS IMS Health advances solutions for enhancing healthcare performance with acquisition of complementary Cegedim business offerings

Expanded capabilities broaden client options to improve RWE and operational eﬃciency Healthcare decision makers are placing increasing importance on more efficiently managing ‘big data’ and the complexities of commercial interactions across multiple stakeholders and channels. Through the recent acquisition of certain Cegedim CRM and Strategic Data businesses, IMS Health provides the step• change in capabilities that clients need. This allows companies to improve the performance of healthcare through more informed decisions as well as the effectiveness of their customer communications, shored by a new depth and breadth of global support services. Cegedim is a global technology and services company specializing in healthcare. It helps clients in over 80 markets, bringing a long history in RWE, which will enable us to provide clients with even more options for realizing the value of RWD as well as leading-edge CRM and marketing capabilities. The integration of the Cegedim Strategic Data business enhances IMS Health’s capacity for connecting solutions across information, technology and services, with significant benefits for clients:

•

Deeper RWD assets and analytical expertise: IMS Health now brings clients even greater access to anonymous patient-level data (including in Europe and Australia) as well as commercial and medical-scientific analytical expertise, to deliver a consistent understanding of patient and treatment outcomes, costs and safety. Reinforcing the unparalleled breadth and depth clients can leverage in uncovering insights from IMS Health RWD, the collective offering includes:

• •

500+ million anonymous longitudinal patient data records in 25+ markets

Partnerships and data sourcing capabilities to ensure the ‘right fact base’

“ PAGE 4

•

• • •

Leading edge technology and analytics for faster data extraction, analysis and visualization Experts in 20+ markets with deep specialism in RWE, HTA and payer requirements to translate insights into actions 3,000+ publications building healthcare knowledge

Powerful new tools for end-to-end CRM: Bringing together IMS Health’s Nexxus™ Commercial Application Suite and Cegedim’s Mobile Intelligence CRM platform and Customer Engagement Hub provides the industry’s most comprehensive and fully connected set of applications – from marketing campaign and performance management to social media monitoring and compliance services. With interoperable applications using the same master data, commercial life sciences teams can send the right messages to the right customers at the right time through the right channels – making this a true multi-channel CRM solution. The result is more efficient commercial operations, including the ability for clients to easily integrate all their data sources through cloud-based master data management services.

Most robust healthcare reference: The incorporation of Cegedim’s OneKey into the IMS One™ cloud-based master data management platform establishes the world’s most robust healthcare reference database with insights on nearly 14 million providers across the globe.

The new technology, expanded information assets and additional services enabled by the acquisition reflect IMS Health’s ongoing commitment to drive healthcare performance through compelling, integrated solutions that reduce costs and help clients operate more effectively. For further information on Cegedim CRM and Strategic Data and the extended capabilities of IMS Health, please email Rob Kotchie at Rkotchie@imshealth.com or Adeline Meilhoc at Ameilhoc@fr.imshealth.com

This enables us to provide clients with even more options for realizing the value of RWD as well as leading-edge CRm and marketing capabilities.

”

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

NEWS EXTENDED RWE PLATFORM Acquisition of Dataline Software offers new potential for improved health outcomes and business performance

Extended RWE technology platform accelerates clinical and cost-of-care insights IMS Health’s technology-enabled RWE platform, Evidence 360™, brings together its vast library of anonymous patient-level data with other anonymous patient-level information sources to help clients understand, measure and interpret healthcare outcomes in near real time.

In a move that significantly expands the capabilities of Evidence 360, IMS Health has acquired Dataline Software, a leader in ‘big data’ analytics for healthcare. UK-based Dataline has worked closely with life sciences companies, payers, healthcare authorities and academia to deliver tailored software for the rapid analysis and elegant visualization of large, complex healthcare datasets.

Accelerated delivery of integrated insights

The combination of Dataline technology with IMS Health’s mission-critical information, global data management capabilities, and scientific and commercial expertise, offers clients an unparalleled portfolio of RWE solutions that accelerate delivery of integrated clinical and cost-of-care insights for assessing healthcare value and performance. Jon Resnick, Vice President and General Manager, RWE Solutions at IMS Health has noted that “Through this acquisition, we will expand our application suite, deliver exciting new visualization capabilities, and accelerate speed to insight – increasing the significant value clients realize from our RWE solutions.”

Treatment and outcome insights will be enabled by a number of new features on the Evidence 360 platform, including:

•

Enhanced search engine, supporting fast, secure access to data. Evidence 360 allows clients to search large volumes of anonymous patient data records in near-real time, covering legacy data storage systems as well as growing sets of newly onboarded data. The platform will incorporate Dataline’s patented algorithm designed for searching complex EMR datasets. Every system interaction and data change can be fully audited to help ensure regulatory compliance with European Medicines Agency (EMA) and Food & Drug Administration (FDA) requirements.

“

•

Improved R&D, clinical trial and observational studies capabilities. With the acquisition, IMS Health provides additional support to clients’ clinical trial research and operations activities. Evidence 360 applications effectively simulate trial designs and patient cohorts, enhance site selection and management, and enable electronic data capture with case report forms auto-populated from EMRs. Population projection across countries can help avoid costly protocol redesigns for clinical trials when patient populations are too small or unavailable. Together with IMS Health’s Clinical Trials Optimization Suite, Evidence 360 now offers market-leading technology solutions for evidence generation across the product lifecycle.

Sophisticated visualization tools to increase usability of insights. Enhanced visualization technologies generate clear, comprehensive reports detailing insights into patient pathways, treatment dynamics and clinical trial feasibility. New decision-support tools enable clients to assess which reports and analytics are most valuable to their organizations, while accessibility features ensure that information can be shared easily and securely across a broad set of users.

Adrian Bleach, founder and Chairman of Dataline Software has underscored the potential of the union with IMS Health: “At Dataline, we are proud to have developed and launched breakthrough software solutions for driving improved outcomes through the use of real-world data. We are excited to join IMS Health, where together we will contribute to even greater innovation and deliver meaningful insights to advance healthcare on a global scale.”

For further information on Dataline Software or IMS Health Evidence 360, please email Ben Hughes at Bhughes@uk.imshealth.com

This offers clients an unparalleled portfolio of RWE solutions that accelerate delivery of integrated clinical and cost-of-care insights for assessing healthcare value and performance.

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NEWS IMS INSTITUTE HEALTHCARE INSIGHTS Major new oncology findings head latest research into market dynamics from the IMS Institute for Healthcare Informatics

Studies identify new threshold for global spending on cancer and US spending on medicines An accelerating pace of change in cancer treatment and rapid shifts in the landscape are bringing new complexity to oncologists, payers and governments in their efforts to provide appropriate care whilst ensuring the sustainability of healthcare systems. This is according to a new study from the IMS Institute for Healthcare Informatics which reveals that global spending on oncology medicines – including therapeutic treatments and supportive care – has now reached the US$100 billion threshold.

The comprehensive review and updated perspective, “Developments in Cancer Treatments, Market Dynamics, Patient Access and Value: Global Oncology Trend Report, 2015”, published in May 2015, highlights the role of earlier diagnosis, longer treatment duration and increased effectiveness of drug therapies as contributing factors in the rising levels of spending on medicines for cancer care. Among its key findings are:

• •

Global oncology market continues to experience steady growth increasing 10.3% in 2014 to reach US$100 billion.

“The increased prevalence of most cancers, earlier treatment initiation, new medicines and improved outcomes are all contributing to the greater demand for oncology therapeutics. Innovative therapeutic classes, combination therapies and the use of biomarkers will change the landscape over the next several years, holding out the promise of substantial improvements in survival with lower toxicity for cancer patients.” Other recent topics covered by the IMS Institute include:

•

Targeted therapies account for nearly 50% of total spending but payers and national health systems have intensified their scrutiny of the value of these medicines relative to their incremental benefits over existing treatments, frequently resulting in limited patient access. Clinical outcomes are improving for major cancers with five-year survival rates rising in most cases through continuous and small improvements in detection and treatment refinements.

Patient access to cancer drugs varies across markets with patients in Japan, Spain and South Korea having access in 2014 to fewer than half of the new cancer drugs launched globally in the prior five years. In pharmerging markets, availability of newer targeted therapies remains low but is increasing. Even among wealthy countries, new drugs may not be reimbursed and consequently will only reach a very small number of patients. Patients are engaging social media and online networks throughout their cancer journey, the most frequent topics of discussion being treatment options and financial concerns. Access and reimbursement issues are likely to become more complicated in coming years as individual and combination oncology medicines address multiple cancer types and patient populations with varying dosage and clinical value.

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•

April 2015: Medicines Use and Spending Shifts: A Review of the Use of Medicines in the US in 2014. This report brings together perspectives on total system spending on medicines at an aggregate and segmented level; the evolution of healthcare demand, delivery and payment systems; patient out-of-pocket costs for medical and pharmacy benefits, including retail prescription copays; and transformations in disease treatment resulting from newly approved medicines. The analysis revealed a record-setting year for US healthcare with the highest ever levels of spending on medicines, due in large part to increased demand for new specialty drugs, a record number of transformative treatments and fewer patent expiries.

April 2015: Understanding the Role and Use of Essential Medicines Lists. As the move towards universal health coverage strengthens so does the role of essential medicines (defined as those that satisfy the priority healthcare needs of the population). This report summarizes how the WHO Essential Medicines List has changed and the process by which the model list is revised. It describes the ways in which the list is used by national health systems in developing their own compilation of essential medicines, reviews and compares the national lists for a range of countries and the factors affecting local implementation, and provides considerations for future revisions of the WHO model list.

December 2014: Impact of Cost-per-QALY (CPQ) Reimbursement Criteria on Access to Cancer Drugs. This report considers the impact of alternative approaches to reimbursement decisions on patient care in cancer, comparing five CPQ countries (Australia, Canada, England, Scotland, Sweden) with five non-CPQ countries (France, Germany, Italy, Spain, USA). The findings identify differences in decision times, reimbursement, access, and historic adoption of new cancer drugs as well as many uncertainties and inconsistencies in CPQ analyses. Correlations indicated between reimbursement of new cancer drugs and cancer survival rates raise several questions for future research.

For further information on these reports and other insights from the IMS Institute for Healthcare Informatics, visit www.theimsinstitute.org. For specific information about the Global Oncology Trend Report, email Rob Kotchie at Rkotchie@imshealth.com

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Introducing the RWE Ecosystem Anonymous patient-level data might seem a bit chaotic: sitting in different places, subject to different rules, created for purposes that are different than how we want to use it. But at IMS Health we can create structure and order. We can find ways of building intelligent access to, and insights from, this data that advance knowledge without compromising patient privacy and protections. We can leverage advanced analytics, technology, data management approaches, and other innovations to bring relevant data together for you and other stakeholders. This provides the scientific evidence needed to support your products’ value proposition, safety, access and price. And we can help you make better commercial decisions with it as well.

Every function can benefit from an organization’s strong RWE ecosystem by creating a more consistent, insightful view of the real-life healthcare system in which it operates. It truly brings R&D, HEOR, drug safety, brand teams and sales forces together to determine how patients are treated today, what outcomes they experience, and where the gaps are still to be filled. They can apply this understanding to inform their own plans - a common currency for evaluating opportunities and challenges. Implementing an RWE Ecosystem is not an incremental move for manufacturers – they are leapfrogging the innovation cycle to bring cures to patients. For further information on realizing the potential of the RWE ecosystem, please email Jon Resnick at Jresnick@imshealth.com

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INSIGHTS RESEARCH & DEVELOPMENT

Realizing clinical trial efficiencies using real-world data A new study from the University of Chicago1 posits that improvements in pharmaceutical R&D productivity can be seen in both the health benefits that new innovations bring as well as the extended applications of existing molecules. Of the approximately US$110 billion the industry spends each year on global R&D,2 60%3 is devoted to the clinical trials that would generate the evidence needed to support such advances. Investment in searching RWE and applying advanced analytics brings potential to realize significant savings through an enhanced and more efficient study process.

The author

linda Drumright, bA is General Manager, Clinical Trial Optimization Solutions, IMS Health Ldrumright@us.imshealth.com

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Opportunity gains from planning through to study execution Most companies are looking to improve the efficiencies of their randomized clinical trials (RCT) to decrease the ballooning costs of executing them and increase resources to explore additional applications for existing molecules or launching new ones. They see opportunities in addressing recruitment delays, unproductive sites and the starts and stops of protocol changes: • • • • •

Approximately 80% of all RCTs are delayed by more than one month

Around 30% of all investigative sites fail to enroll more than one patient;4 each site costs, on average, US$30,000 to initiate5 In phases II-IV, there are an average of 2.9 amendments per protocol; one third of these are considered avoidable,6 costing the industry US$5.4 billion each year Protocol design flaws and recruitment difficulties are responsible for 20% of protocol amendments6

Each protocol amendment carries an average price tag of US$450,000 and causes a trial to be delayed by an average of 61 days6

Given these statistics, it is clear that eliminating protocol design flaws and overcoming recruitment difficulties have the potential to yield significant savings for the industry − more than US$1 billion per year − in avoidable RCT costs. That is without taking into account the value of eliminating go-to-market delays and other costs associated with poorperforming RCTs.

The opportunity to improve RCTs starts as early as planning but certainly continues through initiation and execution. The following sections explain the improvement opportunities and illustrate their potential when applied in practice.

Planning

Protocol feasibility validation Experts often design RCT protocols based on the science in an applicable therapeutic area without an understanding of the operations of clinical care or detailed patient demographics. These factors can cause ripple effects that increase operational costs and/or actually make it too difficult for trials to meet their recruitment targets. Typically, study designs are reviewed by cross-functional committees with representatives from numerous departments (eg, clinical research, drug safety, regulatory affairs, quality assurance) to ensure that they will be safe for patients, are scientifically sound and will test for the appropriate endpoints. Unfortunately, the question of whether the study will be easy to execute is left until the end of the protocol planning process.

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This sequence of events often proves costly because the study’s inclusion/exclusion criteria can make patient recruitment extremely difficult. Provision of that information as an input to protocol design would enable the experts to understand the cost-benefit implications of addressing those challenges. This can be achieved by consulting secondary data sources that present real-world evidence (RWE) on the prevalence of patients with particular conditions, clinical attributes, treatment profiles and demographics.

By tapping diagnosis and treatment details on millions of anonymous patients in these databases, researchers can quickly address the drivers that most impact recruitment, by:

• • • •

Confirming that the target patient actually exists

Determining where patients fitting the criteria can be found

Understanding the impact of each criterion on potential patient populations

Identifying a concentration of patients for a manageable site-enrollment process

This ‘reality check’ is cost-effective given the time and cost savings it enables by avoiding patient recruitment delays and associated issues. A preventable patient shortage One sponsor company was forced to revise its oncology clinical study protocol three times after encountering recruitment challenges. IMS Health performed a retrospective feasibility study to determine whether a ‘reality check’ database search could, indeed, have predicted the shortage of eligible patients that had repeatedly delayed the study and escalated costs.

This search immediately highlighted one particular inclusion criterion as being at fault. As shown in Figure 1, the number of eligible patients dropped precipitously once a requirement for patients to express the KRAS mutation was applied. KRAS was far more prevalent in US than in EU populations – or at least identified less often in Europe because the screening test was not used routinely by diagnosticians.

Having this insight during design would have enabled the clinicians to ascertain the significance of the mutation. If it was important, they could have then explored efforts to increase diagnosis as part of their activities. See Figure 1 overleaf...

continued on next page

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INSIGHTS RESEARCH & DEVELOPMENT

Figure 1: Study feasibility stacked criteria in oncology Number of current NSCLC pts by country Projection Factor

INCLUSION CRITERIA Pts aged =>21 years

Locally advanced or metastatic (IIIB-IV) KRAS mutant

Current 2L NSCLC LOT pts †

Non-relapsed

1L in advanced disease stopped due to progression or toxicity (side-effects) ‡

B Relapsed after 1L ‡ 3

A+B pts combined

WHO performance status 0-1 EXCLUSION CRITERIA Brain metastases

HIV positive

Mixed SCLC/NSCLC histology Total Applicable Patients

(2L mNSCLC, mutKRAS, >21yrs, relapsed or failed 1L therapy)

FRANCE

ITALY

SPAIN

Sample No. Projected Pts.

1114

41.80

4656

1088

46565

2006

906 18 15

944

932

58047

872

57309

854

61.49

37871

699

42982

752

123

627

13 1

799 61 0

732 6

30898

26484 217 0

167

125 84

31546

36.18

The number of eligible patients dropped precipitously once a requirement for patients to express the KRA mutation was applied.

Country selection and allocation

Another important consideration in plan design is country selection as well as the level to target enrollment in each country. Four factors that need to be understood are: 1. Prevalence of eligible patients in the country

2. Performance of sites in the country in past trials

3. Locations where patients are treated (to determine required number of sites to meet patient enrollment targets) 4. Similarity of treatment patterns (to assess feasibility of enrollment)

Fortunately, these factors can be easily addressed with existing datasets. Global consumption datasets that measure worldwide drug sales and prescriptions can be coupled with anonymous patient-level data from sources such as physician surveys that track the incidence of disease. This approach provides a more precise way to find geographic clusters of patient groups treated for specific diseases versus consumption data alone. The resulting index of patient prevalence can then be referenced to an index of each country’s market value and an analysis of the sponsor’s prior experience, to determine a country’s suitability as a trial site. The availability of internal resources as well as country-specific regulatory and operational hurdles are other important considerations for making a well informed decision on study placement. Treatment patterns can also be determined using this data. For example, frequency of certain drug use and location of care provision can be matched to diagnosis codes to verify that published guidelines appear to be followed.

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Evidence belies opinion A sponsor company tried to manually assess patient availability. Specifically, it asked 21 country affiliates to survey physicians on their ability to deliver patients with a particular cardiovascular diagnosis for a trial. Each country spent an estimated 10 hours over four weeks gathering the information.

In parallel, IMS Health estimated patient availability using a database of prescription volume for the diagnosis. Resulting counts were then divided by the number of urban square miles for each specific country to normalize the data and remove the complicating factor of finding patients that were spread too thinly across the geography. Figure 2 shows that while the two methods produced similar results for most countries (albeit with vastly different effort and elapsed time), there were some noteworthy discrepancies. For instance, physicians in Thailand had been quite confident that they could meet the patient quota. However, one of the medications in the inclusion criteria was rarely prescribed in Thailand; the IMS Health analysis had placed Thailand near the bottom of the list. Conversely, investigators in the UK believed they would have a very hard time finding suitable patients; the data revealed that the country had the second-largest eligible population.

See Figure 2 opposite...

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Figure 2: Comparison of country ranking methods for RCT recruitment Country USA

IMS Rank

Sponsor Rank

Rank Diff 15

Brazil

Argentina

Czech

Germany

Poland

Hungry Mexico

Netherlands Italy

Korea

Slovakia

Peru

Thailand

11 6

9 7

Canada

South Africa

Spain

Australia

France

Philippines

19 21

An opinion vs. database approach to assessing patient availability yielded largely consistent results but with noteworthy discrepancies that supported the use of real-world evidence. Endpoint definition and indication targeting The science is usually clear about which endpoints are required to demonstrate efficacy and safety. However, at a time when RCTs are also being used by payers to inform price and reimbursement assessments, they must support more than regulatory submission. RWE can play a key role in helping to prioritize claims by assessing frequency of challenges, cost implications and the value of potential benefits. For example, by looking at anonymous patient-level data, manufacturers can track how many different encounters patients have with the healthcare system. This insight can enable trials to show improvements that could lead to cost offsets that might not be generally understood. Social media analytics, as another example, could highlight Quality of Life (QoL) endpoints that patients would value.

It can also inform the prioritization of new indications by determining the size and level of unmet need where science suggests that a product could be potentially useful. And in areas where the manufacturer is innovating beyond established literature and guidelines, RWE can provide a more robust assessment of primary and secondary endpoints. This not only dramatically changes the risk discussion of RCT design but also serves to make the RCT investment better support a product’s potential to actually reach patients, by addressing payer and provider questions.

Initiation

Site selection and investigator recruitment Traditionally, sponsor companies and Clinical Research Organizations (CROs) have used a number of methods to create a target list of potential clinical investigators, including:

• • • •

Relying solely on investigators who have successfully completed prior trials Purchasing lists of physicians

Accessing data on other studies from regulatory agencies Consulting publically-available population data

About 30% of the sites enlisted using these targeting methods provide at most one patient. This result partly reflects information sources that only offer clues as to whether a physician will enroll patients in the current trial or where there are high concentrations of people with a given condition. They do not quantify with any precision the volume of eligible patients that a given investigator treats – patients who are profiled according to their prior medication use (which can be an exclusion criterion), actual disease state or demographics. By also tapping longitudinal patient-level databases, there are now ways to identify far more definitively which physicians have the best patient population for a study. These approaches are being proposed here for the purposes of clinical research and are not intended to inform a discussion about promotion.

Prioritizing physicians by deciles based on prescribing volume In the US market, a combination of medical claims and pharmacy data can be used to identify precisely the physicians who have the best patient population for study, as determined by patient diagnoses, medical procedures and prescriptions. In other markets, where only anonymous patient-level data collected from pharmacies is available, the patient’s diagnosis must – and can – be inferred from what is known from the prescription record. This is a straightforward process if the disease under study is treated almost exclusively by one physician specialty or if a particular drug is used for a single indication. In these cases, the physicians in the pharmacy prescription transactions database can be simply sorted into deciles to find those with the highest volume of prescriptions written or therapies initiated in a certain drug class without compromising patient privacy. Using predictive models to estimate patient counts In cases when a drug is used to treat more than one condition, the diagnosis must be determined through a combination of the physician specialty and other attributes (eg, patient age, average daily dose of the medication from anonymous patient-level data). Once the factors associated with a diagnosis are established, a predictive model can be created to estimate the number of patients being seen by an individual prescriber for a particular condition. Another predictive modeling approach involves using health plan data to isolate anonymous patients with a clean diagnosis. Those patients and the physicians who treat them are then profiled using an array of attributes from patient age and gender, to physician specialty and geography, to medication history, daily dose and payment method.

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INSIGHTS RESEARCH & DEVELOPMENT

This analysis highlights those factors that are both high and low predictors of the diagnosis. The next step is to create a statistical model capable of predicting the diagnosis in question when applied to the longitudinal prescription data. The goal is to be able to place individual physicians listed in the pharmacy prescriptions transaction database into deciles, based on the estimated

volume of patients having the particular diagnosis and desired patient demographics. To test how well the model performs, it is applied to the subset of this database for which claims data also exists, comparing the model projections with the diagnoses actually contained in the claims database.

Patient counts by physician analysis boosts site enrollment A top specialty pharmaceutical company focusing on rare disorders with high unmet medical needs engaged IMS Health to help rescue an underperforming phase III clinical study for the orphan indication of hypoparathyroidism. IMS Health was able to match de-identified patients within its longitudinal patient database to research physicians seen for the target indication.

The database search identified 363 research physicians who had treated 1,588 unique patients meeting the specified guidelines for diagnosis, age and gender over a 24-month look-back period. All physicians identified were cross-referenced against the FDA 1572 database to verify their research experience. A search was also carried out within a certain radius of existing active sites to identify another 2,688 potential referral physicians treating patients of interest. As a result, a number of additional sites were enlisted to the trial and the sponsor enrollment was completed on time.

Enrollment

Planning, tracking and scenario modeling Patient enrollment is a pivotal success factor for any clinical trial, including its overall expense and timeline management. Study managers are increasingly looking to develop more realistic recruitment plans, track enrollment progress more tightly and activate contingency plans (because even solid enrollment plans require adjustment from time to time). These efforts include the potential deployment of early-warning systems, which are common in manufacturing industries, using repeatable sourcing and production processes. Sponsor organizations have traditionally used home-grown solutions and spreadsheets as their tracking mechanisms with few, if any, planning systems. These tools, however, are inadequate. Spreadsheet software has a limited ability to aggregate data, does not scale across a distributed organization and thus fails to provide insight into problems that may be looming. The result is that too often, enrollment timelines are initially based on unrealistic assumptions and then, during execution, issues such as high screen-failure rates and unproductive sites are not caught until they have already derailed the plan. When equipped with more sophisticated tools, automated enrollment planning and tracking and site performance analysis and selection, study managers can:

• • •

Define comprehensive enrollment plans, model various scenarios and establish a baseline for the study

Validate plan assumptions against historical enrollment and investigator performance data

Monitor trial enrollment performance against the plan in real time at the study, country and site level with the ability to:

• •

Identify and diagnose variances to the study plan

Understand, monitor and adapt to site performance in real time

Figure 3: Driving enrollment predictability

% of studies on/ahead of time

65% 60% 55% 50% 45%

Client mandates use of IMS Health solutions for all studies

40% 35%

Pilot 30% Year 1

Year 2

Year 3

Through streamlining data sources and implementing consistent planning practices, the company achieved a 100%+ increase in studies recruiting to plan and reduced non-performing sites by 33% Source: IMS Health

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

• •

Model rescue scenarios to evaluate the impact of changes in terms of time and cost before taking action

Capture and leverage data on the performance of sites and investigators for future trials

Predictable enrollment delivered on or ahead of plan One sponsor company suffered from systemic enrollment delays across its portfolio and was under immense pressure to reduce costs and manage capacity. Replacing a home-grown, spreadsheet-based solution, it streamlined its data sources into IMS Health StudyOptimizer™, implemented consistent planning practices across the organization, and trained and mandated on use of the application from planning through execution. Year-on-year, the number of studies recruiting on or ahead of plan has been one of the most consistently improved annual metrics for the company: to date, it has realized a 100%+ increase in studies recruiting to plan (Figure 3). Planning processes now involve the creation of multiple scenarios, vetted against its own historical performance as well as industry data in Enrollment Benchmarks, with a formal baseline against which it consistently monitors, tracks and guides to completion.

Conclusion

These applications individually provide a sense of how RWE can make important, albeit incremental, improvements in clinical trial design. But the bigger opportunity is to develop better questions to answer through RCT as well as more informed ways to answer them. R&D organizations can use RWE to understand current treatment dynamics and outcomes in terms that other stakeholders care about (eg, costs, quality of life) as well as in ways that will provide more quantitative insights than just relying on literature and key opinion leader discussions. By understanding how and where patients are treated, protocol development and site selection can be more efficient. Thus, innovator companies can easily prevent millions of dollars in waste and delays. Investment in searching RWE and applying advanced analytics to guide protocol development, country allocation, site selection, and recruitment planning and tracking is money well spent. For a company that runs 100 RCTs per year, these proactive measures can save US$26 million in trial amendment costs alone and recoup vast amounts in opportunity loss from launch delays, a substantial opportunity even before considering the opportunity to develop more valuable treatments.

Further, the company has realized a reduction of 33% in non-performing sites by first leveraging historical investigator performance information captured by StudyOptimizer™ to choose higher performing sites during the early planning phases of its trials. As well, real-time information about investigators’ actual performance has been leveraged by site monitors during execution to drive higher performance based on data-driven discussions with participating sites. The company has automated the transparency and visibility of trial performance throughout the organization, thus improving the efficiency and productivity of upstream and downstream functions. It estimates annual savings in the region of US$38 million in these two metrics alone.

“ 1 2 3 4 5

For a company that runs 100 RCTs per year, these proactive measures can save US$26 million in trial amendment costs alone, even before considering the potential to develop more valuable treatments.

”

Hult KJ. Incremental innovation and pharmaceutical productivity. PhD Dissertation, Department of Economics, University of Chicago; 2015 EFPIA, 2011. Pharmaceutical R&D expenditure (2010 estimates) projected to global using IMS Health data

PhRMA Industry Profile 2006 Thompson CenterWatch analysis

Getz KA. Enrollment performance: Weighing the "facts". Applied Clinical Trials, May 01, 2012; 21(5)

Scrounging your first study. In: Stone J. Conducting Clinical Trial Research: A Practical Guide for Physicians, Nurses, Study Coordinators and Investigators. 2nd ed. Mountainside MD Press; 2010. Available at: http://conductingclinicalresearch.com/sample_chapter.php. Accessed 29 April, 2015. Tufts Center for the Study of Drug Development Impact Report, Tufts University, 2011, Sept/Oct; 13 (5)

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PROJECT FOCUS RESEARCH & DEVELOPMENT

EMR as a highly powerful European RWD source for R&D The value of RWE to improve clinical trial operations and mitigate risk – a case study of leveraging EmR data in Europe. As discussed in another article in this issue of AccessPoint (see page 8), the benefits of using more robust insights from RWD include lower clinical development costs and avoidance of delays. The RWE-related solutions all had a common theme of providing more information about how the patients experienced healthcare: where they were, how they were diagnosed, how they were treated and what outcomes they experienced.

This article discusses a novel approach for supporting a clinical trial in Europe using EMR data to dramatically improve a clinical trial process and outcome.

Caveat about real-world data sourcing

A core belief about RWE in IMS Health is that the RWD used should best answer the question being asked. There is not a single superior data source and there are always trade-offs between breadth and depth. But critical factors to address in designing feasible clinical trials in Europe do nicely lend themselves to EMR data. For example:

• •

•

Finding the right population of patients, especially in terms of inclusion/exclusion criteria. EMR data provides the clinical variables needed to assess how many of those patient groups actually exist. Evaluating the number of sites, helping weigh a trial approach’s recruitment potential per site with other factors such as: KOL involvement; market penetration and regulatory strategy; production & distribution chain constraints. The EMR data can be looked at in aggregate to understand both the size of a site’s potential population as well as how it compares to other sites, to provide a relative rating.

Defining the right populations when the literature and KOLs do not agree. As manufacturers look to develop and launch more innovative drugs, often the broader understanding of the disease is still evolving. EMR data can provide a more objective view of patient characteristics associated with investigated conditions.

The author Adeline Meilhoc, MSC is Vice President, RWE Solutions, IMS Health Ameilhoc@fr.imshealth.com DUS requirements to characterize the prescribing practices of medicinal products during typical clinical use in representative groups of physicians while assessing the main reasons for the prescription. Common primary endpoints provided by EMRs are:

• • •

Demographic and clinical characteristics of treated patients, including co-medication and co-morbidity

Indication for which the product is prescribed in routine clinical practice

Average duration of treatment episodes and the daily doses prescribed according to the route of administration

Case in practice: Cardiovascular disease

The ability to determine requirements for clinical trials in a niche cardiovascular indication (statin intolerant) was challenged by lack of consensus between experts and KOLs regarding the exact definition of this patient population. An analysis was therefore conducted using RWD datasets to determine specific needs for the trials. Methodology

RWD EMR databases covering the top 5 EU (France, Germany, Italy, Spain, UK) (see Table 1) were queried in a two-stage process to (1) determine the profile and number of patients needed and (2) to target and pre-select recruitment sites. In France, the RWD sources included GPs and an additional panel of cardiologists.

EMRs, especially when longitudinal data collection is utilized, are informing research questions along the entire product development continuum. RWD is used to support

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Figure 1: Criteria applied to patient selection

Patient with at least 3 years of medical historical data Patient treated at least 1 time with statin 2 years prior index date Patient initiated with statin within 2 years prior index date Patient who has stopped statin treatment for at least 6 months Patient who presents at least 1 of the following factors in their medical history • Combination of at least 2 atherothrombotic risk factors • Cerebrovascular disease • Coronary disease • Symptomatic peripheral arterial disease Step 1

Conclusion

The first step had three key goals:

1. Characterize and quantify the number of patients to be included in the clinical trials (Figure 1) 2. Validate the patient recruitment hypothesis

3. Establish the best healthcare professional and site profile able to recruit such patients (GPs, specialists, hospitals, etc). Step 2

The second step (Figure 2) was to target and pre-select high potential sites to include in the clinical trials.

The use of RWD brought clarity around the statin-intolerant definition and allowed the inclusion/exclusion criteria to be framed. This provided an evidence base for recommendations to enhance the clinical strategy and ensure that the number of required sites to be involved would not fall short. The ability to achieve this is of major importance within the context of rising costs and limited R&D resources and in avoiding unexpected requirements to boost patient recruitment or complete a rescue study. Shrinking R&D budgets and challenges for funding the new drug development process provide impetus to explore and utilize RWD as a source that is ripe for application to support the achievement of efficiency savings.

continued on next page Figure 2: Number of patients per doctors

300

No of doctors

250

200

150

100

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8 9 10 No of patients

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PROJECT FOCUS RESEARCH & DEVELOPMENT

Table 1: IMS Health RWD EMR in Top 5 EU - collected variables

Demographic Data

Variable Gender

Yes

Year of birth

Yes

Partial

Yes

Partial

Ethnicity

Partial

Death recording

Yes

Partial

Registration date

Yes

“Transferred out” date

Yes

Partial

Exercise

Partial

Lifestyle

Partial

Height

Yes

Weight

Yes

Blood pressure

Yes

Date of events (consultation)

Yes

Home visit

Partial

Risk factors

Yes

Medical history

Yes

Signs and symptoms

Yes

Drug

Yes

Diagnosis

Yes

Duration of script

Yes

Dosage

Yes

Cost

Yes

Partial

Yes

Reimbursement

Yes

Generic name

Yes

Prescription by brand name

Yes

Drug safety

Yes

Prescription by molecule

Yes

Repeat

Yes

Allergies

Yes

Immunization

Yes

Lab & X Ray exams rx

Yes

Lab & X Ray exams results

Yes

Referrals

Partial

Yes

Partial

Yes

Hospitalization

Partial

Yes

Partial

Reasons for hospitalization

Partial

Socio-economic status

Additional Health Data

Drug Prescription

Biometric, Medical Data

Diet

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Enabling clinical trial expansion for a rare disease using US RWD Innovative methodologies leveraging real-world data can inform, strengthen and support expansion of critical drug research and development programs. Randomized controlled trials (RCTs) are the mainstay for demonstrating the safety and efficacy of medical technologies and for advancing healthcare worldwide.

While increasingly demanding across all therapy areas and geographies, the challenges they present are especially acute in the case of rare diseases,1 where small populations, limited clinical expertise, and scarcity of specialist treatment centers pose particular problems for physician and patient recruitment.

To date, few innovative approaches to facilitating research in rare diseases have tapped the potential of observational data.2 However, for one IMS Health client, the creative application of several large, real-world databases proved key to expanding its clinical development program, both strengthening the power of an existing RCT and revealing significant new patient and knowledge clusters for its future research in this area.

background

The company was pursuing a RCT in patients with a rare disease and was keen to identify further sites in the USA, including both patients and physicians, in order to expand its research program. Specifically, there was a need to identify:

• • • •

Additional patients with the rare disease

Subset of eligible patients meeting the trial’s inclusion/exclusion criteria

Physicians diagnosing and/or treating the condition

Metropolitan areas and institutions with a concentration of patients/physicians

To meet these objectives, the company required an approach that would first pinpoint patients diagnosed with the disease and then enable both patients and physicians to be affiliated and ‘rolled up’ to local hospitals so that these possible ‘hot spots’ could be compared nationally for their potential as trial sites. However, the rarity of the disease, combined with key inclusion criteria, made the process of identifying eligible patients a complex challenge. 1 2

The author Robert Steen, BA, BS is Principal, CES, IMS Health Rsteen@us.imshealth.com

Innovative application of RWD

With access to the broadest, deepest collection of scientifically-validated RWD sets and the analytical expertise to apply them to complex challenges, IMS Health took a three-staged approach to find clusters of physicians and patients. This involved sizing the national patient population; mapping these patients to their physicians; and affiliating the physicians to local institutions through the use of a density analysis. 1. Sizing the national patient population with inclusion criteria

The first step in sizing the national patient population was to extract anonymous patient-level data from IMS RWD Claims−US, the most comprehensive integrated US health claims database available, using the ICD-9 diagnosis code for the disease in question (Figure 1).

Fully adjudicated claims were analyzed for the period from June 2012 to May 2013. A 12-month period prior to and post these dates (June 2011 to May 2014) was then used to find a second instance of the same diagnosis code to confirm the accuracy of the original. Several additional inclusion and exclusion criteria were applied, including administration of diagnostic tests and intravenous drug treatment, based on HCPCS codes (Healthcare Common Procedure Coding System). Using these additional ‘flags’, the patient population was narrowed down to more closely represent the segments being targeted. These ‘raw’ populations then formed the basis of national projections which provided the client with a customized perspective on the likely size of its intended patient population.

continued on next page

A rare disease is defined in the US as one that affects fewer than 200,000 Americans and in Europe as one that affects fewer than 5 per 10,000 of the population. Gagn JJ, Thompson L, O’Keefe K, Kesselheim AS. Innovative research methods for studying treatments for rare diseases: Methodological review. BMJ, 2014;349:g6802. Available at:http://www.bmj.com/content/349/bmj.g6802 Accessed 14 April, 2014.

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PROJECT FOCUS RESEARCH & DEVELOPMENT

Figure 1: IMS RWD Claims−US patient-level database

IMS RWD Claims–US patient-level database

Pharmacy Claims Data

Medical Claims Data

Pharmacy claims are derived from a subset of the IMS Health prescription database and provide robust coverage across pharmacy channels.

• • •

Retail Pharmacy

Diagnosis Claims

Specialty Pharmacy

Procedure Claims

Mail-order Pharmacy

Lab Values

Over 65% of all retail prescriptions in the USA are catured within the database as well as over 55% of traditional mail-service and 45% of specialty pharmacy transactions Database contains over 150 million unique anonymous patients

Over one million unique prescribers are captured within the database

Medical claims are derived from electronic routing of medical office claims through practice management software and third-party electronic switches to health insurers or web service providers.

• • • •

Over one billion claims are received per year

Data is collected from 865,000 practitioners per month

Patients and providers are demographically and geographically representative All major payer types are represented

IMS RWD Claims−US was leveraged to conduct the market sizing analysis and identify the targeted clinical population

Next, the process was repeated using IMS RWD LRx−US prescription data to understand how patients were being treated − the drugs in use having been researched and confirmed by the IMS Health clinical team. As before, an index and look back/look forward periods were used to identify the variety of treatments prescribed.

An index period of June 2012 to May 2013 was used to identify the diagnosis code, and a post-index period of June 2013 to May 2014, to flag instances of drug therapy use. These counts were then projected nationally. Patients were grouped according to their first-, second-, and third-line treatments to identify those who had received treatment and subsequently progressed to a later stage of disease. This information, combined with the various ‘flags’ included in the diagnosed population from the medical claims data, enabled the potential size of the target population to be more accurately gauged for potential future clinical trial designs. 2. Locating diagnosing and treating physicians

Since the adjudicated claims are based on the CMS-1500 claim form, isolating the patient population also identified the physician involved. This enabled aggregation of specific counts of diagnosed patients who had two or more office visits during the three-year period, according to physician. The client was then in a position to compare this list of physicians with its own internal information for consideration with regard to targeting as well as potential clinical investigators.

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A similar process was used to identify patients receiving drug therapy since the treatment data also included the prescribing physician. Taken together, the list of physicians who had diagnosed and/or treated patients for the condition provided a valuable reference for clinical planning, communication and promotion applications. 3. Creating density analysis

Next, the identified physicians were aligned to local hospitals using IMS Health’s Healthcare Physician Services reference data. This enables doctors to be affiliated with local institutions based on their attending/admitting privileges. The assumption made here is that these will be the hospitals where the diagnosed patients will be treated for any acute aspect of their condition. By ‘rolling up’ the counts of physicians with their respective patient counts, IMS Health was able to generate a density analysis to show which hospitals across the country had significant clusters of relevant physicians and patients (Figure 2). These groupings could then be analyzed by the client to identify potential future clinical trial sites as well as new areas for increased promotion and targeting efforts.

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Figure 2: Top 20 facilities diagnosing and/or treating the rare disease

Unique Treating and/or Diagnosing

Treating

Diagnosing

80 70 60 50 40 30 20 10 0

Top facilities by number of doctors Source: IMS Health

Use of custom analytics for clinical and commercial applications

Through the innovative use of related RWD − medical claims, longitudinal prescription information and physician-hospital reference affiliations − IMS Health was able to identify clusters which could serve as a potential list

ACCESSPOINT • VOLUME 5 • ISSUE 10

of new trial sites for future research studies in the rare disease, and a physician list of potential new contacts who could serve as investigators. Critically, too, the analysis shed new light on the disease for the client, providing previously unknown insights into diagnosed patients, treatments and experienced physicians, at both national and sub-national level.

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INSIGHTS RESEARCH & DEVELOPMENT

Helping the R&D function integrate RWE into clinical development With greater application of RWE throughout the pharmaceutical lifecycle, learnings are emerging that oﬀer guidance for approaches to derive the maximum value. This article captures the author’s experience at a leading international biotech, with insights for smoothing RWE assimilation into clinical development and realizing the beneﬁts it brings.

The author

Joel Kallich, PHD is Principal, Big Health Data Jkallich@bighealthdata.net

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Practical insights for aligned, more accurate decision making “What follows is a discussion of how RWE worked for me in my role as a bridge between R&D and commercial in a leading biotech. This may not work the same in other companies but I believe there are some principles that transcend a single case study. Whether it was bringing regulatory and reimbursement RWE issues to the attention of commercial teams or helping R&D appreciate the need for evidence of product value, it was all about proof. And when each function appreciated the challenges of the other, a successful product launch could be ‘almost’ guaranteed.” Understanding the issues

1. R&D productivity/revenue decline

Without considerable increases in R&D efficiency, the pharmaceutical industry’s health and wellbeing may be in great peril.1 This shortfall in R&D productivity and associated revenue is rooted in the growing focus on addressing unmet therapeutic needs and unexploited biological mechanisms − areas where the risk of failure is particularly high. At the same time, the pharmaceutical industry has been shedding jobs, primarily in R&D and reportedly in excess of 100,000 over the last three years.2

With fewer but more innovative products addressing smaller patient populations, as well as fewer researchers, increasing the price of each product to achieve overall profitability has created even more pressure for justifying value and moderating the prices being charged, as in the case of Sovaldi (sofosbuvir).3

The challenge is actually two-fold: (1) to increase efficiency while decreasing costs in drug development and at the same time (2) to increase the quality, breadth and depth of evidence supporting a product’s value. Note that ‘value’ here also includes the safety profile, sometimes referred to as the benefit-risk ratio of the product. Thus, the current process of discovering and successfully developing a new medicine needs substantial upgrading to enable very large increases in efficiency and decreases in R&D costs. 2. The digital revolution in healthcare

Alongside the crisis in clinical drug development is a revolution in information technology that is shaking the very foundations of healthcare delivery in the US. This is illustrated by the fact that in 2011, almost three quarters of all US hospital outpatient departments reported using an electronic health record (EHR) − a 60% increase since 2006.4 One result of this greater use (Figure 1) is an overload of production and dispersion of health information and data from a cacophony of sources.

continued on next page

Figure 1: Hospital outpatient departments with EHR technology able to support selected Stage 1 Meaningful Use Objectives: United States, 2007-2011

Recording patient history and demographic information

100 86.5

83.4

Percent

83.9

77.4

76.0

70.4 61.9

60.3

55.1 41.3

47.5

60 39.2

40 27.6 20

39.5 31.8

45.7

37.2

34.0

26.8 20.6 20.5

26.1 25.5

28.4 27.4

2007

2008

2009

Recording patient problems list Ordering prescriptions Providing warnings of drug interactions or contraindications Providing reminders for guideline-based interventions

0 2010

2011

NOTES: All trends were significant (p<0.05) except for recording patient demographics. EHR=Electronic Health Record. Information on 5 of 14 Stage 1 Meaningful Use objectives was collected in the National Hospital Ambulatory Medical Care Survey from 2007-2011. Source: CDC/NCHS, National Hospital Ambulatory Medical Care Survey from 2007-2011

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INSIGHTS RESEARCH & DEVELOPMENT

An unexpected consequence is that almost all randomized clinical trials (RCTs), the foundation of evidence-based medicine, pharmaceutical development and marketing approval, now rely upon retrieving data of uncertain quality from electronic administrative systems.

However, these data sources are crucial, not only for conducting RCTs but also for understanding the value of pharmaceuticals and their place in efficient healthcare delivery based on real-world practice. Companies must not only cope with this flood of information but also access and harness it to improve the efficiency and perceived value of the innovation effort. RWE is the process of integrating these data sources and conducting studies that provide comparative cost-effectiveness, ie, cost and quality outcomes − the key components of the healthcare value equation.

A personal perspective

These opportunities and challenges were recognized relatively early at my company when it began working with electronic medical record (EMR) data in 2004 to understand the penetration of injectable products into the population with appropriate medical need, while our clinical trial (CT) management organization became concerned about the integrity of EMRs to deliver robust data for RCTs. Our quality assurance department in clinical development took considerable effort to audit data systems in some of our trial sites.

While the benefits of RWE and an integrated data platform for R&D may be apparent to some, it is no easy task for an organization that considers RCTs their most important deliverable for the company’s success to incorporate RWE into clinical development. Real-world databases must compete with funds for running very large and expensive RCTs that are still needed for marketing approval. Moreover, the knowledge and experience required to succeed in the RCT domain is not the same as that in the observational data world. Finally, RCT is considered the gold standard for evidence of causality, so the case needs to be made for building more evidence of effectiveness in real-life settings.

What to do – as easy as falling off a log

Bringing change to an organization that has been built to deliver RCTs for drug approval is thus a special challenge but there are some good principles and rules for effective project management. 1. Frame RWE as a supplement and support to the RCT

A key point to stress is that the overall success of the company, and specifically the individuals who have led the R&D endeavor, rely upon the RCT; do not attempt to argue that it can be replaced with RWE.

Further, it is important to show proper deference for the difficulty in building the CT management organization and how it can be assisted. Most people appreciate having their efforts and knowledge respected and valued as they are shown how things could be incrementally improved. RWD and its insights have many applications in the clinical development process but overselling the benefits of RWE, for example to clinical trialists (typically MDs specializing in designing, writing and executing protocols), can backfire badly; efforts to assist can be easily viewed as competition.

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The following are two examples of how RWE can perform a supporting role that improves the efficiency and effectiveness of the RCT program. While making these points is important, many decision makers will require more extensive arguments.

•

Application of current patient, clinical, sociodemographic and healthcare delivery site characteristics to RCT design, including modeling patient eligibility, new potential patient entry into each site, and historical site and patient-type-specific consent rates for participation in RCT research. RCT site selection and optimization strategies are the starting point for building an optimally efficient CT management organization which minimizes costs, delays in recruitment and time-consuming modification of protocols.

Identification of both sites and investigators to conduct the trial. Knowledge regarding the clinical and sociodemographic characteristics of the patients who are seen at hospitals, clinics and offices, as well as the individual physicians who practice at each site, provides data-driven insights for investigator and site selection and management over time.

2. Know ALL the company groups/functions that will benefit from RWE

Being aware of the problems, goals and requirements of all functions provides a knowledge base for identifying key data sources, designing solutions and incorporating stakeholders’ points of view. PowerPoint presentations that acknowledge and combine the functional needs of the various groups who will be utilizing the solutions never fail to engage the many audiences who will pass judgment.

•

Some of the many functions and groups involved in RCT design are biostatistics, epidemiology, CT operations, regulatory & safety and clinical trialists − all of whom benefit from being able to model the draft RCT protocol against RWD. In particular:

• •

•

New research questions can be tested and explored using the clinically wide-ranging data sources.

Specific RCT protocol inclusion/exclusion criteria can be modeled to determine feasibility, including the quantity of clinical sites needed to achieve required patient numbers for statistical significance. Using large, timely and longitudinal data sources, ongoing pharmacovigilance with real-time active surveillance of adverse events becomes a true possibility.

The data is adaptable, with the ability to add new data variables and sources as they become available. And with relationships to the providers of deep, clinical data (clinics, hospitals, physician offices, disease registries), opportunities exist to retrieve additional information from unstructured data fields, queries to professional caregivers regarding decision making, and even patients for further follow-up − which is of benefit to all groups.

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Figure 2: Data sources into data platforms: Real-world evidence insights for R&D

Translational Discoveries

Pharmacovigilance

New Research Questions

Hypothesis Generation

Study Feasibility Assessment

Data PlatformCommon Data Format

EMR-1 Disease Registry

EMR-2

Evidence Generation

EMR-3

Cohort Identification

Open Claims Death Records

Data Analysis

Closed Claims Lab Results

Data Quality Assessment

Data Integration

HIPAA Compliance

Unique Patient Identifier

Real-time Reports

Targeted Chart Reviews

Record Linkage

Encryption

Source: IMS Health

Figure 2 identifies the basic applications of R&D functions and the foundation required to ensure a regulatory-compliant and acceptable deliverable that is scientifically based. Specifically, clinical trialists, biostatistics, CT management, regulatory, outcomes researchers and safety functions all work together, hopefully in a harmonious way, to move a concept from the scientific bench to a clinical research protocol/study. The flexibilities that benefit this type of data approach allow R&D functions to deliver the research required in the most efficient manner and create and test hypotheses without conducting an expensive RCT, as well as generating the scientific evidence necessary for ongoing regulatory submissions. Examples include the ability to precisely determine:

• • •

Patient population being prescribed and administered a drug Proportion of patients aligned with the label

Outcomes for patients not studied in the drug development RCT program

The benefits of such precision should be clear: identifying and assessing the success of programs to ensure patient safety, providing a solid data basis for interactions with regulatory authorities as well as ensuring good regulatory compliance.

Administrative systems (eg, healthcare claims for reimbursement) are the backbone for identifying, measuring and determining the health system costs and benefits (ie, net value) of changes in care delivery. When a new therapeutic intervention provides a marginal efficiency improvement, they allow for accurate cost measurement which is of primary interest to the health economist/outcomes

research groups in pharma. The precise identification and quantification of therapeutic value is the basis for delivering true comparative cost-effectiveness and will always be needed by these groups. Figure 2 also illustrates the foundational need for robust technological and governance expertise to increase confidence in generating and using RWE. R&D organizations require in-depth knowledge of the fundamentals underpinning a data platform. “How does the encryption work and why is it HIPAA compliant?” are not just idle questions but spring from the challenges they deal with frequently. Providing detailed information on how a ‘targeted chart review’ would work and why it is the most cost-effective approach when further observational research is required, creates an “aha” moment for the audience as they integrate their previous knowledge of conducting these types of studies with new information as to how to conduct them in a novel and efficient manner. This certainly proved to be the case at my company, as just about every R&D employee knew the cost and process of generating RCT data and the cost of a chart review but not the costs or steps involved in analyzing secondary data sources. As these individuals tend to be either directly or formerly ‘hands on’ and both want and need to engage with clinical sites, creating opportunities for them to visualize working with these sites is an essential requirement. Further, the integration and data cleansing process (data curation) of these disparate data sources, with millions of patients and billions of data points, often require machine learning and algorithms to scour the records – a service that few in pharma R&D have previously experienced.

continued on next page

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INSIGHTS RESEARCH & DEVELOPMENT 3. Recognize differential motivation and groundbreaking research potential

R&D staff have a different motivational basis than the rest of pharmaceutical company employees. It is important not to underestimate that one of the primary drivers of people who seek careers as scientists is to make a discovery that no one has ever seen before. Aspiration to be part of the team or the lead discoverer of new and important information that will transform the practice of medicine is in the DNA of all R&D staff.

Many clinical research projects are not primarily concerned with therapy but investigate, for example, the natural course of diseases, criteria for diagnosis, the role of patient education and continued surveillance. Often, clinical research now includes studies on the role of genes and metabolic pathways in relation to health and disease development. Some is also concerned with the function and efficiency of the healthcare delivery system as the value of incremental improvements in medications, while not having tremendous clinical importance, can have tremendous healthcare effectiveness and public health impact. Longer-acting antibiotics, for example, while not a breakthrough, can substantially improve patient adherence thus reducing the likelihood of developing antibiotic-resistant bacteria and considerable downstream patient suffering and healthcare system costs. Who would not like to be the person who saves the world from drugresistant bacteria? When patient-reported outcomes are collected via mobile phone or hand-held computer technology and are coupled with the wealth of information from administrative systems, it creates a more complete understanding of a patient’s functioning, symptoms, quality of life and impact of a pharmaceutical on their everyday life. These methods provide decision makers with RWE of the impact of medicines on important outcomes and quality of care, allowing for identification of the specific points, value and differentiation that a new therapeutic has compared to existing and competing therapies.

“ 1 2 3 4

Conclusion

Drug companies are seeking to increase the clinical success rates of new drug candidates by developing tools and resources to help them predict the likelihood of marketing approval and improve their estimates of revenue over the product lifecycle. They are also attempting to create a systematic process that incorporates this information into business planning earlier in clinical development.

This shift in approach favors data-driven methods over intuition. Replacing the poor quality models of incidence, treatment prevalence and product uptake can improve decision making and increase sales which in turn lead to corporate success. At my company, for example, it was possible to more accurately forecast month-to-month revenue than previously, to predict − with amazing accuracy and to many internal accolades − the uptake and penetration of new oncology products upon launch, and finally to very successfully counter several legal claims with robust evidence. The pharmaceutical industry, while focusing on RCTs for marketing approval, recognizes the growing need to improve the efficiency and lower the cost of these trials while responding to increased demands from regulatory bodies for more and better quality evidence of safety, effectiveness and outcomes. Further, as financial pressures intensify to moderate drug prices, the value that a pharmaceutical product brings to the marketplace must be clear, significant and scientifically robust. Thus, there has been increasing attention to issues of comparative effectiveness, as well as understanding all the patients who will be administered and take the products, ie, those ‘realworld’ patients with multiple diseases and various characteristics that were excluded from the Phase I-III RCTs employed for marketing approval.

Replacing the poor quality models of incidence, treatment prevalence and product uptake can improve decision making and increase sales which in turn lead to corporate success.

”

Berndt ER, Nass D, Kleinrock M, Aitken M. Decline in economic returns from new drugs raises questions about sustaining innovations. Health Affairs, 2015; 34 (2): 245-252

Fiercepharma. Merck, AstraZeneca, Pfizer top list of biggest pharma job-cutters. Oct 7, 2013. Available at: http://www.fiercepharma.com/story/merck-astrazeneca-pfizer-top-list-biggest-pharma-job-cutters/2013-10-07 Accessed 25 April, 2015.

Fischer K. Employer heads to court for class-action suit over cost of Hep C Drug Sovaldi. HealthLine News, December 14, 2014. http://www.healthline.com/health-news/class-action-suit-over-cost-of-hep-c-drug-sovaldi-121514 Accessed 16 April, 2015.

Jamoom E, Hing E. Progress with electronic health record adoption among emergency and outpatient departments: United States, 2006– 2011. NCHS data brief, no 187, February 2015. Hyattsville, MD: National Center for Health Statistics, 2015

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INSIGHTS HEOR, PHARMACOEPIDEMIOLOGY & DRUG SAFETY

Multi-country drug utilization studies in Europe A major shift in regulatory requirements has placed RWD at the heart of drug safety activities in Europe. most drug utilization studies (DUS) – a key tool in evaluating risk management measures – are now underpinned by analyses leveraging vastly expanded datasets. As the role of RWD continues to broaden, we consider its particular value in pharmacovigilance and the challenges fuelled by a growing need for multi-country DUS assessments.

The authors

birgit Ehlken, mSC is Director, RWE Solutions, IMS Health Behlken@de.imshealth.com

Jacco Keja, PHD is Senior Principal, RWE Solutions, IMS Health JKeja@nl.imshealth.com

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INSIGHTS HEOR, PHARMACOEPIDEMIOLOGY & DRUG SAFETY

multi-country drug utilization studies in Europe Increasing importance of using RWD database analysis In 2012, the European Medicines Agency (EMA) established a framework for Post-Authorization Safety Studies (PASS) in Europe. PASS are any studies relating to an authorized medicinal product, conducted with the aim of:

• • •

Identifying, characterizing or quantifying a safety hazard Confirming the safety profile of the medicinal product

Assessing the effectiveness of risk management measures

A PASS can be requested by the EMA whenever there are concerns about the risks of an authorized medicinal product:

• • •

As part of the initial marketing authorization application During a post-authorization regulatory procedure Due to an emerging safety concern

Drug utilization studies to meet regulatory requirements

The PASS design should be appropriate to address the study objectives. Knowledge of the quantitative and qualitative patterns of drug use is a key element for the rational use of medicines, the rational assessment of the risk-benefit ratio, and for decision making on risk-minimizing actions for medicines. Drug utilization studies (DUS) provide simple metrics for monitoring appropriate drug use and thus are often a key element for assessing the effectiveness of risk minimization measures (RMMs). The Pharmacoepidemiological Research on Outcomes of Therapeutics by a European ConsorTium (PROTECT) study is

a collaborative European project which aims to enhance monitoring of the safety of medicinal products, firstly by addressing the limitations of methods currently used in pharmacovigilance and pharmacoepidemiology, and secondly by strengthening the monitoring of the benefitrisk assessment of medicines in Europe.

According to a search on nationwide administrative medicines consumption databases in Europe, conducted in 2010, PROTECT has identified 31 administrative nationwide medicine consumption databases in 25 countries.1 The majority of the databases provide information on the outpatient sector, whereas inpatient drug utilization data on national level basis is rarely available.2

A recent analysis of 35 DUS requested by EMA and registered in the EU-PAS register found that about two-thirds of studies (63%) are based on already available data sources such as electronic medical records (EMR) databases, claims databases and registries.3 The majority consider multiple countries (Figure 1).

Most of the 35 DUS include France, Germany, Italy, Spain and the UK as target countries (Figure 2). The choice of the big EU5 countries reflects the potentially high number of exposed subjects but also the access of eligible databases. This data consideration explains why Scandinavian countries are frequently included, despite the relatively smaller number of patients. Specifically, they offer rich data (including potentially patient hard-level linkages of different registers on morbidity, drug use, etc) with national coverage registry data.

Figure 1: Number of target countries in DUS

Number of studies

0 1 country

2-4 countries

5-7 countries

8-10 countries

>10 countries

*listed in the e-register of ENCePP

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Figure 2: Countries included in 35 DUS requested by EMA

Source: EU-PAS register, October 2014

The lower number of executed studies in Eastern European countries likely reflects the limited availability of eligible databases, especially when longitudinal information at patient level is required, for example pre-treatment, comorbid conditions as well as treatment duration. Indications of high public-health relevance like infection, cancer, contraception, mental health, cardiovascular conditions and metabolic disorders are in the focus of DUS requested by EMA (24 of 35 studies; 69%).

Varied information requirements

Information requested by the EMA varies by indication. In areas like contraception and infections, it included basic drug utilization patterns such as number of users, distribution of indications associated with the prescription and off-label use. In the case of drugs for metabolic diseases (eg, diabetes) impacts on drug utilization patterns by labelchange were sought, as well as trends over time in drug switches and laboratory parameters. For indications that are prone to off-label use, abuse and diversion, such as pain medication and psychoactive drugs, pharmaceutical companies were requested to show the effectiveness of RMMs.

benefits of databases for DUS

Since the majority of DUS are conducted through databases, it is reasonable to conclude that this timely and efficient method of data collection has become a standard approach for such studies. But what are the advantages of working with databases in DUS instead of more bespoke, noninterventional observational approaches?

• • • •

Wide geographic coverage Good representativeness

Larger patient sample sizes

More time efficient for study set-up and conduct

• •

Better cost-effectiveness: typically lower resource and cost requirements

Information that is closer to real prescriptions and thus less prone to observational bias (social desirability, information obtained through the study, etc) which can influence the answers of healthcare professional in a study using primary data collection

The eligibility of databases is highly dependent on the objectives of the DUS requested by regulators as well as the parameters of interest. Whereas several databases allow the description of drug utilization on a cross-sectional basis, according to prescribed, dispensed or reimbursed medicines, they often lack the availability of longitudinal anonymous patient-level information in order to describe, for example, pre-treatment or concomitant drug use. Two approaches for a multi-country PASS using a drug utilization of substances indicated for mental and behavioral disorder are outlined in Table 1.

lessons learned

The data integration working group of the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP) is working on guidelines for methods of using multiple data sources for studies with safety endpoints. These guidelines are expected to be released for public consultation in 2015. Given the importance of these data sources, a topic of the last plenary meeting of ENCePP in November 2014 was dedicated to the lessons learnt from using different data sources, including their advantages and limitations.4

Summary and outlook

Increasingly demanding regulatory requirements on the one hand and technological advances on the other are driving a paradigm shift to RWD databases as the foundation for pharmacovigilance in Europe.

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INSIGHTS HEOR, PHARMACOEPIDEMIOLOGY & DRUG SAFETY

Table 1: Approaches for a multi-country PASS using a drug utilization of substances indicated for mental and behavioral disorder

DUS as part of Risk Management Plan (RMP) for upcoming launch in EU countries • Client – Pharma HQ

• Upcoming product launch in 15 EU countries

Situation

• Wish to include 5-year DUS in Europe as part of RMP

• Goal of providing drug utilization data

annually for up to 5 years following launch to allow evaluation of off-label use

DUS to provide annual data on established product for Periodic Safety Update Report (PSUR) • Client – Consortium of Pharma, HQ

• Wish to include annual updates of drug

utilization data in 20 EU countries in PSUR

• Goal of providing drug utilization data

annually for up to 5 years to allow evaluation of compliance of prescription behavior with labeling information.

FOCUS OF ANALYSIS

• Prescriber specialty

• Patient profile (age, gender)

• Indication

• Prescription (dosage, switches, duration, first time user, repeat user)

• Indication

• Average daily dosage

• Pre-treatment

Approach

DATABASES USED

• IMS RWD EMR (IMS Disease Analyzer) data

• IMS Health Prescribing Insights databases

Longitudinal databases

(Germany) and CPRD (UK)

Cross-sectional databases

• National disease plus prescription

registries (Denmark, Finland, Norway, Sweden)

• IMS RWD LRx pharmacy prescription data (Belgium, Italy, Spain, Netherlands, Switzerland)

Cross-sectional databases

• IMS Health Prescribing Insights databases DUS are increasingly being used as part of a broader PASS package and RWD is becoming a more effective, efficient and cost-effective way to conduct them. Already, the majority of these studies that are requested and registered by EMA are based on established data sources. These massive datasets provide larger patient pools and geographic coverage, good representativeness and faster results. Historic limitations, such as lack of longitudinality and sufficient detail on endpoints, along with the siloed system view, are evaporating with technological advancements and the development of validated advanced methods of linkage. 1 2

3 4

The next task is clear: since most DUS involve multiple countries, the shift to RWD poses the new challenge of harmonizing and finding the right electronic data sources to address the required objectives. Currently, this can be only handled by groups with the right level of expertise to ensure that the advantages of working with RWD are upheld.

Ferrer P, Ballarín E, Sabaté M, Laporte JR, Schoonen M, Rottenkolber M, Fortuny J, Hasford J, Tatt I, Ibáñez L. Sources of European drug consumption data at a country level. Int J Public Health, 2014; 59(5): 877-87

Sabaté M, Ferrer P, Ballarín E, Rottenkolber M, Amelio J, Schmiedl S, Reynolds R, Klungel O, Ibáñez L; PROTECT Work Package 2. Inpatient Drug Utilization in Europe: Nationwide Data Sources and a Review of Publications on a Selected Group of Medicines (PROTECT Project). Basic Clin Pharmacol Toxicol, 2015; 116(3) 201-11

Schroeder C, Keja J, Hughes B, Ehlken B, Toussi M. Understanding patterns of drug utilization studies (DUS) requested by the European Medicines Agency (EMA). Presentation. 30th ICPE Conference, Taipei, Taiwan, 24-27 October 2014

Use of routinely collected electronic healthcare data: Lessons Learned. ENCePP Plenary, 25 November 2014, European Medicines Agency. Available at: http://www.encepp.eu/publications/documents/3.1_MToussi_electronic_healthcare_data.pdf

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Improving drug benefit-risk assessment leveraging social media brand teams have been using social media for years to provide patients with useful, accurate information as they try to better understand diseases and treatment options (as allowed by market). While there are risks to be managed, there is also signiﬁcant new potential for pharmacovigilance. Here we explore the under-tapped safety-related applications.

The authors

massoud Toussi, mD PHD, mSC, mbA is Principal, RWE Solutions, IMS Health Mtoussi@fr.imshealth.com

Siva Nadarajah, bSC is General Manager, Social Media, IMS Health Snadarajah@us.imshealth.com

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INSIGHTS HEOR, PHARMACOEPIDEMIOLOGY & DRUG SAFETY

Improving drug benefit-risk assessment leveraging social media Time to hear the patient voice A significant increase in healthcare information gathered through digital media – which includes websites, web pages, blogs, social networking sites, internet forums, and health portals – reflects growing public interest in sharing and discussing healthrelated issues online. In the USA, a reported one third of consumers use social media sites such as Facebook, Twitter and YouTube to inform decisions about their health, share symptoms with others and derive or proffer opinions on treatments and physicians;1 in the UK, research has identified Facebook as the fourth most popular source of health information;2 and in Europe more broadly, over 40% of online consumers have stated their use of social media forums for health purposes.3 Overall, it has been found that individuals spend 24 times longer on healthcare consumer community sites than on healthcare company sites.1 Notably, most of the data responsible for this exponential growth is unstructured, and includes tweets, comments and videos. Such has been the speed of take-up – social media has grown faster than any other media platform4 – that the technology for evaluating and managing this type of information is struggling to keep pace. And the trend is set to continue: by 2020, it is estimated that the amount of data recorded on digital media will reach 44 zettabytes;i 9% will be related to healthcare, of which half will be related to drugs.5

Challenges for pharma

The pharmaceutical industry has been more reluctant than most to adopt digital media. Research from the IMS Institute for Healthcare Informatics shows that half of the top 50 pharmaceutical companies do not engage with consumers or patients through social media on healthcarerelated topics.6

A recognized need to improve their effectiveness in this area has seen more pharmaceutical marketing departments start to leverage these channels to understand patient perceptions about their drugs. However, other functional areas, such as safety and pharmacovigilance, remain

skeptical about the validity of the knowledge extracted. This cautious approach to adopting social media reflects a combination of issues but particularly concerns around regulatory compliance, privacy and the validity of the accumulating data.

Regulatory issues

Traditionally, the identification of adverse drug reactions (ADRs) has relied on individual case reports overseen by physicians and drug safety groups. The European Medicines Agency’s (EMA) Good Pharmacovigilance Practices (GVP) define an ADR as a response to a medicinal product which is noxious and unintended. Such reactions are deemed serious if they involve death, a life-threatening condition, inpatient hospitalization or prolongation of hospitalization, persistent or significant disability or incapacity, a congenital anomaly or a birth defect. An individual case safety report (ICSR) describes one or several ADRs that occur in a single patient at a specific point in time. An ICSR is considered valid in the presence of:

• • • •

at least one identifiable reporter a single identifiable patient

at least one suspect adverse reaction

at least one suspect medicinal product

Applying these definitions to social media reports of ADRs is challenging. However, the importance of ADR reporting cannot be overstated. Marketing Authorisation Holders (MAHs) are legally responsible for the safety and effectiveness of medicines on the market. They are required to report ADRs to the relevant authorities, operate appropriate pharmacovigilance and risk management systems, and ensure that action can be taken when necessary. Only with a thorough understanding of the ADRs caused by their products can they fulfill these requirements. Within the EU, MAHs are legally obliged to forward adverse events (AEs) to the EMA. There are also voluntary programs to improve ADR reporting such as the FDA Adverse Event Reporting System (FAERS) in the USA, and The Yellow Card Scheme in the UK.

Additionally, MAHs have an onus to regularly screen internet or digital media under their management or responsibility for potential reports of suspected ADRs. Any reports that come to light in a non company-sponsored digital medium must also be assessed to determine whether they qualify for reporting.

1 zettabyte = 1021 bytes

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

•

Opportunities for enhanced drug safety

Today, the growing use of social media by patients as a vehicle for sharing their experiences with medicines offers a new and thus far largely underutilized source for ADR reporting.

Web-based patient-reported outcomes can provide an opportunity for MAHs and regulatory bodies to understand the benefits and risks of medicines in the real world. Information captured from online communities can aid appreciation of how patients perceive their ADRs, improve the way adverse effects of drugs are managed, and facilitate the development of strategies for improving treatment adherence. It can also serve to highlight topics that are of particular concern to patients (eg, medication convenience or packaging) and side-effects that are not discernible in clinical trials. In addition to ADRs, social media data can also help to assess patient perception of risk.

Although research on tracking ADRs with the help of social media is still nascent, documented evidence of its validity is emerging, along with demonstrations of its value:

•

In monitoring pharmaceutical products in Twitter, Freifeld and colleagues identified more than 4,000 posts that resembled AEs, and demonstrated a significant correlation with data from FAERS by System Organ Class (p<0.0001)7

Analysis of 3,785 items from five social media sites found that patients with glaucoma had stronger positive feelings towards complementary therapies and treatments with a poor evidence base than towards medically proven therapies, suggesting a lack of awareness about the latter8 A mixed methods study examined the content related to aromatase inhibitor (AI)-associated side-effects posted by breast cancer survivors on 12 message boards between 2002 and 2010. Of the 25,256 posts related to AIs, 18% mentioned at least one side-effect. Close to 13% mentioned discontinuing AIs and 28% switching AIs9

Analysis of patient narratives on popular social media websites for health-related topics in France before and after withdrawal of all medicines containing benfluorex found a drastic change in patient perceptions: prior to the withdrawal date, most posts concerned efficacy; after removal, most discussed cardiovascular side-effects10

Figure 1: IMS Health’s Nexxus™ Application Suite AETracker provides a cloud-based engine for AE monitoring

Natural language processing and semantic algorithms

AETracker Unstructured Data Disease, conversation and side-effect ontologies

Rx Ontology

MeSH (Medical Subject Headings)

PV Analysis

Potential Adverse Events

Custom syndicated ontologies from client projects

Unified Medical Language System

Feedback into the ontology

Nexxus Social Media Ontology

continued on next page

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INSIGHTS HEOR, PHARMACOEPIDEMIOLOGY & DRUG SAFETY

Technical considerations

The increasing use of social media by patients to post and discuss their experiences with diseases, drugs and treatments, has generated a large volume of unstructured information, specifically concerning reactions to medicines that MAHs are required to monitor and act on accordingly. Current tools and techniques for analyzing unstructured data, especially in pharmacoepidemiology and safety, are limited. There is thus a need for a solution to both capture the data and leverage it efficiently for detecting ADR reports and bringing them to the attention of MAHs for validation and further actions. Two examples providing insights into the technical possibilities of detecting safety signals through the internet are:

•

IMS Health’s Nexxus™ Application Suite and its module AETracker. This provides a cloud-based engine for AE monitoring, off-label usage and other legal, regulatory and reputation risks in company-sponsored digital assets including social media accounts and mobile apps. In real time, pharmacovigilance experts review and confirm any false positives or alert the client within one hour of an AE being reported (Figure 1).

2 3 4 5 6 7 8 9

Growing public interest in health-related issues coupled with a surge in the volume of data generated through social media, in particular the sharing of information on ADRs, brings specific challenges for pharma. However, it also offers unique opportunities for pharmacoepidemiology to tap a rich new source of information and provide insights for a more complete benefit-risk evaluation of medicines.

While there is still unmet need for regulatory transparency around the tracking of ADRs through social media, along with the technology required to assess and analyze the data, steps have been taken by governments and agencies to address the gaps. Going forward, there is a role for a multistakeholder approach involving the industry, patients, regulators, prescribers and academic groups. For individual manufacturers, the analysis of social media – even for purposes other than drug safety – may generate ADR information beyond their current processing capabilities. However, with the right management and coordination between functions this new data source can be effectively leveraged to help improve both patient safety and internal commercial effectiveness.

In the UK, the WEB-RADR initiative, a multi-stakeholder initiative led by the MHRA, seeks to investigate technologies for gathering ADR data through a mobile app to add to the established safety profiles of medicines, enable earlier detection of new signals, reveal new patterns or trends in reporting, and even provide a means for geo-pharmacovigilance.

“ 1

Conclusion

There are unique opportunities for pharmacoepidemiology to tap a rich new source of information and provide insights for a more complete benefit-risk evaluation of medicines.

”

Social media “likes” healthcare: From marketing to social business, PwC Health Research Institute, April 2012 Dawson J. Doctors join patients in going online for health information. New Media Age, 2010

New Study Shows 72 Percent of European Online Consumers are Social Health Users. Available at http://manhattanresearch.com/News-andEvents/Press-Releases/european-social-health-users Accessed 30 Apr 2015 Turning buzz into gold: How pioneers create value from social media. McKinsey & Co, May 2012. Available at: http://www.mckinsey.de/sites/mck_files/files/Social_Media_Brochure_Turning_buzz_into_gold.pdf Accessed 30 April, 2015

Wikibon Blog. A Comprehensive List of Big Data Statistics Available at: http://wikibon.org/blog/big-data-statistics/

IMS Institute for Healthcare Informatics. Engaging patients through social media: Is healthcare ready for empowered and digitally demanding patients? January, 2014.

Freifeld CC, Brownstein JS, Menone CM, Bao W, Filice R, Kass-Hout T, et al. Digital drug safety surveillance: Monitoring pharmaceutical products in twitter. Drug Saf, 2014;37(5): 343-50

McGregor F, Somner JE, Bourne RR, Munn-Giddings C, Shah P, Cross V. Social media use by patients with glaucoma: what can we learn? Ophthalmic Physiol Opt. 2014;34(1): 46-52

Mao JJ, Chung A, Benton A, Hill S, Ungar L, Leonard CE, et al. Online discussion of drug side effects and discontinuation among breast cancer survivors. Pharmacoepidemiol Drug Saf, 2013; 22(3): 256-62

Abou Taam M, Rossard C, Cantaloube L, Bouscaren N, Roche G, Pochard L, et al. Analysis of patients’ narratives posted on social media websites on benfluorex’s (Mediator®) withdrawal in France. J Clin Pharm Ther, 2014; 39(1): 53-5

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Prospective identification of drug safety signals from primary care EMR At a time of growing demand for more accurate and timely drug safety evidence, a landmark study supports the value of electronic medical records (EmR) for detecting new adverse reactions. It also shows that statistical associations in EmR must be treated with as much caution as those from individual case reports − and be subjected to clinical and epidemiological review. A deep understanding of the methodologies, data collection and clinical practice involved is implicit.

The author

David Ansell, mb, CHb, mRCS, PHD is Associate Director, RWE Solutions, IMS Health Dansell@uk.imshealth.com

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INSIGHTS HEOR, PHARMACOEPIDEMIOLOGY & DRUG SAFETY

Prospective identification of drug safety signals from primary care EmR Insights from The Health Improvement Network (THIN) database Increasingly stringent regulatory requirements for pharmaceutical risk management and safety surveillance have accelerated research to improve the detection of new adverse drug reactions (ADRs) under conditions of normal product use. For many years, the process of identifying potential signals and the existence of previously unknown risk has relied mainly on individual case safety reports (ICSRs). More recently the use of longitudinal health data (LHD) has been explored, both to complement ICSR information and overcome some inherent limitations. Most studies looking to apply LHD have investigated its ability to distinguish established ADRs from unrelated adverse events; few have attempted to examine a role for this data in detecting emerging safety signals.

leveraging EmR in pharmacovigilance

Marking an important milestone in efforts to apply EMR in day-to-day pharmacovigilance, a new study has sought to evaluate a process for assessing temporally associated drugs and medical events (adverse events) in this data.1 Specifically, the researchers aimed to determine (1) to what extent exploratory analysis of EMR would identify important potential safety signals and (2) what proportion of false alarms could be expected if the temporal associations were taken at face value rather than subjected to epidemiological review. Utilizing the Uppsala Monitoring Centre’s vigiTrace™ framework for health data exploration, the study comprised integrating the vigiTrace™ software framework with the primary care EMR and performing a structured assessment of more than 500 pairs of drugs and medical events in THIN (The Health Improvement Network) – an electronic medical records resource from primary care in the UK. THIN includes more than 12 million patients, with over 3.8 million being currently active patients. The EMR are collected from general practices and are representative of the entire UK population in terms of age, gender, medical conditions and death rates. The data extract for the current evaluation was from January 2011 and covered 7.7 million patients. A key element of vigiTrace™ is a graphical display (chronograph) which summarizes and visualizes temporal associations between two events. In this case, the chronograph focused on the cohort of patients with new prescriptions (Rx) of the drug in question and explored variation over time in the recording of a medical event relative to those new Rx. Further, it contrasted the observed number of patients with a record of the particular event to an expected value in each time period, based on an external control group. VigiTrace™ also provided analytics to support the structured assessment, providing a calibrated self-controlled cohort analysis.

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Evaluation process

Over 40 drugs were randomly selected from THIN on the basis of specified inclusion/exclusion criteria, key amongst which was the presence of more than 5,000 new Rx. Medical events (up to 20 per drug) chosen at random from those identified as temporally associated with a new Rx of the drug in question, were assessed for relevance prior to undergoing in-depth analysis. The in-depth assessment was based on a structured questionnaire and included a review of the UK Summary of Product Characteristics (SPC) document as well as additional exploration of data in THIN. Among factors addressed as part of this appraisal were: the nature of the temporal pattern; demographics of the cohort; use of concomitant medicines; previous signs and symptoms; and potential confounding by underlying disease. Results

From the more than 500 relevant drug-event combinations that were identified, 25% were categorized as known ADRs, based on the SPC review (eg, sleep disturbance for a drug with insomnia listed, glaucoma for a drug with acute glaucoma listed).

Close to one hundred of the remaining combinations were classified as meriting full clinical review, beyond the restricted scope of the study assessment. Examples include multiple organ failure with a selective serotonin reuptake inhibitor (SSRI); skin sensation disturbance (eg, paresthesia, numbness, tingling) with a long-acting beta-2 agonist; and an ophthalmic condition with a diuretic. The strength of evidence for these combinations varied: most of them merely lacked alternative explanations to suggestive temporal patterns, whereas a few also had support in experimental evidence or regulatory information from other countries than the UK. In contrast, the majority (approaching 300) of the highlighted drug-event pairs were deemed unlikely to reflect direct causal relations and hence dismissed from further review. The most common reasons for this were confounding by the underlying disease or earlier signs and symptoms indicating that the onset of the medical event preceded the start of drug treatment. Examples include endometriosis with a drug for the relief of IBS where the prior diagnosis of IBS (based on abdominal pain) was later shown to be endometriosis, and eustacian tube dysfunction with antibiotic drops utilized for treating an ear infection. Examples of the chronograph outputs are shown in Figure 1 opposite.

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Figure 1: Sample outputs from the vigiTrace™ chronograph

24 %

91 Merit further evaluation 509 Temporally associated drug-event pairs

75%

382 New

25%

Epiphora is temporally associated with new prescriptions of amiloride and was classified as meriting further review on account of the suggestive temporal pattern.

127 Already known

Cannot sleep – insomnia is temporally associated with new prescriptions of reboxetine and was classified as already known since insomnia is listed as a very common adverse reaction to reboxetine in the UK SPC.

291 Dismissed

Endometriosis is temporally associated with new prescriptions of hyoscine but was dismissed from further review on account of suspected protopathic bias. Hyoscine is given to treat abdominal cramps, which are a common symptom of endometriosis.

Source: Cederholm S, Asiimwe A, bate A, bhayat F, brobert G, Hill G, Star K, Norén GN. Structured assessment for prospective identification of potential safety signals in electronic health records (Poster). 30th International Conference on Pharmacoepidemiology and Therapeutic Risk management (ICPE) 24-27 October, 2014 Taipei, Taiwan

Implications

With this study has come a clear demonstration that exploratory analysis of EMR is a valid and feasible approach for detecting important drug safety signals. If a primary care EMR such as THIN is utilized as the source, then signal detection will be confined to those drugs prescribed within the primary care setting. The initial epidemiological review revealed a considerable number of temporally associated drugs and medical events, ranging from significant, lifethreatening conditions to less serious but potentially problematic events for patients. Importantly, some of these were conditions that the current pharmacovigilance system, with its reliance on individual ADR case reporting, may be challenged to capture. Some of the identified events have not been previously linked to these therapeutic agents and have highlighted the requirement for further investigation.

That said, the fact that 75% of the drug-event pairs were dismissed from further evaluation following initial review, indicates that signal detection using LHD should form part of a wider, comprehensive process of detailed clinical and epidemiological review. This is an important area for further research to inform the future role of LHD in signal detection. It would include examination of individual patient histories, evaluation of more detailed information in THIN (eg, temporal patterns for similar drugs and medical events) as well as exploration of alternative, complementary information sources such as the scientific literature and collections of individual case reports. A broader, contextual understanding of the methodologies employed, approaches to data collection, and the prevailing medical practice in the setting being studied would be a key part of this process.

The study referenced in this article was performed in collaboration with scientists from Eli Lilly, Pfizer, Takeda, Bayer and Cegedim UK, within the public-private partnership PROTECT, which is funded through the European Innovative Medicines Initiative. 1

Cederholm S, Hill G, Asiimwe A, Bate A, Bhayat F, Persson Brobert G, Bergvall T, Ansell D, Star K, Norén GN. Structured assessment for prospective identification of safety signals in electronic medical records: Evaluation in the Health Improvement Network. Drug Saf, 2015; 38: 87-100

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PROJECT FOCUS HEOR, PHARMACOEPIDEMIOLOGY & DRUG SAFETY

Answering complex questions in health outcomes and epidemiology by linking retrospective datasets Innovative linkage of retrospective data extends the breadth and depth of individual datasets to meet increasingly challenging research needs. Realizing the potential of RWE to provide rich insights into patient care and outcomes requires all relevant and related data to be brought together, regardless of where and how it is collected. The value of this is beginning to metamorphosize health outcomes and epidemiology research but the transformation requires sophisticated analytics, complex data management and pragmatic trade-offs.

The following examples illustrate how this was achieved where answers were sought to a number of complex questions:

• • • • •

How is seizure frequency between clinic visits related to the specific anti-seizure medication(s) used and adherence to therapy?

What is the impact of a retail pharmacy chronic medication adherence program on the risk of hospitalization and overall medical utilization?

What is the relationship between adherence to antiplatelet therapy following discharge from hospital for acute coronary syndrome (ACS) and outcomes of readmission, death and healthcare costs?

What is the incidence of hospitalization for acute pancreatitis among severe hypertriglyceridemia patients?

To answer these questions, the research required data from multiple sites of care (pharmacy, clinic, hospital, lab) and with a level of clinical detail (seizure frequency, inpatient blood product utilization, adherence interventions, mortality). As is now commonly understood, this type of retrospective data typically sits in many isolated datasets (Figure 1). These vary in several ways:

• •

Rolin (Ron) Wade, RPH, MS is Principal, RWE Solutions, IMS Health Rwade@us.imshealth.com Chi-Chang Chen, PHD, MS.PHARM is Director, RWE Solutions, IMS Health C.Chen@us.imshealth.com Ajita De, MA, M.PHIL, MS is Senior Consultant, RWE Solutions, IMS Health Ade@us.imshealth.com

How is the use of blood products and clotting factors administered during hospitalization for serious upper GI bleeding affected by pre-admission use of anticoagulants?

Combining breadth and depth

•

The authors

Size and degree of national representativeness (size of circle)

Level of completion for data capture across sites of care (x-axis)

Most retrospective database research still relies on individual datasets. Although this usually offers the largest sample size, it often fails to address the research questions in a comprehensive manner which requires taking into account the patient’s full continuum of care. In addition, one major limitation of this approach is the trade-off between using data that is clinically rich (EMR, hospital charge master) versus data that captures patient activity across multiple sites of care (billing or claims). In the case examples shown, the research questions posed could not be well addressed using any of the single data sources depicted in Figure 1 since they required the ability to both analyze patient activity across multiple sites of care and capture specific clinical details. The desired solution was thus to utilize multiple data sources which, when combined, would provide longitudinal clinical information as well as insights into the broad range of care for the patients of interest. While primary data collection (such as medical chart abstraction) can be used, the linking of datasets1 is more cost-effective and timely.

Richness of the clinical information (y-axis)

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Figure 1: Retrospective data typically exists in disparate datasets

Deep

Level of clinical richness

EMR Hospital Charge Master

Open Source Claims

Prospective Registry

Adjudicated Claims Death

Thin Single Site

All Sites

Capture across multiple sites of care Source: IMS Health

Table 1: Research questions and approaches to solutions Research question How is seizure frequency between clinic visits related to the specific anti-seizure medication(s) used and adherence to therapy? How is the use of blood products and clotting factors administered during hospitalization for serious upper GI bleeding affected by preadmission use of anticoagulants?

What is the impact of a retail pharmacy chronic medication adherence program on the risk of hospitalization and overall medical utilization? What is the relationship between adherence to antiplatelet therapy after hospital discharge for ACS, and outcomes of readmission, death and healthcare costs? What is the incidence of hospitalization for acute pancreatitis among severe hypertriglyceridemia patients?

• • • • • • •

Key clinical elements

• • • •

Seizure frequency

Seizure-free status

Prescription utilization Inpatient admission for bleeding events

Use of blood products during hospitalization

Pre-admission exposure to anticoagulant medication

Record and type(s) of pharmacy-based medication adherence counseling received Medication adherence Mortality

Lab results for triglyceride levels

Inpatient admission/ treatment for pancreatitis

• • • • •

Required care settings

• • • • • • •

IMS Health Solution

Outpatient pharmacy prescriptions

Linkage of pharmacy claims dataset to progress notes in the EMR

Inpatient hospital care

Linkage of hospital charge master data to outpatient pharmacy/medical claims

Outpatient physician office visits Outpatient pharmacy prescriptions

Outpatient physician office visits Pharmacy registry

Encryption of pharmacy records and linkage to fully adjudicated claims database (IMS RWD Claims)

Inpatient hospital

Linkage of hospital charge master, IMS RWD Claims and Social Security Death Index

Complete longitudinal view of all medical care received

Complete longitudinal view of all medical care received Death records

Inpatient hospital

Clinical laboratory

Linkage of clinical lab data and hospital claims or charge master

continued on next page

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INSIGHTS HEOR, PHARMACOEPIDEMIOLOGY & DRUG SAFETY There are a variety of data-linking techniques available, which fall into three general categories:2

1. Match on direct patient identifiers such as Social Security number; typically, these identifiers have not been collected or been available in many databases due to regulatory reasons. 2. Use indirect identifiers such as admittance dates, diagnoses codes, gender and age; this technique is also known as probabilistic or statistical matching and has been used successfully in a variety of circumstances. However, it may be restricted to specialized patient populations3,4 as well as having other limitations.

3. Take a deterministic approach, whereby a unique encrypted ID is created for each patient in any given database prior to extraction of data into a de-identified database.5 Using this method, it is possible to link virtually any patient-level database to another, provided the encrypted ID can be attached prior to data extraction.

Growing applications of database linkage

Deterministic linkage allows answers to complex questions in health outcomes and epidemiology utilizing very large HIPAA-compliant databases by combining data elements from a wide variety of databases. These include fullyadjudicated or open source administrative claims, electronic medical records, inpatient data sources such as charge master data, and patient registries. The same technology is also now being applied to link these data to consumer preference information, social-demographic information, and death index, all of which continue to expand the ability to ask and answer increasingly challenging and interesting research questions.

IMS Health has extensive experience in applying a deterministic approach to build linked datasets to answer complex questions, while maintaining HIPPA privacy rule standards.6 Table 1 shows how the application of this expertise addressed the requirements of the research questions. Through the innovative linkage of patient-level data from diverse datasets it was possible to provide answers which required information on the patient journey as well as clinical detail across treatment settings.

“

2 3 4 5 6

Deterministic linkage allows answers to complex questions in health outcomes and epidemiology utilizing very large HIPAA-compliant databases.

”

Kornegay C, Segal JB. Selection of data sources. In: Velentgas P, Dreyer NA, Nourjah P, et al, eds. Developing a protocol for observational comparative effectiveness research: A user’s guide. AHRQ Publication No. 12(13)-EHC099. Rockville, MD: Agency for Healthcare Research and Quality; January 2013: Chapter 8, pp. 109-28 Herzog, TN, Scheuren FJ, Winkler, WE. Data quality and record linkage techniques. Springer; New York: 2007

Hammill BG, et al. Linking inpatient clinical registry data to Medicare claims data using indirect identifiers. Am Heart J, 2009, June; 157(6): 995–1000 Pasqual SK, et al. Opportunities and challenges in linking information across databases in pediatric cardiovascular medicine. Prog Pediatr Cardiol, 2012, January; 33(1): 21–24

Kohan ME, et al. United States Patent Application 20050256740. Nov 17, 2005.

Blanchette CM, et al. Probabilistic data linkage: A case study of comparative effectiveness in COPD. Drugs Context, 2013; 2013: 212258

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

INSIGHTS COMMERCIAL & MARKET ACCESS

RWE: A new way to engage Integrated Delivery Networks As pharmaceutical manufacturers look for ways to build stronger relationships with their Integrated Delivery Network (IDN) clients, RWE is emerging as a desired infrastructure capability, presenting a window of opportunity to support and collaborate on IDN eﬀorts. If done well, these RWE-related partnerships should provide value for both parties involved but require pharma to expand its mindset beyond product-speciﬁc approaches.

The authors

marla Kessler, mbA is Vice President, RWE Solutions, IMS Health Mkessler@imshealth.com

Jon Resnick, mbA is Vice President and General Manager, RWE Solutions, IMS Health Jresnick@imshealth.com

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INSIGHTS COMMERCIAL & MARKET ACCESS

RWE: A new way to engage Integrated Delivery Networks Capturing a window of opportunity for collaboration The US healthcare industry is paying increasing attention to the growing importance of Integrated Delivery Networks (IDNs). Although there is no single model of an IDN, the term generally describes a linked group of facilities and care providers and may include a payer body as well. IDNs are organized to provide patients with a continuum of care, theoretically enabling them to break down silos of incentives and information sharing that plague disconnected care models.

Pharmaceutical manufacturers recognize IDNs as a critical customer group. Relative to other risk-bearing entities without care delivery capabilities and objectives (eg, MCOs), IDNs are uniquely interested in developing a holistic patient view across settings of care. This increases their appeal as potential collaborators on efforts to improve patient outcomes. However, pharma is still trying to understand how best to serve them. In a recent survey conducted by IMS Healthi RWE emerged as a priority area for IDNs, both in terms of potentially generating value but also one where they have notable internal skill gaps. They use patientlevel, clinical data consistently (Figure 1) for a variety of purposes (Figure 2). i

However, IDNs will need help in using RWE more broadly and consistently. They see pharma as a potential provider of RWE to support this process, but are unsure they can trust the RWE they generate. In the survey, 60% of IDNs cited these trust issues as a reason for not using RWE more, although lack of internal capabilities was also called out (by 55% of IDNs). And while IDNs are using RWE, the survey showed that they focus their work on three to seven therapy areas (TAs) today but plan to look at different TAs in the future. This concentration on a select number of TAs indicates that IDNs would be viable partners for the right manufacturers to approach for a disease-specific RWE program.

Implications for pharma

As with any relationship where partners have opposing interests, progress requires each stakeholder to recognize the role of the other, as well as transparency and a series of incremental steps designed to build trust between the parties. Thus, while IDNs acknowledge that pharmaceutical manufacturers are able to generate more RWE than they can, perceptions of its trustworthiness would be accelerated by the full disclosure of the data, methods and findings (both positive and negative) to an independent third party. And yet their distrust of pharma-generated RWE cannot be ignored.

On-line survey of 70 payers and IDNs conducted by IMS Health in December 2014.

Figure 1: Most frequently used real-world data sources1

Figure 2: How IDNs use RWE today1

IDNs Hospital Data

Formulary Decisions

EMR

Comparing Treatment Costs Patient Management

Pharmacy Prescription Data

Guideline Development

100 85

Disease Insights Physician Claims Data Studies Supplied by Pharma Social Media Data

Development

Performance

Burden of Illness

Applying RCT to Pop Risk Sharing Stimulate RCT Impact

1 Q1: How often do you use each of these data sources to make decisions/monitor activity? Source: 2014 ImS Health Payer RWE survey, n=70 US Payers, including 20 IDNs

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Benefit Design

IDNs

45 30 15

1 Q2: How often does your organization use these types of information with regard to the following potential applications? Source: 2014 ImS Health Payer RWE survey, n=70 US Payers, including 20 IDNs

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

The challenges and opportunities for pharmaceutical manufacturers reside in five key facts:

1. Pharma can benefit from the alignment RWE can drive. Providing more substantial proof, based on reallife use, can elevate brand propositioning by placing its cost into a broader evaluation to better show its benefits and value but also align on the baseline needs for a patient population. 2. IDNs differentiate ‘pharma’ as an industry from individual companies, creating room to build direct relationships. This is similar to the political phenomena where voters will ‘dislike congress’ as a whole but ‘like and consistently vote for their congress person’. As shown in Figure 3, IDNs see each pharmaceutical manufacturer’s credibility distinctly.

3. IDNs need help. In identifying barriers to generating and applying RWE while having a desire to use more of it, IDNs recognize they lack many of the internal analytic and technological skills needed to create more complex RWE. In addition, they are keen to understand how to develop robust RWE and assess RWE that is shared with them. Interest in evaluating RWE was also expressed by payers and manufacturers during a recent IMS HealthJHU Symposium, indicating that a certification process/body to assess RWE is one potential solution (see News feature in this issue of AccessPoint on page 2). 4. IDNs are open to solutions that involve pharma. It was repeatedly stressed in the research that solutions involving pharmaceutical manufacturers are both interesting and not hard to imagine implementing. The current use of pharma-generated RWE today suggests an

opportunity for companies to be involved in its increased generation and application. The involvement of third parties (eg, to validate data and methodologies, create transparency) may be a helpful enabler of future solutions.

5. The window for action for pharma may not last long. IDN openness to collaboration likely reflects their position on the learning curve. Given that pharmaceutical manufacturers have been conducting outcomes research for decades and are building RWE capabilities today, they have valuable skills and experience to bring to the table – but they will need to act quickly while the opportunity exists.

A path towards IDN collaborations

While there is significant variation in a pharmaceutical manufacturer’s reputation for providing credible information to IDNs, now appears to be a uniquely good time to focus on collaborating with them on RWE. This process should begin by understanding how RWE could fit into IDN plans for quality and care management.

The rationale of integrating a delivery network should in no small part involve gaining fundamental value out of the integration. Recent research conducted by IMS Consulting Group with IDNs found they believed the creation of a common patient data platform – or at least linkable data – would be a key enabler of the integration. This would have the goal of allowing them to implement guidelines, programs and pathways across their systems to achieve optimal outcomes and manage healthcare costs, but the first step would be in just understanding their system’s current performance.

Figure 3: Perception that pharma company is credible provider of RWE1

IDNs Pharma Company

Pharma Company

Q16: How credible do you believe the following companies are in providing you RWE you would value/ﬁnd useful? Source: 2014 ImS Health Payer RWE survey, n=70 US Payers, including 20 IDNs

IDNs Pharma Company

Pharma Company

Pharma Company Pharma Company

20 15

Pharma Company Pharma Company

25 35 20 30

continued on next page

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INSIGHTS COMMERCIAL & MARKET ACCESS

However, below are three examples of how pharmaceutical manufacturers with RWE capabilities (RWE Leaders) could partner with IDNs in innovative, valuable ways.

Figure 4: Three levels of IDN data aspiration

Level 1: Understand their current performance

Level 2: Identify areas for improvement and actions for capturing them

Level 3: Implement changes to realize value

Source: ImS Consulting Group research and analysis; n=35 IDNs

This first step can be defined as Level 1 – Understand current performance (Figure 4) and requires IDNs to develop a common platform for electronic information to achieve a more complete picture of their system’s performance. Many are still struggling at this level, sitting on highly fragmented data, especially if they have grown through the acquisition of local hospitals and practices. Even IDNs that analyze EMRs or electronic health records (EHRs) may not be analyzing all of them if they are in incompatible systems.

Some IDNs have moved past Level 1 and are approaching Level 2 – Identify areas for improvement. At this point, they are focusing on improvement efforts for specific disease states. Since these improvements involve clinical care decisions rather than formulary design or other more administrative actions, they typically concentrate on a few disease areas only. IDN priorities here reasonably reflect the cost of the disease and their patient demographics but also their system’s ability to make changes in that disease. This effort can identify best practice in their own system or insights from other systems. All IDNs seem to understand that Level 3 – Implement changes to realize value would be critical for capturing the benefit of integrating healthcare data. However, few have been successful here even in one or two diseases. The challenge is understandable given the difficulty in shifting physician and patient behaviors but it is more addressable when informed by relevant, quality RWE.

Within this context, there are clear areas where pharmaceutical manufacturers could pursue RWE with IDNs. Supporting IDN efforts to integrate their data platforms through pilots or programs (likely through a third party) would not be recommended, being a low value activity for pharma where the main asset they provide is financing.

PAGE 42

1. Provide additional data. As noted, IDNs often sit on highly fragmented data. They may not be analyzing all of this, let alone complementary datasets. RWE Leaders potentially could play a role by helping to bring in other data sources or working to integrate data for analysis in specific priority areas. This could involve an extraction of EMR data by a trusted party to analyze with other data, such as payer claims or even social media, to develop a true picture of the current situation.

2. Provide quality benchmarks and analytics using broader information sets. IDNs that have moved beyond Level 1 and understand their current performance may not be fully prepared to compare it to best clinical practice and/or implications for their financial performance. RWE Leaders can provide insights to support this activity. IMS Health, for example, helped a manufacturer improve relationships with providers facing Pay-for-Performance (P4P) in high-risk patients. Using Healthcare Effectiveness Data and Information Set (HEDIS) measures for quality benchmarks and EMR, the manufacturer was able to help the provider create patient segments based on factors such as BMI and look for ways of contracting to optimize the P4P situation. 3. Develop pilot programs for improving outcomes. Pilot programs can serve to apply learnings and continue to use data to improve outcomes such as compliance. Pharma’s knowledge of diseases, treatments and methodologies, such as predictive analytics, could be especially valuable in helping identify at-risk patients, find rare disease patients, create more tailored treatment models and even change payment approaches to better reflect value. These types of programs can be built on external data that pharma uses to create and validate the algorithms and interfaces and then pulls from the IDN to simplify implementation.

Conclusion

RWE is a critical mechanism for major improvements in healthcare. It creates an opportunity to better understand the current situation and evaluate alternative treatment approaches. IDNs are fundamental stakeholders in applying RWE; working with them to help generate and apply this evidence is thus an important goal for all parties who are committed to improving outcomes for patients and the US healthcare system. Pharma can play a key role in proactively increasing engagement with RWE whilst also benefitting from the additional insights it provides. This article is based on a more detailed IMS Health White Paper “Why Pharma needs to work differently with payers and IDNs on RWE.” To find out more about the research conducted or to request a copy of the full report, please email Marla Kessler at Mkessler@imshealth.com or Jon Resnick at Jresnick@imshealth.com

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Convergence of HTA assessments in Europe – reality or aspiration? Health policy developments across Europe continue to focus on the dual ambition of controlling costs while improving access to innovative drugs. Health Technology Assessments (HTA) are a key lever for appraising the value of medicines to manage pharmaceutical expenditure. With their inﬂuence and number growing in the region there have been moves towards harmonization but as analysis of recent launches shows, many complex and countervailing forces make this a challenging goal.

The author

Natalia balko, mbA is Engagement Manager, RWE Solutions, IMS Health Nbalko@imshealth.com

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INSIGHTS COMMERCIAL & MARKET ACCESS

Convergence of HTA assessments in Europe – reality or aspiration? HTA trends in Europe HTA agencies have been playing a meaningful role in pharmaceutical pricing and reimbursement in Europe for a number of years and will continue to do so. However, their impact can vary due to differences in assessment approach and implementation. Assessment approach

Since they were first established, the various European HTA bodies have continued to evolve their criteria and methodologies for assessment. These typically include: measures of clinical effectiveness and safety; quality of life; cost (including cost-effectiveness or budget impact); and country-specific values (eg, equity). Further, individual countries may have their own specific requirements. In Germany, for example, appropriate comparators are defined by the G-BA (Federal Joint Committee); failure to use an appropriate comparator results in a ‘no additional benefit’ result from the HTA process.

Implementation

Typically, HTA agencies influence access; many also affect reimbursed price. Exceptions are France and Germany, where HTA solely impacts reimbursed price (Figure 1).

Some countries have had a proliferation of regional HTA bodies (eg, Italy) or agencies focused on a subset of therapeutic classes (eg, Denmark for high-cost therapies). With different scopes of influence, the impact of an HTA decision on price, access and ultimately uptake will vary based on the specific system. As implementation of HTA is primarily defined by the pricing and reimbursement structure, there will necessarily be differences by country or region.

Given that implementation will vary from market to market by definition, addressing differences in assessment approach has become the focus of efforts for convergence by policymakers, pharmaceutical manufacturers, HTA agencies and associations, with the goal of achieving greater consistency in evaluation of the underlying evidence.

Given the differences in assessment criteria, methodologies and requirements, HTA decisions among countries can differ substantially for a given product. This becomes challenging for manufacturers in planning development and launch strategies if the same evidence package can be evaluated in different ways, with varying results.

Figure 1: Scope and impact of HTA by market

YES

Germany

Belgium

Bulgaria

Estonia

France Italy

Czechoslovakia

Greece

Slovenia

Turkey

Finland

Lithuania

Netherlands

Poland

Portugal

Romania

Sweden

Spain

Croatia

Cyprus

Denmark

Norway

Impact on Reimbursed Price

Austria

Ireland

Malta NO

Hungary

Slovak Republic

Latvia

Switzerland

YES Impact on Access

PAGE 44

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

The push towards HTA convergence

As countries evolve their HTA systems, there is a natural tendency towards divergence in their evaluations. However, several counterbalancing forces are tempering this:

•

Formal and informal referencing. Increasingly, countries have been referencing the HTA decisions of other markets; in particular, the UK, Sweden, France and Germany are often referenced by neighboring markets or countries with similar value systems. A recent IMS Health analysis found evidence of formal referencing in 10 EU markets and informal referencing in 16 markets. Three markets showed evidence of both formal and informal referencing depending on the timing of reviews, specific topics (eg, cost-effectiveness) and case-by-case needs. Most countries that do not reference today are expected to begin referencing informally in the future. In considering the evaluations of other countries, HTA agencies effectively reduce some of the differences in reviews and methods. Potentially, this also leads to a more consistent evaluation of evidence. European collaboration. Progress is being made towards greater collaboration in assessments among EU markets, with the goal of developing common approaches. In particular, the establishment of EUnetHTA has been instrumental in facilitating this collaboration, in part through the development of methodologies, guidelines and tools.

Reassessments. Conditional reimbursement and requirements for RWE are becoming increasingly common. As an example, Zytiga (abiraterone) gained access in Sweden conditional on an agreement to study real-world use and performance. France recently reevaluated the ‘new oral anticoagulants’, lowering the therapeutic (SMR) value of Pradaxa (dabigatran) and raising that of Eliquis (apixaban) given evidence from real-world practice and the level of value perceived.

RWE generated to support these reassessments increases the evidence base that can be evaluated on an ongoing basis and can address some of the uncertainties that led to different initial decisions. These forces can be expected to moderate divergence but not fully correct for it; some criteria considered by HTA agencies, such as cost or local guidelines, will vary by market and limit the potential for total convergence. However, greater consistency in evidence evaluation, particularly around the perceived level of benefit improvement, would help to reduce inefficiencies and risks for pharmaceutical manufacturers and, potentially, barriers to access and uptake.

Drivers of convergence and divergence in HTA evaluations

To assess the extent of convergence among HTA evaluations, IMS Health analyzed results for 12 recent launches in four therapeutic areas (TA): type 2 diabetes; multiple sclerosis; prostate cancer; and hepatitis C. As a proxy for convergence, the analysis considered the heterogeneity of HTA evaluations between countries and within a country for products in a TA. Convergence in the market would be seen if:

• • •

Views of the evidence submission were similar among countries Products were evaluated similarly across markets

Products in the same class or TA were evaluated using a consistent set of criteria

The TAs were selected to represent characteristics that can differentially affect HTA decisions:

• • • •

Type of TA (traditional vs. specialty) Budget impact

Payer perceived unmet need Level of genericization

continued on next page

Figure 2: Dimensions affecting HTA convergence

Dimension Divergence Nature of Therapeutic Area

High cost

Convergence

Low unmet need, limited diﬀerentiation

Epidemiology

High unmet need, strong product diﬀerentiation

Critical Endpoints Patient-reported outcomes

Surrogate endpoints

Hard endpoints

Trial Design Several plausible comparators

Superiority vs. inferiority

Subgroup deﬁnition

Clear comparator

Source: IMS Health

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INSIGHTS COMMERCIAL & MARKET ACCESS HTA evaluations were compared in France, Germany, Sweden and the UK (England and Scotland) due to the importance of these markets in influencing other EU countries and the perceived differences between the HTA approaches.

The analysis identified three primary dimensions that influence the extent of convergence that can be expected for HTA evaluations across markets (Figure 2). Overall, HTA agencies had greatest alignment for TAs that are more ‘simple’ – that is, they have well-accepted benchmarks (eg, overall survival primary endpoint for prostate cancer), clear subpopulations, and well-accepted treatment paradigms and guidelines.

HTA agencies were least aligned for more ‘complex’ TAs and situations where there is the greatest room for interpretation around the level of improvement. This suggests that there is some implicit convergence in HTA decisions but an opportunity for greater alignment in areas where there is a fundamental difference in the understanding and evaluation of the evidence.

Nature of the TA

Inherent characteristics of a TA can affect the extent to which HTA assessments are likely to diverge. While many of these factors are largely beyond the influence of manufacturers, they provide context for the environment in which the product will be assessed.

•

High unmet need, strong product differentiation. HTA assessments tended to converge on the benchmarks used to evaluate the product and the overall level of clinical benefit afforded. In the case of hepatitis C, for example, HTA agencies were in general agreement that Sovaldi (sofosbuvir) was differentiated, addressed unmet needs and offered clinical benefit.

Epidemiology. Country-level differences in disease epidemiology can influence the perceived need within a disease or specific subgroups and therefore the value that a therapy can bring. In hepatitis C, agencies evaluated genotypes differently, which can be attributed in part to prevalence differences in individual countries.

Low unmet need, limited differentiation. Products are more likely to have divergent HTA evaluations between markets. In type 2 diabetes, for example, the ultimate result of evaluations for the SGLT-2 class varied substantially between markets, even though agencies were relatively consistent in their evaluation of products within the class. The differences may be attributed to a number of factors, including different thresholds for the level of benefit expected.

“ PAGE 46

•

High cost. With HTA agencies varying in their consideration of cost measures, high-cost therapies are inherently subject to divergence as these bodies look to manage cost or budget impact exposure.

While many of these intrinsic TA characteristics cannot be changed by manufacturers, they nevertheless should be considered in designing the trial and evidence submission to understand where divergence is likely and anticipate evidence needs to address underlying differences.

Critical endpoints

Choice of trial endpoints has a substantial impact on efficacy evaluations. HTA agencies varied significantly in their assessment of ‘soft’ endpoints, including the extent to which they afforded a benefit and the weight these endpoints played in decision making. In many cases agencies expressed uncertainty in this assessment, which suggests a role for manufacturers in working with HTA bodies to develop understanding around these endpoints early in development to maximize impact.

•

Hard endpoints. Hard endpoints, such as overall survival in prostate cancer, were evaluated with greatest consistency among countries and products. As these endpoints are well understood and tend to have established benchmarks, agencies generally agree in their evaluations.

Surrogate endpoints. Agencies tend to view surrogate endpoints differently across markets, in part because their impact on overall outcomes may not be well defined. This is especially true for surrogate endpoints that are relatively new within a given TA, such as blood pressure and weight for the SGLT-2 inhibitor class. Given the often lack of general agreement over evaluation of these endpoints, interpretation can vary by market.

Patient-reported outcomes (PROs). Similar to surrogate endpoints, PROs can be interpreted differently by market, depending on acceptance and perception of their value. Different views are compounded because agencies vary in the weight they place on these endpoints (eg, quality of life) and whether they expressly take them into account as a part of the evaluation. Sweden, for example, tended to consider the impact of new prostate cancer therapies on pain more explicitly than other countries.

In many cases, choice of endpoint is dictated by the TA. Nevertheless, manufacturers should anticipate that agencies are likely to have divergent views on surrogate endpoints and PROs, and work with them to improve understanding of these endpoints, which can lead to more consistent evaluation.

Intrinsic therapy area characteristics should be considered in designing the trial and evidence submission to understand where divergence is likely and anticipate evidence needs.

”

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Trial design

Elements of trial design, such as comparator, subgroup definition and powering of the trial (superiority vs. noninferiority) can be a deciding factor in HTA evaluations. This is particularly true in markets like Germany, where use of the ‘wrong’ comparator can result in ‘no additional benefit’ being granted. More complex TAs (many comparators, lack of appropriate standard of care, complicated subgroups) can be subject to divergent assessments because each agency can define its benchmarks and important criteria differently.

•

Comparator selection. Having a clear comparator supports convergence across markets. However, in TAs with multiple plausible comparators, selecting the ‘right’ comparator is critical. In Germany, for example, it is critical to include an appropriate comparator as defined by the G-BA. Failing to do so will create divergence, especially if other markets accept the specific comparator. Choice of comparator influences place within the treatment paradigm so it is important that the comparators selected adequately account for market differences.

Sub-group definition. Subgroups can support positive HTA evaluations by narrowing the population to one that shows greater effectiveness, relative benefit or costeffectiveness. However, unless relevant subpopulations have robust and statistically significant clinical endpoints, agencies can interpret the benefit in these populations differently. In the case of subpopulations that are not clearly defined, this segmentation can be detrimental to the evaluation.

Trial powering (superiority vs. non-inferiority). Superiority trials are typically thought to be demanded by payers. However, they appear to hold greater weight in certain markets, such as France. For example, lack of superiority data for Tecfidera (dimethyl fumarate) was cited as a key reason for its ASMR V rating (no therapeutic benefit); however, it had more positive evaluations in Sweden and the UK, reflecting a lack of HTA convergence in multiple sclerosis overall.

“

Each HTA agency has requirements or preferences for trial design elements; failure to follow these principles can lead to a negative evaluation but also divergence of evaluations across markets, due to different standards. However, trial design presents an opportunity for pharmaceutical manufacturers to align with agencies during drug development to ensure that trial plans meet stakeholder needs. Further, this is an area where EU collaborative efforts and closer alignment with regulators can increase the potential for convergence through clear methods and standards.

Implications

Convergence in HTA assessments has begun but is far from being widespread. A greater degree of convergence is observed in more straightforward situations where benchmarks are well understood, such as clear hard endpoints, high unmet need and strong differentiation, and clear comparators and subgroups. On the other hand, divergence continues in more complex situations which would stand to benefit from greater convergence.

There are several principles that manufacturers should consider during development and pre-launch to increase the likelihood of more consistent evaluations across markets:

• • •

Carefully select appropriate comparators Focus on hard endpoints where possible

Ensure that subpopulations are clearly defined with robust analyses

Efforts to align stakeholders should increase shared understanding of endpoints, benchmarks and trial design elements, such that a piece of evidence is evaluated similarly across countries. However, full convergence is unlikely as countries will still have fundamental differences, for example on the importance of cost or the weight placed on PROs. Manufacturers should consider how TA and product-specific factors are likely to be evaluated differently by each HTA agency to inform trial and launch planning as well as preparations for post-launch RWE generation. It may be possible to influence greater convergence by creating shared understanding of different endpoints and trial design elements. In doing so, manufacturers can reduce risks and inefficiencies associated with divergent evaluations.

Efforts to align stakeholders should increase shared understanding of endpoints, benchmarks and trial design elements, such that a piece of evidence is evaluated similarly across countries.

ACCESSPOINT • VOLUME 5 • ISSUE 10

”

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INSIGHTS COMMERCIAL & MARKET ACCESS

Using RWE to size complex markets for product valuation purposes An increasing pharma focus on specialty indications presents new and growing challenges for market sizing. Case study examples in three disease areas with their own particular complexities, demonstrate the unique ability of RWE to improve accuracy, bias and understanding, and reveal the drivers that are key to its successful use in this context.

The author

Stefan lunglmayr, mbA, m.ENG is Engagement Manager, Strategy and Portfolio Analysis, IMS Consulting Group Slunglmayr@imscg.com

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Enabling clarity and precision in challenging therapy areas Pharmaceutical companies are increasingly looking to serve unmet needs in specialty indications and/or narrowly defined patient profiles. A key factor in both investment and commercial support decisions is the underlying market size of treatable patients which forms the basis of product valuation upon which other assumptions, such as achievable market share, treatment patterns, as well as price and access, can determine how best to support a brand and what to expect in terms of revenue potential. However, with traditional means of market sizing poorly suited to the specialty setting, getting this figure right is a challenge. For example, published literature and syndicated research reports in this area often produce very large ranges of patient numbers, making them difficult to interpret. Triangulation with pharmaceutical sales data is less feasible, particularly for biologics where market measurements are not as accurate and usage covers multiple indications often with individual dosage and treatment duration. Typically, too, these measurements lack the specificity to identify patient segments of interest. Furthermore, in the case of more complex diseases, KOLs and prescribers may be missing the full patient picture, creating a bias in primary market research. And the very nature of niche conditions can make representative sampling problematic.

Why market sizing matters

Market sizing plays an important role in key business decisions throughout the product lifecycle: it informs portfolio investments with insights into the potential of new therapy areas; facilitates evaluation of in-licensing decisions; underpins product valuation for go-/no-go stage decisions during the product development process; supports business planning and allocation of commercial resources for lifecycle management; and enables valuation of label extensions and indication expansion.

At any point in the lifecycle there is a high cost to pay for uninformed assumptions regarding market size. Setting these too high in early development can lead to later revision of a program’s commercial viability; setting them too low can mean the loss of viable business opportunities. After product launch, this can lead to sub-optimal commercial spend and/or indication and label expansions that do not bring expected benefits. There are examples of mature specialty products for which the addressable market size and real-world usage are not precisely known after many years on the market.

Figure 1: Typical therapy area challenges where RWE can add incremental value

Disease characteristics

• Poorly defined patient

population, high number of un/misdiagnosed patients

• Paitent characteristics (eg, •

biomarkers) influencing progression and treatment Slowly progressing disease

Setting of care

Treatment options

• Patients diagnosed and

• Underlying treatments not

treated by multiple specialists across multiple settings of care

• Patients dropping in and out of treatment

specific to a single indication

• High levels of drug •

concomitancy Drug treatments complementary to or competing against surgery or other medical procedures

Source: IMS Health

continued on next page

“

At any point in the lifecycle there is a high cost to pay for uninformed assumptions regarding market size.

ACCESSPOINT • VOLUME 5 • ISSUE 10

”

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INSIGHTS COMMERCIAL & MARKET ACCESS

Figure 2: Case study examples of RWE use in market sizing

Case study

Sizing the endometriosis and uterine fibroids market

Forecasting patients at risk of Rx opioid dependency Revisiting the epidemiology of first-line treated metastatic patients in a common cancer

Main objective

Strategic development portfolio review Brand investment decision Business planning, piloting RWE use in commercial functions

Degree of therapy area challenge where RWE can add incremental value

Geographical scope

Disease characteristics

Setting of care

Treatment options

USA; EU5

High

Europe

High

Low

USA; EU5; Japan

High

Medium

High

The case for RWE in market sizing

market size in therapy areas where the disease characteristics, setting of care and treatment options present particular challenges, as indicated in Figure 1.

Experience shows that increasingly, companies are addressing these challenges in market sizing in two ways: by closely collaborating with their epidemiology departments; and by leveraging RWE − using real-world data (RWD) for measuring patient populations in complex settings and RWE analytics to bridge gaps in data availability. Assuming the existence and accessibility of suitable data (with sufficient history, granularity and coverage) and resources to perform the analyses, RWE can add significant value in assessing

To demonstrate how RWE can add value in market sizing, the following case study examples illustrate its use in overcoming the particular challenges of three very different therapeutic areas: gynecological disorders; Rx opioid addiction; and oncology (Figure 2).

Figure 3: Approximation of the diagnosed and undiagnosed endometriosis and UF market

Figure 4: Iterative approach of RWD analytics and primary market research in market sizing

Narrow ‘precise’ market Endometriosis and UF

Symptomatic but undiagnosed patients who receive endometriosis/UF drug treatments (excluding pain killers) Diagnosed patients Source: IMS Health

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Broader ‘symptoms’ market

Symptomatic patients who do not receive typical endometriosis/UF drug treatments

Application in practice

Validate hypotheses with KOLs and/or prescribers

Develop initial hypotheses informed building on information available in RWD

Conduct analysis on market size based on validated assumptions

Source: IMS Health

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

1. Sizing the endometriosis and uterine fibroid markets

As part of a strategic portfolio review, a company had revisited its development candidates for endometriosis and uterine fibroids (UF). Literature sources had shown a broad range of prevalence values and a previously commissioned observational study had failed to bring clarity. IMS Health was asked to perform an in-depth assessment of market potential in the USA and EU5 using RWE. Why RWE?

•

• •

Disease characteristics: Endometriosis and UF typically present with general symptoms that overlap with a wide range of other conditions, leading to a large number of initial misdiagnoses and a high proportion of undiagnosed and untreated patients. RWE analytics can be applied to identify patients with underlying conditions that are potentially undiagnosed.

Setting of care: Both GPs and specialists are involved in treatment (the latter in more severe cases). RWD can inform progression of disease across settings of care. Treatment options: The drugs typically used to treat these conditions are indicated for many therapy areas and surgery plays an important role in late-stage treatment which reduces the pool of treatable patients. RWD can bring clarity around treatment modalities.

RWE approach

IMS Health investigated the number of patients diagnosed with endometriosis and UF (the ‘narrow’ precise market) versus the number treated for symptoms typically associated with these conditions (the broader ‘symptoms’ market). This incremental patient pool was then further narrowed down by identifying patients who received similar treatments to patients in the diagnosed pool (Figure 3). Hospital medical records (Hospital Episode Statistics), GP medical records (IMS RWD EMR-UK) and IMS RWD Claims– US were then interrogated to estimate the diagnosed and undiagnosed patient pool and to assess treatment dynamics including pharmacological and surgical procedures. A comparison against French hospital medical records (PMSI) was performed to cross-check applicability of UK numbers in other geographies. The results were then extrapolated to other European markets based on their particular healthcare system characteristics. Client impact

Having been faced initially with wide-ranging estimates from the published literature, the company was now able to narrow down the potential market size in these two therapy areas, decreasing uncertainty and enabling more informed product development decisions.

ACCESSPOINT • VOLUME 5 • ISSUE 10

2. Forecasting the Rx opioid dependency market in Europe

A company had developed a product indicated for the treatment of patients addicted to opioids caused by the use of prescription analgesics. This market had been growing significantly in the USA but it was unclear whether or not a similar trend would be observed in Europe. The company commissioned a market sizing assessment and forecast to estimate the patient population at high risk of developing this dependency. Why RWE?

•

Disease characteristics: The number of individuals dependent on Rx opioids is difficult to estimate due to the stigma associated with the condition. Many factors contribute to patients not being identified, including: patients hiding their dependency from the physician; physicians being aware of but not treating the dependency; physicians not recording the dependency in the patient’s medical records. One way around this is to develop patient profiles using assumptions based on a patient’s medical history. RWE analytics can be used to identify patients according to these profiles.

RWE approach

Leveraging a literature review, the expertise of the client medical team and an interview program with KOLs, IMS Health identified potential risk factors in a patient’s history that it was possible to determine from available data. These included, for example, patient diagnoses; type of products dispensed; strength of the products; and duration of treatment. Based on the risk factors and thresholds, an assumption was made as to whether patients were at low, medium or high risk of developing addiction. These parameters were then applied to an analysis using IMS RWD EMR in several European markets collected from office-based physicians to determine the number of patients according to their risk profile. As a next step, a forecast of future patient numbers was developed by projecting underlying opioid drug use trends and applying external events, such as potential prescribing restrictions. Client impact

The analysis provided the company with a good understanding of current market size and the future evolution of patients at high risk of addiction, enabling evidence-based adjustment of its business plans.

continued on next page

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INSIGHTS COMMERCIAL & MARKET ACCESS

Figure 5: Microsimulation approach to simulate disease progression in oncology

Diagnosed with early-stage cancer

Time (Years) Remission Start

Death Treatment

Remission Start

Stage IIIB/IV Treatment

Age : 56 Stage II Biomarker

Remission Start

Patients with characteristics based on RWD

Death Treatment

• Risk of death • Risk of progression

Outcomes and timing dependent on patient characteristics at model start

Source: IMS Health

3. Revisiting epidemiology in cancer using RWE

A company was faced with discrepant epidemiology estimates for the sales forecast of their main product. Available syndicated publications on first-line treated metastatic patients were not transparent or in line with the sales of its drug in the tumor type in question. IMS Health was asked to use the company’s existing RWD assets to create a more transparent forecast of new recurrent and diagnosed metastatic patients for the cancer indication. Why RWE?

•

Characteristics of the disease: Although diagnosis of this particular cancer is fairly straightforward, the long time to progression after early-stage treatment is difficult to quantify. Also, biomarkers play an important role in classifying patients. RWE analytics can both inform patient characteristics and time to progression. Setting of care: Early stage patients undergo surgery (and potential neo-adjuvant or adjuvant drug treatment) and a large number go into remission. Only if they return and progress to the metastatic stage do they again become visible to treating physicians. This leads to a bias towards late-stage patients in conventional market research. RWD can mitigate this bias. Treatment options: There is high treatment concomitancy as well as complex treatment algorithms based on biomarker status. In this case, the uncertainty around drug sales figures added a further layer of complexity for market sizing. RWE analytics can enable issues like this to be circumvented, in the current example by estimating the patient pool progressing rather than drug use.

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RWE approach

As no single individual dataset was available to facilitate determination of market size, a patient microsimulation approach was taken to simulate early-stage disease progression. This combined data from multiple RWD and literature sources (Figure 5).

A mortality analysis was conducted using data from the SEER (Surveillance, Epidemiology and End Results) Program, the leading US public epidemiology database on cancer incidence and survival. This was then linked to the risk of relapse rate using the literature. Syndicated oncology tracking data provided by the company was mapped into the SEER dataset. Linked outpatient and hospital patient records in the UK (CPRD/HES) and PMSI in France combined with the literature were used to determine country-specific treatment distribution. Additionally, features were added to allow simulation of future developments (eg, new markers, improved neoadjuvant and adjuvant treatment, accessibility of cancer care in general) and determine their impact on the available patient pool. Client impact

The company gained a better understanding of metastatic patient numbers to feed into their business planning and a tool to simulate downstream changes in early stage treatment and their impact on market size. A summary of the unique added value enabled by RWE in each of these disease areas is shown in Figure 6.

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Figure 6: Summary of RWE value-add in market sizing in selected case studies

Case Study Example

Incremental understanding in presence of complex disease characteristics

Reduced bias in complex settings of care

Improved accuracy and understanding in complex treatment protocols

Sizing the endometriosis and uterine fibroids market in the EU5 and US

Analyses of co-diagnoses and drug treatment choices provided quantitative insights in the likely undiagnosed population, significantly impacting the market size

Forecasting patients at risk of Rx opioid dependency in Europe

Ability to profile patients by their disease history and Rx drug usage allowed identification of patients at risk, overlooked in

With a better view on patient treatment in different settings of care, the company understood much better the opportunity at different stages of the disease and implications for overall market potential

Clarity on distribution of pharmacological and nonpharmacological treatment modalities for both diagnosed and likely undiagnosed patients led to better understanding of competitive environment

Chosen methodology helped overcome bias in syndicated research towards late-stage patients through comparison with RWD

Advanced RWE analytics to simulate patient progression helped circumvent limitations of measuring the market looking at drug consumption

Revisiting the epidemiology of first-line treated metastatic patients in a common cancer

conventional market research

Tapping into large-scale data sources to assess distribution of patient characteristics and outcomes increased representativeness of analysis

Key success factors for RWE in market sizing

Collectively, these case studies identify a number of factors that are key to the successful use of RWE in market sizing, with broad applicability across similar engagements: 1. Create awareness in Business Development, Product Valuation and Business Planning teams

Although awareness of RWE use is increasing, it is not always seen as the first go-to point when addressing market sizing questions. RWE functions should continue educating business functions in the potential use and benefits of their assets, and facilitate access to data and experienced resources.

2.Integrate RWE with primary market research to gain additional benefit

Primary market research is often conducted separately from RWD analysis. Synergies can be achieved by making this process more iterative, for example by developing hypotheses on patient characteristics found in RWE for indication sizing and validating this with KOLs before finalizing the analysis. This can both increase accuracy and reduce duplication in market research efforts.

3. Determine level of complexity and resource accordingly

Sizing questions that can be addressed by pulls of patient counts combined with extrapolation and triangulation with the literature, typically can be performed by

ACCESSPOINT â&#x20AC;˘ VOLUME 5 â&#x20AC;˘ ISSUE 10

business analysis and experienced data analysts. Taking a more scientific approach will generally slow down critical turnaround time and adds limited value for product valuation purposes. However, in cases similar to the oncology forecast described where complex simulation techniques were combined with analysis of multiple data sources for outcome-specific parameters, it is strongly advised to set up cross-functional teams and let scientists drive the analysis.

4.Keep timeline requirements in mind

Product valuation teams look for fast turnaround of results for decision making. Analyses using RWD in general should be able to compete with commercial primary market research in many instances where no formal study protocol submissions are required. However, companies must ensure that resource capacity to conduct studies is available at the right time. This could be achieved through building in-house capabilities (eg, analytics Centers of Excellence), or ad interim supported by seamless cooperation with third parties for accessing in-house RWD assets.

The author gratefully acknowledges the contributions of Andy Tisman, Senior Principal, Consumer Health, IMS Health, Tim Davis, Principal, Strategy & Portfolio Analysis, IMS Consulting Group, and Matthew Radford, Senior Consultant, HEOR, IMS Health, to this article.

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INSIGHTS RWE PLATFORM DEVELOPERS

Building innovative, effective real-world evidence platforms As more pharmaceutical companies pursue RWE as a core capability in their organization, they have been increasing their investment in integrated evidence platforms. With a unique and objective market perspective, supported by our experience of working with companies in this area, we consider the lessons learned and the key drivers behind successful implementation.

The authors

Ian bonzani, PHD, bSC is Principal, RWE Solutions, IMS Health Ibonzani@imshealth.com

marla Kessler, mbA is Vice President, RWE Solutions, IMS Health Mkessler@imshealth.com

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Four ‘secrets’ to successful implementation Over the past five years, pharmaceutical companies have been significantly increasing their investment in RWE platforms as they look to make RWE a core capability. Integrated evidence platforms are systems that access and identify fit-for-purpose RWD sources, use IT solutions to host, integrate and enable access to those sources, and provide frontend user access and interrogation tools and service models to address varied internal and external evidence needs across a number of stakeholders. During this time, IMS Health has had the unique opportunity

to work with more than 10 pharmaceutical organizations to

collaboratively scope, build and run a number of evidence

platforms across a variety of geographies, therapeutic areas

(TAs), data sources and applications. This article reflects that experience, including assessments made during numerous

benchmarking exercises.

Varied approaches but common themes

Companies have developed enterprise RWE solutions in a

variety of ways once they have made the commitment to

move beyond ad-hoc studies. Some platform builders have kept them almost exclusively as scientific research

platforms, even separating out commercial functions from use. Others have developed fully integrated, cross-

functional capabilities. A few have tried to build the

platform across the entire business while others have

looked to support specific therapy area/franchise evidence needs. Although many platforms have been built as a

reaction to a brand crisis or a slower-moving portfolio threat, there are clear signs of a market shift to more systematic and proactive RWE development.

Based on objective observations of these varied approaches, it is possible to identify common themes in terms of what makes these platforms successful. This is based on a

quantitative and qualitative blend of their ability to improve not only internal performance but also engagement efforts

with a variety of external customers (eg, regulators, payers, providers and patients).

Keys to an effective evidence platform SECRET #1

It’s all about the therapy area

One of the key pitfalls is to view all RWE as the same,

regardless of application. While it can make sense to look at RWE at the enterprise level across the entire portfolio − and many decisions such as IT programs and governance

structures can be consistent across the organization − the need to match RWD requirements and RWE efforts to the

way the evidence will be used, quickly becomes dependent on the medical area and competitive dynamics.

Success is achieved when the RWE approach meets the core

evidence needs of a brand or franchise, requiring a TA focus

to ensure that what is to be created will generate immediate and lasting value. In this way, the type of evidence required as well as the thresholds become much clearer, revealing

the specific applications needed (eg, commercial insights to plan brand strategies; value dossiers with unique value propositions; phase IV trials to prove ongoing value).

A TA approach also enables RWE to rapidly become a core

part of ‘business as usual’ functions and decision making processes for a key brand or franchise because it solves

their immediate challenges. In order to gain traction, it must be useful to them. If experience can be leveraged

across franchises, then movement to enterprise solutions

can be exploited. Thus, the TA solution can often empower a

movement to enterprise solutions.

Without this focus, companies often end up with a vast

amount of non-specific data in a very powerful box, but

without the use cases, awareness, capabilities or capacity to turn the data into meaningful insights. It has become

abundantly clear that platform success is not just about

having big volumes of data, but rather having the right data

and fit-for-purpose solutions to efficiently and credibly turn that into insights.

A platform can become a tool of the franchise to proactively

support its evolving RWE strategies – which is where the

value of platforms resides. The role of franchise teams and

the value that platforms provide directly align; hence a franchise approach is critical to success.

continued on next page

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INSIGHTS RWE PLATFORM DEVELOPERS SECRET #2

There is no ‘I’ in platform success: Cross-team collaboration is critical in both the sell and execution stages

Given the level of resource, time and budget investment in

these platforms, it is essential to involve all parties early on

in the scoping, business-case building and internal buy-in activities. However, a strong commercial voice and

leadership are essential to help gain momentum.

The strength of evidence platforms lies in their number of

SECRET #3

Advertise: Build a platform brand and target quick wins Critical to creating RWE use and user ‘stickiness’ is to create a distinct brand for the platform. It has to be seen as an

asset that is delivering value for the organization. Ascribing it a brand identity enables manufacturers to discuss it both internally and externally as a credible and useful asset, as well as ensuring early awareness and the ability to build a positive support community across the organization.

Although not always publicized, IMS Health experience

uses and users; this means identifying their potential

shows that clients are increasingly using branding as a way

possible in the scoping process, which requires the

having a brand name is not the end; targeting the

applications and the insights they can deliver as early as inclusion of medical, safety & epidemiology, P&MA, HEOR and commercial in the discussion.

In addition, it is also important to determine and define the respective roles of global HQ and individual countries in

terms of platform users and consumers, and ensure these

are well understood. To maximize impact and ensure quality and consistency of messaging, this should reflect global strategy and oversight with local execution:

•

Global: Responsible for driving the investment case and

support across the franchise; developing the global

RWE strategy; ensuring that the vision and

information/use governance of the platform is

maintained; sharing cross-market insights and

•

learnings; and building new capabilities.

Local: Responsible for supporting in-country data

identification, sourcing and evaluation; building

external relationships with customers through

RWE-enabled insight-based engagement and

dissemination; and leading and driving local studies,

including analytic execution.

This collaborative approach also helps to overcome another critical issue associated with RWD/RWE: awareness-

building in terms of uses and insight dissemination across

teams and geographies. For example, the initiative may be led by HEOR and P&MA but with the close involvement of brand and medical colleagues.

Experience shows that when the RWE efforts are ringfenced off as a specialized function, efforts fail to gain

traction. This usually results in under-leveraged platforms and an overall worse ROI in terms of both insight volume and impact. However, it is equally important that as the users and uses of the platforms increase this occurs in a governed and managed way – due to the inherent risks

associated with information flows around and outside of the organization.

PAGE 56

to translate RWE from concept into practice. However,

generation of quick-win insights (either through studies or ad-hoc pieces of exploratory analyses) is the next critical piece for gaining traction in a number of areas:

• • •

Justifying the large build-phase investment required for

platform set-up

Creating strong and immediate first franchise and

organization impression

Showing skeptics how the conceptual translates into

business value and converting these individuals into new users and consumers of RWE

These are all ‘reasons to believe’ in the platform. Success here lies in the ability to leverage foundational

and instantly accessible data sources to address priority questions of the franchise. For one IMS Health client,

a franchise platform enabled an immediate response to a critical emerging competitor issue by delivering RWD insights into treatment patterns, while the company

prepared subsequent more high-risk studies of safety and comparative effectiveness.

Trying to create or access that single ‘unicorn’ data source

or data-point before producing any insights will inevitably

result in impatience and loss of value. In a further example,

a client was able to generate the first piece of evidence from the platform within the initial three months of its

implementation, without slowing down background data

sourcing priorities, allowing it to build momentum and an

evidence story.

Finding these quick wins requires a core understanding of

the business needs and detailed mapping of these needs to a data sourcing and access strategy; failure to do so will delay

the insights produced or result in the production of insights

that are not seen as a priority for the franchise – both of which are unhelpful for platform business.

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

SECRET #4

Conclusion

stakeholder engagement, going beyond the brand

The success of teams and companies to build platforms that

The value of RWE to the external community is in providing

entire organization, provides helpful guidance for others

The halo effort of knowledge: Elevate evidence to elevate

a view of the world that reflects routine clinical practice and elevating disease understanding and patient outcomes

can create a stronger foundation of RWE to benefit the looking to achieve their own RWE goals.

beyond the level of a single brand. RWD and an evidence

If the platform is created flexibly enough to integrate new

relies on setting a vision and strategy that aim to look at

an integral part of the development and commercialization

platform are directly supportive of this but the achievement

outcomes, insights and customer engagement in a different

way. This can help products at launch by better showing the

needs in the market as well as over time to demonstrate

data as the organization’s RWE needs grow, it will become

processes. However, these experiences show that platform development has to be purposeful and nurtured with a vision for its longer-term use, including supporting

stakeholders on issues beyond products.

their value.

Although this challenges pharma to move beyond a brand focus in the short term, portfolio success is achievable

through the two-way exchange of new and credible TA-

centric insights. For example, in the US, Integrated Delivery Networks indicate that they are eager to use more RWE to

improve patient management and outcomes but lack the

skills and resources to achieve it.1 They are open to working

with pharma in those areas but want a non-product

approach since drugs are often only a small driver of

performance when looking at care delivery.

This may require a new way of supporting the brand or

engaging with stakeholders around the evidence generated

but ultimately it can result in owning the disease area from

an insight generation and understanding perspective. One client has been able to leverage its platforms in key

franchises to help stakeholders identify unmet needs and understand treatment patterns, epidemiological profiles,

geographic differences in treatment and healthcare use, and how these all translate into real patient outcomes.

“

Platform success is not just about having big volumes of data, but rather having the right data and fit-for-purpose solutions to efficiently and credibly turn that into insights.

”

On-line survey of 70 payers and IDNs conducted by IMS Health in December 2014.

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INSIGHTS RWE PLATFORM DEVELOPERS

T-shaped guided RWD portfolios RWD is increasingly accessed for decision making but often in the absence of a systematic process for ensuring that it is ďŹ t for purpose. A T-shaped approach which acknowledges the need to build a portfolio of broad and deep data assets allows maximum value to be derived from RWD and the type of analyses that were previously possible only through observational studies and primary research.

The authors

Ashley Woolmore, D.ClIN.PSYCH, mbA is Senior Principal, RWE Solutions, IMS Health Awoolmore@imscg.com

Daniel Simpson, m.bIOCHEm is Senior Principal, RWE Solutions, IMS Health Dsimpson@imscg.com

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Addressing the trade-off between breadth and depth RWD and the evidence that evolves from it is increasingly being used to support critical decisions in R&D, medical, drug safety and market access. It allows companies to make choices, engage with healthcare stakeholders and demonstrate the value of their medicines, based on millions of patient healthcare encounters. In recognition of its growing importance, and in addition to collecting data through primary observational research, companies have been moving quickly to acquire ‘off-the-shelf’ RWD datasets which exist as a byproduct of medical transactions captured from everyday clinical practice. This RWD includes longitudinal prescription data, integrated claims data, physician panels, patient registries and EMRs. Companies have rightly started to migrate away from prospective data collection to address their research needs. But as they enter the world of secondary data acquisition, many have been too linear and transactional in purchasing RWD without a clear view of how a particular type of data or collection of datasets can be used across the organization and into the future. This less than efficient approach to RWD reflects errors in five key areas: 1. Lack of a comprehensive approach for assessing data needs, categorizing research questions and navigating data sources, leading to disconnected purchases

2. Settling for incomplete datasets, which may be readily available but not always the best solution and often the tip of the iceberg in terms of what could be achieved

3. Poor prioritization of investments in datasets due to their complex attributes and caveats, which make it difficult to determine their relative value in addressing specific research questions and drive purchases that are not fit for purpose, are sub-scale or lack the necessary precision

4. Failure to anticipate long-term data needs and the lead time to acquire suitable data

5. Pursuit of a higher burden of proof than is required, or even possible, in situations when a directional answer may be sufficient and more cost-effective

Recognizing a need for trade-offs

Unlike customized studies, which are intended to address a specific business issue, ‘off-the-shelf’ RWD datasets exist for reasons that are entirely independent of the industry’s research requirements and are thus ill-designed to meet many of them. No single one contains all the necessary information to answer a company’s questions regarding patients’ real-world treatment experience.

A fundamental characteristic of RWD is that it is extremely rare for any dataset to include all four key elements, namely: clinically rich, high-quality, longitudinal data, with sufficiently large numbers of patients. In practice, there is always a compromise between breadth and depth and that a collection of datasets will be needed. Research is also limited by the ready availability of really high-quality data assets. The world of data collection, especially electronic, is still quite nascent. Although some centers have prioritized the development of their information infrastructure and use it to help improve clinical care, others are less sophisticated in collecting and managing the quality of their data. The information being sought may not be captured or readily available in the countries, timeframe or format required. And the issues of coding can further complicate the usability of the (see article in this issue of AccessPoint on page 62). To make the best use of RWD, each business question must be matched to the most appropriate data source available, based on the line of enquiry and the particular characteristics of the dataset. In this context ‘available’ does not automatically mean commercially available; included in that definition are sources that need to be accessed using different models. This will mean accessing multiple sources, accepting that the match will never be perfect and that trade-offs will have to be made.

In order to build an efficient RWD strategy, companies must invest in creating a portfolio of data assets that are sufficiently specific to their research foci but also offer broad utility to meet the nuanced needs of different functions across the organization. Each element must be carefully scrutinized to ensure the investment is costeffective and the data acquisition fit for purpose.

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To make the best use of RWD, each business question must be matched to the most appropriate data source available, based on the line of enquiry and the particular characteristics of the dataset.

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INSIGHTS RWE PLATFORM DEVELOPERS A well-organized group of datasets will serve a company in the short, medium and long term, positioning them to answer questions around population characteristics, clinical practices, product effectiveness, comparative effectiveness and disease characteristics, as well as conduct deep scientific investigations. The identification, analysis and matching of sources to research questions is referred to here as a nascent capability of ‘data navigation’.

T-shaped dichotomy

Longstanding experience of working with pharmaceutical companies and witnessing some of the common mistakes that are made in addressing RWD requirements, illustrates the value of differentiating business questions and systematically assessing which data sources will address them. This approach puts companies on the right path to building a comprehensive and flexible portfolio of RWD assets.

Some questions (eg, around epidemiology, treatment patterns, clinical care or product use in the patient population) necessarily warrant a broad, comprehensive view of a large group of patients. However, the constraint of taking a broader view is the lack of clinical depth. Breadth can be achieved − RWD sources such as disease registries1 or national databases can span broad, near population-level cohorts − but only with minimal clinical information about each individual patient.

The opposite also holds true in that deep, clinically rich data can be obtained (from modules of specialized EMRs, for example) but only for a defined and relatively finite patient population, typically with coverage of between 5-10% of a total market population.

A good portfolio of RWD assets adheres to the T-shaped principle

‘T-shaped’ is thus a way of guiding a company’s future strategy around RWD as it identifies what questions are being asked and which are the right sources (off-the-shelf or otherwise) that will help deliver answers to those key questions. It allows companies to adopt a more concise, segmented and intelligent use of RWD based on acceptance that there are different formats of the data which, when used in the right way, can deliver a more complete, focused answer.

Companies considering how they should acquire or procure their set of RWD assets should thus know what questions they want to ask, then construct a portfolio with a choiceful selection of stems and bars that enables them to answer all of their questions. In doing so, they should bear in mind their evolving needs, the potential of different data access models and the broader context of RWD’s value in the organization’s investment in insight generation.

Figure 1: T-shaped principle reflects the need to consider both breadth and depth when accessing the most appropriate fact base.

BROAD

Nationally relevant databases

Range of data types

Augmented datasets

DEEP

Biobanks, labs, registries

Clinically rich, deep data for a discrete population of patients typically with coverage of 5-10% of a total market population.

Complete disease views can be created through sophisticated approaches to supplement data including: eCRF, ePRO, NLP and rapid custom sourcing/linkage

Deep, flexible therapy-area-specific data

Population coverage Source: ImS Health

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Within such a portfolio, the different types of sources need to be analyzed in an integrated way. Bar data reveals the nuances and variations across the breadth of clinical settings. It is essential to the interpretation of the data obtained through ‘stems’ but providing knowledge of the specificities and perhaps idiosyncrasies of their particular patient populations and clinical settings. Furthermore, multiple stems need to be considered together, in order to achieve sufficient cohort size or to provide a diverse group of patients.

best practice

Companies that succeed in accessing the right RWD will:

• • • • • • • •

Understand the limitations of each RWD source and the need to make trade-offs Spend time matching datasets to current and anticipated needs

Avoid a fragmented approach to acquiring RWD

Adopt a portfolio mindset that leverages a combination of datasets to achieve the best answer

Plan to ensure that the highest priority diseases areas are appropriately supported Anticipate future evidence needs and start building access now Focus on enhancing available data

Be open to new access models beyond ‘data purchase’

A step towards connectivity

In moving forward with RWD, the T-shaped approach also paves the way for a new era of connectivity. The link that exists between ‘stem’ data and the clinical setting provides an environment where it is possible not only to observe but also, through the connection to that environment (either virtually or otherwise), to contextualize those observations, supported by qualitative narrative from those who work there.

Conclusion

In a world where there no single RWD dataset can fulfill all their research and information requirements, companies need to prioritize their business questions and map them to the appropriate RWD source. With the proper sourcing strategy and a long-term view of data needs and availability, the shortcomings of any single source can be overcome and a company’s information needs met. Constructing a T-shaped guided RWD portfolio allows maximum value to be derived from RWD sources and enables the type of deep analyses that previously have only been possible through observational studies and primary data collection. By following the rule of T-shaped data, companies will be enabled to make the necessary trade-off decisions when acquiring RWD and operate within a more flexible model where the data is constantly refreshed and available on demand for multiple types of users. Those that successfully construct a T-shaped portfolio of RWD assets will have a cost-effective system capable of answering a wide range of business questions now and in the future. They will be able to understand clinical practices, analyze how patients interact with the healthcare system, perform broad evaluations at the product level, and explore a disease area in depth. With faster speed to insight they will improve decision making across the organization and throughout the product lifecycle. To realize full value from their RWD investment, they will need to underpin their strategy with the right infrastructure and organizational principles for working within this new model successfully.

For example, moving from merely analyzing data from a group of primary care practices in a region, to interpreting those analyses potentially with a view to proposing an appropriate public health intervention to change the way in which care is organized, or educate patients in a better way. This can only be achieved because of the additional context obtained through narrative from known individuals and the ability to engage with them and their actions in that system.

“ 1

Constructing a T-shaped guided RWD portfolio allows maximum value to be derived from RWD sources and enables deep analyses that previously have only been possible through observational studies and primary data collection.

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Defined here as databases created and maintained by health systems/governments for population management and care planning rather than databases created by manufacturers or researchers as part of non-observational studies used to test the safety or efficacy of a drug in a given real-world context.

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INSIGHTS RWE PLATFORM DEVELOPERS

The challenges of codes in real-world data Real-world data is the backbone of evidence generation but as a resource created for very diﬀerent purposes, and its confounding characteristics can be a challenge for unfamiliar users. Here we consider the particular complexities of coding – a critical prerequisite for data aggregation but one that demands quite speciﬁc solutions to tap into and realize the value of the underlying content.

The author

Christian Reich, mD, PHD Vice President, RWE Solutions, IMS Health Creich@us.imshealth.com

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Addressing the ‘curse’ of RWE Real-world data (RWD) – most of it – is coded. Not much is represented in textual form. Things that happen to us as patients – diagnoses, complaints and symptoms, drug treatments, lab tests, diagnostic and therapeutic procedures and applications of medical devices – are represented by codes from standardized coding schemes.

This is an amazing fact given that we are talking about healthcare – an industry that has been lagging in computerization and the introduction of industrialized processes by decades. In fact, these coding schemes are not only pervasive but they are also designed to be comprehensive, projecting every relevant possible situation in the typical healthcare settings. The reason lies in the primary purpose of collecting the data when it first became digital: mortality and morbidity reporting and reimbursement claims processing. Electronic medical records (EMR) were very rare at the time and even today still have some way to go to create a complete representation of the facts in structural form: discharge summaries and pathology reports are often still just plain text. The first wave of healthcare digitization came in the 1980s with systems that helped to process claims. In order to make that a repeatable and reliable process, all the various services were standardized and assigned a code. Since the services required justification of why they were rendered, the justifications themselves were coded as well. This brought us coding conventions for procedures and diagnoses. Next came drugs, this time for pharmacy reimbursement by payers for filling prescription medicines and for the FDA to know what products were on the market (resulting in the introduction of the National Drug Code (NDC)). At least, some would claim with money at stake the quality of this data should be more reliable.

All this would be just an interesting fact were it not that the entire RWE industry is based on it. Without the codes it would be impossible to aggregate data at the necessary scale for it to become the foundation of evidence generation. Neither would it be possible to put together and interrogate databases of more than 80 million patients and explore the natural history of a condition, its treatments and their effectiveness, and compare them with other treatments or to no treatment at all. While the number is impressive, the downside is that this data is ‘shallow’ with a lot of the detail missing and with a half-life of six months per patient. Nevertheless, compared to the epidemiological research of old – some poor analyst in the basement of a hospital

“

sifting through dusty patient records and counting facts using a clipboard – this is an amazing leap forward and opens monumental opportunities in understanding and improving disease and healthcare. That’s the good news.

The bad news is that everything is coded; the codes are all we have and we must live with them. But that isn’t always easy.

Curses of coding

The problem is that codes are made for a purpose – the management of healthcare processes (claim reimbursement or medical transactions). This means they represent facts that are relevant for those particular transactions but not necessarily for understanding a patient’s underlying etiological and pathogenetic processes or their treatments. Specifically, they make life difficult in four key ways: 1. Overabundance of coding schemes: There is a myriad of competing coding schemes representing more or less the same domains. For example, there is ICD9, ICD10 (with national versions), Read and SNOMED for diagnoses. There are more than half a dozen coding schemes for drugs: NDC, GPI, FDB, Multum, Multilex, DM+D, Gemscript as well as Read and SNOMED. The situation for lab tests and procedures is similar. Unless crosswalks or mapping is provided, it is down to the analyst to navigate this Babylonian language jumble. However, it takes a long time to become truly ‘fluent’ in these terminologies, making such analysts a rare breed, which is a big problem for the customers.

2. Ambiguity in precision: For some common conditions there are multiple codes representing various details of the disease. In the case of diabetes mellitus, for example, there are 95 ICD9 codes. This level of detail is due to diabetes being a very prevalent disease with many different complications. In the case of HIV, another example of a frequent disease, there are only four codes in ICD9. Code systems are designed to be comprehensive. However, in some cases the enumeration of all possible variants of a disease would result in very large amounts of codes, and the medical community might not agree on the exact composition of such an enumeration. For those cases, the concept ‘not otherwise specified’ or NOS was created. For example, ICD9CM 362.14 stands for “Retinal microaneurysms NOS”, meaning any microaneurysm that does not have a cause coded in another retinopathy, such as hypertensive or diabetic retinopathy.

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Without codes it would be impossible to aggregate data at the necessary scale for it to become the foundation of evidence generation... but living with them isn’t always easy.

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INSIGHTS RWE PLATFORM DEVELOPERS

However, to understand exactly which conditions are summed up in this NOS, the analyst will need to know all the codes where the microaneurysms are ‘specified’. Hence, the meaning of this code depends on the meaning of an unknown number of other codes. This may be an acceptable solution for billing, but not for dissecting precise medical conditions. Then there are codes which are just general catch-all concepts. One particularly interesting one is 729.99 ‘Other disorders of soft tissue’, which is completely useless for observational research or RWE generation since half of all diseases could be construed as a disorder of a soft tissue.

3. Inconsistent hierarchical structure: When a physician diagnoses a disease, the result will reflect the level of work-up. For example, a patient with a dilated cardiomyopathy due to taurine deficiency will present first as a cardiomyopathy or disease of the myocardium leading to a dilation of the heart. After excluding primary causes, such as ischemic or infectious cardiomyopathies, the search will go into causes of the disease that are the result of another illness, such as a metabolic disorder or nutrient deficiency. Only at the end will the cause be determined as lack of taurine, a major constituent of bile. However, each of these are legitimate diagnoses, nested into each other: a secondary cardiomyopathy is a cardiomyopathy but not necessarily the other way around.

All of this matters because the coding schemes make it look as though there is a linear list of all possible impairments and that one has nothing to do with the other. Statistical analyses do the same thing, using a code as a single covariate to calculate risk or probability. In other words, they treat codes as in a one-man, one-vote

system. In reality, these conditions are all heavily interdependent on each other; our ability to generate precise evidence depends on the ability to understand these relationships.

Some code systems have hierarchical relationships inbuilt. SNOMED-CT, for example, has a fully developed hierarchy of diseases and other domains. Other coding systems are less robust. ICD9, for example, features a simple three-layer hierarchy micro-coded in the codes. However, this hierarchy is very primitive, only allowing up to one parent for each code; some of the hierarchical relationships are daring at best. For example, ICD9 785 ‘Symptoms involving cardiovascular system’ has descendants of such completely unrelated conditions as arrhythmias, abnormal heart sounds, gangrene, enlargement of lymph nodes (which are not part of the cardiovascular system) and shock (Figure 1).

3. Mixing of domains: Coding schemes are controlled vocabularies for a certain area or domain of medicine – diagnoses and conditions, drugs, devices, procedures, tests, etc. That is how they start. Then, due to their role in organizing the healthcare processes, those strict limitations are broken down by a growing number of exceptions. For example, the coding scheme CPT4 stands for ‘Current Procedural Terminology, 4th Edition’. The assumption is that the codes contain procedures. Indeed, CPT4 has almost 12,000 codes for procedures that can be administered by the provider. However, it also contains over 600 quality survey codes, such as 0583F ‘Transfer of care checklist used (Peri2)’, and about 100 drugs, mostly vaccines. HCPCS, another coding system commonly assumed to represent procedures in the USA, has only a minority of about 1,000 procedures but 3,500 medical devices, such as L7007 ‘Electric hand, switch or myoelectric controlled, adult’ or a simple thing such as L7360 ‘Six volt battery’.

Figure 1: Relationships of medical entities

Anatomical Site Lower respiratory tract structure

Entire lung

Lung structure

Clinical Finding (Disease) Bacterial lower respiratory infection

Infectious disease of lung

Myco bacteriosis

Pneumonitis

Pulmonary disease due to mycobacteria

Tuberculosis

Nonphotochromogenic mycobacteria

Finding site Granulomatous infection

Exudative granulomatous inflammation

Associated morphology

Necrotizing granulomatous inflammation

Tuberculosis of lung with cavitation

Pulmonary tuberculosis

Isolated tracheal or bronchial tuberculosis

Causative agent

Tuberculous fibrosis of lung

Slow growing mycobacteria

Mycobacterium tuberculosis complex

Micro-organism

Anatomical Site Source: IMS Health

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

The solutions that can systematically address the issues presented by the coding schemes and enable reliable evidence generation need to include two aspects: a comprehensive map of the entire semantic space of medical entities, and a tool to navigate it:

Figure 2: Composition of select vocabularies

Observations Drugs Procedures Devices Conditions

GPI NDC 624,965

•

SNOMED 395,822 ICD10

•

MedDRA 96,494

HCPCS

CPT4

ICD9CM

Source: IMS Health

HCPCS even contains diagnoses, such as G8848 ‘Mild obstructive sleep apnea’ (Figure 2).

None of these issues are insurmountable, providing the analyst knows, for example, to find sleep apnea patients in a procedure coding system and is familiar with all the other coding idiosyncrasies. However, while this is already a problem for an integrator who is intimately familiar with the data, it is a bigger one for the customer. Fortunately, solutions do exist.

Cracking the code

Coding schemes are perceived to make it hard to generate reliable evidence, particularly in ensuring the right code lists representing a certain patient population and that nothing has been left out. They also call for in-depth knowledge of the underlying healthcare system in which the codes are used, creating an additional burden when generating evidence across different countries.

“

•

Master Catalog, containing the universe of coding schemes and their codes, including lifecycle information such as deprecation and succession to keep them fresh for actual use in RWD. Currently, users trying to access that information have to select from public websites of unclear quality, one for each coding schemes.

Mapping between equivalent codes. Equivalence is defined here as supporting the purpose of a certain evidence generation, rather than any type of semantic equivalence. This will allow cross-walking between coding systems.

Hierarchical grouping of codes. Such hierarchies need to be pre-populated for typical drug classes and disease hierarchies, etc, but should allow user-defined groupings as well. Lateral or semantic relationships between codes. These represent medical facts, such as indications of drugs, complications of procedures, etc.

The problems have been recognized. For example, the OMOP Common Data Model, which is geared towards evidence generation from observational data, includes Standardized Vocabularies with mapping, relationships and hierarchical classes. There are also commercial providers of medical terminologies, such as Health Language, Intelligent Medical Objects or Appelon. However, none of these solutions really solve the problem for the researchers: allowing the generation of evidence on the basis of a robust understanding of the semantic space of the involved medical concepts or entities. Future solutions of the IMS Health application and technology platform Evidence 360™ will incorporate this functionality, providing the user with self-service tools to navigate through the maze of domains, schemas and codes and allow generation of the same type of evidence reliably across all IMS Health data assets, regardless of the healthcare system of origin or type of data capture. Existing open-source or public solutions such as the UMLS or the OMOP Standardized Vocabularies can serve as a starting point for a comprehensive and industrialized solution to the problem.

Solutions that can systematically address the issues and enable reliable evidence generation need to include a comprehensive map of the entire semantic space of medical entities and a tool to navigate it.

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INSIGHTS RWE PLATFORM DEVELOPERS

Accessing the right RWD for your evidence strategy Despite the increasing capture of relevant medical information, the right combination of high-quality sources of RWD that can enable consistent evidence creation across multiple geographies remains hard to ďŹ nd. manufacturers are often faced with limited options to supplement foundational syndicated RWD to address the breadth of research question and, in turn, depend on timeconsuming and expensive prospective observational research. With the right approach to navigating RWD sources, these companies can build rich, useful RWD portfolios more eďŹ&#x192;ciently.

The author

Filip Dosselaere, PHD, mSC is Director, Supplier Services, RWE Solutions, IMS Health Fdosselaere@be.imshealth.com

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IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

building fit-for-purpose RWD portfolios RWE is increasingly being leveraged to generate insights about current clinical practice, disease characteristics, treatment outcomes and related costs. The research questions are growing more complex and demand specific views beyond foundational EMR and claims resources typically used. As a result, manufacturers traditionally consider expensive and time-consuming prospective studies or focus on different research questions. The good news is that healthcare delivery is increasingly supported by health information technology (HIT) creating additional electronic data sources that can be used as raw RWD ingredients for RWE. While the storage of electronic data is not a new phenomenon, what is changing is that stored data is being made more accessible and integrated with other data sources to support cost-effective, highquality care delivery at an individual patient level. Lower barriers of data entry, also supported by mobile devices, combined with changing electronic health record systems that can exchange data with other applications, are slowly driving greater capture and use of relevant medical information about the patient. However, despite the positive trend towards better and integrated use of HIT systems, researchers still struggle to find these high-quality RWD sources. In essence, the RWD supply and demand market today is still immature and highly non-transparent with imperfect information available to both RWD suppliers and consumers.

Current challenges of RWD supply

From the supply perspective, the RWD market is first and foremost highly fragmented. Every healthcare provider, hospital or care delivery facility is a potential source of clinically rich RWD, although typically covering a relatively small patient population. Clearly, there are established aggregated datasets covering larger patient populations but their availability and potential use differs greatly between countries and they typically lack the clinical richness required for certain evidence generation.

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The second challenge is that RWD in reality is what could be called ‘dirty’ data, typically being a mix of structured, semi-structured and unstructured information. This reflects the large volume of free-text physician notes that are still in use. Moreover, data is being captured with varying levels of quality and completeness, is often stored in multiple systems using different standards and formats even within the same care setting, and there is limited linkage/connectivity across settings of care. This leads to wide variation in the clinical depth, quality, completeness, longitudinality – and thus the resulting value – of the different RWD sources.

Finally, the protection of patient confidentiality and related data security and use is critical in dealing with patient-level information for research purposes. However, variation in privacy laws across different regions and countries, combined with general lack of awareness around appropriate de-identification techniques and adequate data governance standards, can concern data source owners when it comes to sharing their data with third parties. Consequently, they may impose access restrictions, making it challenging to use the data within those usage rights. In some cases, access is blocked altogether. Against this background, and with the high and specific expectations about content and data availability from the demand side, it can be difficult for the data consumer and data source owner to find each other and build a trust basis that enables optimal use and insight generation from the RWD.

There are hurdles at the various stages of engagement towards ultimately finding a sustainable collaboration model. As a result, life science manufacturers still turn too easily to the well-known alternative of running more expensive prospective observational studies.

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The RWD supply and demand market is still immature and highly non-transparent with imperfect information available to both RWD suppliers and consumers.

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INSIGHTS RWE PLATFORM DEVELOPERS

Solutions for accessing RWD sources

Even given the supply-side challenges, there is growing recognition that the long-term benefits and value generation from a strategically developed RWD portfolio supporting multiple evidence requirements over the product lifecycle, far outweigh the time and effort involved in identifying, accessing and platforming the most valid data sources. With the right strategy and mix of capabilities the main hurdles to RWD access can be overcome. 1. Define the approach

Evidence requirements call for clinically rich, high-quality, longitudinal data along the complete patient pathway, often across different settings of care. Given the characteristics of RWD today, it is rarely available in a single data source covering a large population of patients. There is thus a trade-off to be made between the number of patients covered (breadth) and the clinical richness provided (depth). However, the careful selection and combination of data sources with varying breadth and depth can allow the synergies between them to be exploited to meet the diverse range of scientific, medical and commercial needs. Advances in data technology, including data linkage across different data sources, support the capability to integrate, manage and analyze these complex RWD sets. 2. Identify the sources

The high level of fragmentation in the RWD market can make it challenging to understand what data is available in the respective countries of interest, leaving companies struggling to identify the appropriate sources. At the same time, there are data source owners who appreciate the value of their data but are uncertain how to make their assets known to potential data users. While there are good initiatives to provide search engines for healthcare data, such as Bridge-to-Data, ENCePP and the ISPOR Outcomes Research Digest, these typically do not cover the smaller but clinically rich data sources and as a result are missing a substantial part of the RWD landscape. For example, in a recent oncology-specific landscaping exercise across Europe, IMS Health identified over 700 dedicated oncology RWD sources, with around 57% managed by academic institutes or individual hospitals. Therefore, a broad and thorough sweep of the disease-specific data landscape is required in order to identify the potentially deep clinical data sources. 3. Profile the data

Once the potential data sources have been identified, the next step is to assess the breadth, depth, quality and consistency of the data being captured within them. As part of this process, the requirement for data manipulation, integration and harmonization will be identified in addition to uncovering critical data gaps that can be filled by data supplementation activities – to be agreed by both the data owner and user. The goal of this profiling exercise is to assess how the particular data source can help to fulfill specific evidence needs but also to compare and prioritize in a standardized way the value of different sources against

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each other. This due diligence process can take considerable time as it involves building a trusting relationship between the data user and the data source owner and in many cases must be achieved without actually accessing the RWD itself. 4. Agree the terms of access collaboration

With the data sources prioritized, the terms of the longterm collaboration must be agreed. Critical aspects to work through here are (1) the model for accessing, storing and manipulating the data to gain scientific insights and (2) the specific use rights received on the data. The different rules and restrictions that individual data source owners may impose can challenge the creation of a RWD portfolio supporting RWE generation across the different data sources in a seamless way. Having the right mix of governance standards, best practices on privacy management and technology-enabled data access options will help during these discussions to reach a workable solution. In practice, any RWD portfolio will need to accommodate several different access models:

• •

•

Anonymous patient-level data is sent by the data source owner and onboarded to RWD infrastructure to allow for direct manipulation and analysis of the raw data by users.

Anonymous patient-level data remains on site with the data source owner, but the user is able to access the data and transform it on site to generate the required aggregated outputs in support of the evidence generation. This can come in different variations, with technology a key enabler to support remote access and analysis of the RWD.

The data source owner provides pre-agreed aggregated outputs to the data user. In this most restricted model, the user is not able to manipulate or view the underlying data unless it is specifically required for quality control and/or audit purposes. In this case, the data source owner requires the capabilities and capacity to deliver against the requirements from the data user.

5. Lock down collaboration incentives and benefits

Finally, given the non-transparency of the RWD market, it is not easy to understand the fair market value and thus the resulting cost for accessing the RWD. As part of the contracting negotiations there are different elements to consider in locking down the long-term collaboration incentives and mutual benefits for both parties.

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

IMS HEALTH RWE SOLUTIONS LOCATIONS

Global scope, local expertise ImS Health Real-World Evidence Solutions experts are located in over 20 countries worldwide and they have published on projects completed in more than 50 countries on all continents. Your primary contacts

Jon Resnick, Vice President and General Manager One IMS Drive, Plymouth Meeting, PA 19462, USA – Tel: +1 610 834 0800 – Jresnick@imshealth.com

Dr. Jacco Keja, Senior Principal 210 Pentonville Road, London N1 9JY, UK – Tel: +31 (0) 631 693 939 – Jkeja@nl.imshealth.com

Dr. Patrik Sobocki, Senior Principal Sveavägen 155, SE-113 46 Stockholm, Sweden – Tel: +46 (0) 8 508 999 95 – Psobocki@se.imshealth.com Alison Bourke, Managing Director 1 Canal Side Studios, 8-14 St Pancras Way, London NW1 0QG, UK - Abourke@uk.imshealth.com

ImS Health Real-World Evidence Solutions key office locations ASIA PACIFIC REGIONAL HEADQUARTERS

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Sveavägen 155/Plan9 11346 Stockholm Sweden Tel: +46 8 508 842 00

SWEDEN

18/F 216 Tun Hwa South Road Sec 2 Taipei 10669 Taiwan ROC Tel: +886 2 2376 1836

TAIWAN

210 Pentonville Road London N1 9JY United Kingdom Tel: +44 (0) 20 3075 4800

UNITED KINGDOM

8280 Willow Oaks Corporate Drive, Suite 775 Fairfax, Virginia 22031 USA Tel: +1 (703) 992 1025

UNITED STATES

One IMS Drive Plymouth Meeting PA 19462 USA Tel: +1 610 834 0800

10 Exchange Place, Floor 22 Jersey City NJ 07302

Theaterstr. 4 4051 Basle Switzerland Tel: +41 61 204 5071 Tel: +44 (0) 20 3075 4800

SWITZERLAND

For further information, email RWEinfo@imshealth.com or visit www.imshealth.com/rwe

ACCESSPOINT • VOLUME 5 • ISSUE 10

PAGE 69

IMS HEALTH RWE SOLUTIONS OVERVIEW

Enabling your real-world success ImS Health takes a straightforward, credible, global approach to using RWD for decision making and engagement to support HQ and marketlevel need.

We combine the best data for client research requirements, expertise and innovation in technology and analytics, and powerful applications tailored by need, to create and deploy evidence that enables decision and alignment. With foundational depth and geographic breadth we deliver insights that enhance understanding of product efficacy, safety, cost and value to inform a new world where patient outcomes are the currency that brings healthcare stakeholders together.

Create dat as et s

Real-World Data Identify and access the most appropriate data sources whilst ensuring patient privacy The broadest and deepest collection of scientiﬁcallyvalidated, anonymous patient-level data assets Complement ﬁt-for-purpose data by custom data sourcing to close data gaps and access deep anonymous patient-level information

• •

TechnologyEnabled Analytics

Real-World Data (RWD)

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Services and Engagement

App

Analyze the d ata

the right real -wo cess c A rld

leadership and innovation across the RWE and HEOR spectrum

ly t h e in sig hts

Technology-Enabled Analytics Bring data across sources as needed and appropriate for analysis leveraging innovative technologies Analytic tools that use powerful technologies to deliver scientiﬁc and commercial insights eﬃciently

•

Services and Engagement Develop an RWE strategy and analyze RWD using scientific rigor, clear governance and advanced analytic and processing capabilities Strategic support Outcomes Research, Pharmacoepidemiology & Drug Safety Health Economics & Market Access Market-level engagement

• • • •

Applying the appropriate scientific and commercial lens and the latest techniques to the right RWD is critical to realizing the value of RWE in healthcare decisions.

#1 RWE Partner of Choice ImS Health is excited to announce that Cegedim Strategic Data has joined our Real-World Evidence Solutions team, boosting our RWD assets and analytical expertise and conﬁrming our role as the partner of choice for RWE.

• 500+ million anonymous longitudinal patient data records in 25+ markets

• Partnerships and data sourcing capabilities to ensure clients have the ‘right fact base’

• 3,000+ publications building healthcare knowledge

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• Leading edge technology and analytics to

enhance understanding of patient outcomes, healthcare costs, drug safety and product value

• Experts in 20+ markets with deep specialism in RWE, HTA and payer requirements to translate insights into actions

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

IMS HEALTH RWE SOLUTIONS EXPERTISE

Expertise in depth The IMS Health RWE Solutions & HEOR team brings unrivalled experience and specialist knowledge from industry, consulting, government and academia globally, and includes leading scientists in epidemiology, drug safety and risk management. With proven expertise in all key therapy areas, we have a track record of helping clients meet the growing demands of an increasingly complex pharmaceutical landscape.

Our senior team Sophie Jouaville Abrouk, PHD, MSC

• • •

Dr. Sophie Jouaville Abrouk is a Senior Medical Writer responsible for scientific affairs, with expertise in RWE, retrospective and prospective observational research, clinical and patient-reported outcomes studies, and innovative solutions.

Sophie joined IMS Health from Cegedim Strategic Data. She has more than 15 years of experience in medical research and medical writing and significant therapeutic knowledge spanning academia and the life-science industry. She has conducted research in Italy and the USA, where she served as a junior faculty at Harvard Medical School, and is the leading research author of several original articles in top scientific journals. Sophie holds a PhD in Biochemistry and Molecular Biology and a Master’s degree in Health Biology from the University of Bordeaux II.

Jean-Marc Aubert, M.ENG, MSC

• • •

Jean-Marc Aubert is a Senior Principal, supporting healthcare providers, health authorities and payers.

Jean-Marc has extensive pharmaceutical experience ranging from real-world effectiveness and the regulatory process to sales force, marketing effectiveness and brand performance. His background includes roles as a partner heading business development in the healthcare sector at Jalma, as deputy director at CNAMTS (French National Health Insurance Fund for Salaried Workers) and as Chief of Staff of the State Secretary for Health Insurance.

An expert in the French healthcare system, market access, commercial effectiveness, RWE and HEOR, Jean-Marc holds a Master’s degree in Engineering and a Master of Science degree, both from École Polytechnique, France; a Specialist Postgraduate Diploma in Statistics and Economics from École Nationale de la Statistique et de l’Administration Économique (ENSAE); and a Specialist Postgraduate Diploma in Economics (DEA) from École des Hautes Études en Sciences Sociales (EHESS), France.

Karin Berger, MBA

• • •

Karin Berger is a Principal, with a focus on RWE, PROs and cost-effectiveness evaluation analyses at a national and international level.

Formerly Managing Director of MERG (Medical Economics Research Group), an independent German organization providing health economics services to the pharmaceutical industry, university hospitals and European Commission, Karin has more than 15 years experience in the health economics arena. She lectures at several universities, has published extensively in peer-reviewed journals, and regularly presents at economic and medical conferences around the world. Karin graduated as Diplom-Kaufmann (German MBA equivalent) from the Bayreuth University, Germany, with a special focus on health economics.

Ian Bonzani, PHD, BSC

• • •

Dr. Ian Bonzani is a Principal, leveraging his scientific background and consulting experience to help clients create and implement franchise strategies in the pricing and market access and RWE space. He manages largescale RWE engagements across stakeholders, functions and geographies.

With a background that includes roles in the IMS Consulting Group in Europe, Ian has expertise in RWE strategy, franchise evidence generation strategy, real-world data sourcing, and data marts/technology platforms. He has been involved in a wide range of global projects, including RWE planning, large-scale data mart creation and implementation, collaborative engagement models, and disruptive evidence generation.

Ian holds a PhD in Regenerative Medicine from Imperial College London (Marshall Scholar) and a Bachelor of Science degree in Biomedical Engineering from Worcester Polytechnic Institute, Worcester, Massachusetts.

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IMS HEALTH RWE SOLUTIONS EXPERTISE Richard Borrelli, MBA

• • •

Richard Borrelli is a Principal, leading a team in Canada supporting evidence-based solutions for healthcare stakeholders. He is recognized for his expertise in leveraging longitudinal patient-level data to better understand and quantify real-world treatment pathways, and heads development of innovative research protocols involving EMR supplemented with patient and physician feedback.

Richard has extensive experience leveraging Canadian pharmacy and claims data to evaluate patient utilization of medicines. These insights have informed decision making for market access, health economic, sales and marketing divisions of pharmaceutical companies, as well as payer organizations in the country. Richard also utilizes Canadian EMR to describe indirect and direct burden of illness while evaluating patient real-world outcomes. Richard holds an MBA (with distinction) from DeGroote School of Business, McMaster University, and a Bachelor of Commerce degree from the University of Toronto.

Nevzeta Bosnic, BA

• • •

Nevzeta Bosnic is a Principal, focused on managing projects to meet the broad spectrum of client needs in the Canadian pharmaceutical market.

Formerly Director of Economic Consulting at Brogan Inc, Nev has led many strategic consulting, policy and data analyses for pharmaceutical clients, government bodies and academic institutions in Canada. She has extensive knowledge of public and private drug plans across the country and in-depth expertise and experience on the drug reimbursement process. Nev holds a Bachelor’s degree in Business Economics from the School of Economics and Business at the University of Sarajevo, Bosnia-Herzegovina.

Alison Bourke, MSC, MRPharm.S, FISPE

• •

•

Alison Bourke is a Managing Director, with over 25 years experience working with primary care patient data resources in the UK. She has a particular interest in the use of this data to explore innovative scientific methodologies.

Prior to joining IMS Health, Alison headed the research team at CSD Medical Research UK, providing primary care data and support for a range of studies, including pharmacoepidemiology and health outcomes research. She pioneered innovative linking ‘pseudonymization at source’ technology and was instrumental in setting up the Health Improvement Network (THIN), bringing access to 12 million pseudonymized patient records. A trained pharmacist, Alison previously held roles at BMS where she analyzed one of the first computer-collected safety studies, and Cegedim INPS where she supported the successful launch of GPRD. Alison holds a Master’s degree in Computing from De Montfort University, Leicester, and a Bachelor’s degree in Pharmacy from Manchester University. She is a Member of the Royal Pharmaceutical Society and a Fellow of the International Society for Pharmacoepidemiology.

Chakkarin Burudpakdee, PHARM.D

• • •

Dr. Chakkarin Burudpakdee is a Principal, with extensive experience in HEOR and strategic consulting, including product value development and communication, market entry strategies and lifecycle management plans. He has led teams in observational research, economic modeling, patient and provider surveys, systematic reviews and meta-analyses. Prior to joining IMS Health, Chakkarin was VP, Evidence Development at MKTXS, where he built and oversaw scientific direction of the HEOR department and developed relationships with academic institutions around the world that provided access to patient-level data for observational research. He began his career as a clinical analyst at ValueMedics Research LLC.

Chakkarin holds a Pharm.D from Philadelphia College of Pharmacy and Science, now University of the Sciences in Philadelphia, and is a Research Assistant Professor in the College of Health and Human Services, University of North Carolina at Charlotte.

Joe Caputo, BSC

• • •

Joe Caputo is Regional Principal, leveraging more than 20 years experience in the pharmaceutical sector to help clients address the challenges of global reimbursement and market access throughout the drug development program. He has led numerous projects involving payer research, value dossiers, local market access models and HTA submissions in the Asia Pacific region. Joe’s background includes industry roles in drug development, sales and marketing, and UK and global health outcomes, as well as consulting in health economics. He has wide-ranging knowledge of the drug development process at both local and international level and a unique understanding of evidence gaps in light of reimbursement and market access requirements.

Joe holds a Bachelor’s degree in Applied Statistics and Operational Research from Sheffield Hallam University, UK.

Adam Collier, MSC

• •

•

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Adam Collier is a Senior Principal, with responsibility for consulting and data related to IMS Health patient-level data assets in the UK. He has 18 years commercial experience in the UK and European healthcare industry.

Adam’s background spans pharmaceuticals, consulting and healthcare provision, allowing an unusually broad view of the challenges inherent across the healthcare arena. He spent nine years at GlaxoSmithKline in roles within customer and trading strategy, commercial analysis and European marketing, and two years at Accenture, where he also completed a secondment to the Medicines & Healthcare Products Regulatory Agency (MHRA) to work on their patient data asset GPRD (now CPRD). Prior to joining IMS Health, he spent several years with a private healthcare provider. Adam holds a Master’s degree in Chemistry from the University of Oxford.

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Neil Corner

• • •

Neil Corner is a Leader, RWE Solutions, supporting government, academics and the pharmaceutical industry in understanding and delivering health outcomes data, with a focus on mHealth, integrated patient data and EMRs, including the creation of interactive electronic patient registries.

Neil has 27 years experience in the pharmaceutical industry in the UK, US, EMEA and Canada, 16 of which were spent at Janssen Pharmaceuticals, including the post of Global Commercial Leader. Prior to joining IMS Health, where his roles have included international franchise lead for patient and medical data, Neil led Helix Healthcare, a division of Quintiles. Neil is the author of several publications on EMR data validation, RWE in the Canadian market and Customer Relationship Management. His research and development activities currently focus on the innovative design and construction of integrated health data ecosystems to create outcomes in the world of big data.

Bruce Crawford, MA, MPH, BSC

• • •

Bruce Crawford is a Senior Principal, with over 20 years consulting experience and expertise in prospective study design, patient-reported outcome evaluations, cost-effectiveness analyses and reimbursement.

Over the past 13 years, Bruce has worked on projects throughout Asia. He was previously Managing Director Asia and Senior VP at Adelphi, prior to which he was Operations Director at Mapi Values and Japan. He has worked in managed care and for a major CRO as a health economist, and been involved in research and training with the US FDA, the Japanese PMDA, and the Thailand FDA and National List of Essential Drugs committee.

Bruce has written and lectured on pharmacoeconomic and outcomes research methodologies and impacts on study validity, and recently held appointments as Adjunct Project Professor of HTA and Public Policy at Tokyo University Graduate School of Public Policy and as Adjunct Instructor at Kyoto University, School of Medicine and Public Health, Dept. of Pharmacoepidemiology. He holds a Master of Arts degree in Economics and a Bachelor of Science degree in Mathematics and Economics from the University of New Hampshire, and an MPH, specializing in Epidemiology and Biostatistics, from Tufts University School of Medicine.

Mitch DeKoven, MHSA

• • •

Mitch DeKoven is a Principal, leading teams in a variety of projects, including value development plans, retrospective database studies and observational surveys.

Prior to joining IMS Health, Mitch was an Associate Director of Reimbursement and Market Access at ValueMedics Research LLC. His previous roles include Manager of Reimbursement Services at United BioSource Corporation’s Center for Pricing & Reimbursement, Consultant with CHPS Consulting, and Program Manager of the Center for Cancer and Blood Disorders Children’s National Medical Center in Washington, DC, a position he held after completing an administrative fellowship with the Johns Hopkins Health System.

A past president of the board of directors of the Lupus Foundation of America Greater Washington Chapter, Mitch serves on six editorial advisory boards and is a peer reviewer for a number of international healthcare journals. He has also authored several articles. Mitch holds an MHSA from the University of Michigan School of Public Health and a Bachelor’s degree in Spanish from Washington University in St. Louis.

Filip Dosselaere, PHD, MSC

• • •

Dr. Filip Dosselaere is a Director, Supplier Services, focused on international data sourcing for RWE. He has extensive expertise in global sales and account management, business development and strategic data sourcing.

Filip’s background spans 15 years of international sales, account management and business development experience, primarily in the biotech and pharmaceutical sectors. During this time he has worked in data source screening and assessment, access and governance models, and source contracting and management, engaging with a multitude of data sources. These range from EMR providers, registries and claims/sick funds to academic centers and health authorities. Filip has also conducted scientific research in genetic engineering. Filip holds a PhD in Applied Biological Sciences, a Master’s degree in Bio-engineering, and a post-graduate degree in Business Administration, all from KULeuven in Belgium.

Richard Fordham, PHD, MA, FFPH

• • •

Professor Richard (Ric) Fordham is a Senior Principal, with a specialism in applied economic evaluation models and analysis in the context of medical innovation and decision making. He has extensive research experience in the economics of orthopedics, ophthalmology, respiratory disease and cancer.

In a career spanning 30 years, Ric has established an international reputation in academia and consultancy. He was previously founder-Director at Lewin-Fordham, Quintiles, Australia and has also run his own health economics consultancy and medical software businesses. He has been an advisor to bodies such as WHO Europe, NICE and the UK’s National Obesity Observatory, led the emerging sub-specialty of public health economics, and been sought as an external referee for international health technology committees in Australia, Canada and Singapore.

Ric holds a PhD in Health Economics from the University of Western Australia, a Master’s degree in Health Services Studies from the University of Leeds, and a Bachelor’s degree in Economics from the University of York. He has received a number of honors and in 2008 was elected a lifetime member of Sidney Sussex College, Cambridge for services to health economics teaching.

continued on next page ACCESSPOINT • VOLUME 5 • ISSUE 10

PAGE 73

IMS HEALTH RWE SOLUTIONS EXPERTISE Frank-Ulrich Fricke, PHD, MSC

• • •

Dr. Frank-Ulrich Fricke is a Principal at IMS Health and Professor for Health Economics, Georg-Simon-Ohm University of Applied Sciences, Nuremberg in Germany, with a focus on health economic evaluations, market access strategies and health policy.

Formerly a Managing Director of Fricke & Pirk GmbH, and previously Head of Health Economics at Novartis Pharmaceuticals, Frank-Ulrich has conducted health economic evaluations across a wide range of therapeutic areas, developing a wealth of experience in pricing, health affairs and health policy. As a co-founder of the NIG 21 association, he has forged strong relationships with health economists, physicians and related researchers working in the German healthcare system. Frank-Ulrich holds a PhD in Economics from the Bayreuth University, and an MBA equivalent from the Christian-Albrechts-University, Kiel.

Franca Heiman, PHD

• • •

Dr. Franca Heiman is Medical Research and HTA Manager, leading the RWE and health technology team in Italy. She has expertise in health economics, outcomes research, market access, HTA and medical research projects.

Franca’s background includes 20 years of experience in medical marketing and health economics gained in roles at Ciba Geigy, Pharmacia, Searle and Bracco Imaging. She was previously with CSD Medical Research where she initially provided scientific support before subsequently opening the company’s Italian office. Franca holds a PhD in Statistics and Economics from the University of Bologna and a diploma in Health Economics from Stockholm School of Economics.

Joshua Hiller, MBA

• • •

Joshua Hiller is a Senior Principal, supporting the strategic planning and development of IMS Health capabilities for data sourcing, integration, analytics and studies. He is also currently serving as Alliance Director in the company’s collaboration with AstraZeneca for the advancement of RWE.

During a career that includes roles in market analytics, government and healthcare consulting in both the US and UK, Joshua has led a wide range of projects for clients in the pharmaceutical and biotech sector as well as industry associations. He has extensive experience in pharmaceutical pricing, contracting, market landscape development, supply management, cross border trade, lifecycle management, competitive defense, generics market drivers and account management, with expertise across US and European markets. Joshua holds an MBA (Beta Gamma Sigma) from Columbia Business School, New York, and a Bachelor of Science degree in Mathematics from James Madison University, Virginia.

Benjamin Hughes, PHD, MBA, MRES, MSC

• • •

Dr. Ben Hughes is a Vice President, leading development of the company’s RWE strategy and offering. He has helped many clients in the pharmaceutical industry to articulate and implement their RWE strategies through definition of RWE vision, business cases for RWE investments, capability roadmaps, partnerships, brand evidence reviews, HEOR function design, RWE training programs and related clinical IT strategies.

Previously head of the European RWE service line at McKinsey & Co, Ben has extensive experience advising healthcare stakeholders on health informatics and RWE-related topics. This includes work on France’s electronic health record strategy, EMR adoption strategy for governments across Europe and Asia, data releases to support the UK’s transparency agenda, and the development of payer health analytics and RWE capabilities across countries in Europe.

A widely published author on health informatics, Ben holds a PhD in Medical Informatics from ESADE Barcelona, an MBA from HEC Paris, and Masters’ degrees in Research from ESADE Barcelona and in Physics from University College, London.

Jacco Keja, PHD

• • •

Dr. Jacco Keja is a Senior Principal, drawing on deep expertise in global market access, operational and strategic pricing, and health economics and outcomes research.

Jacco’s background includes four years as global head of pricing, reimbursement, health outcomes and market access consulting services at a large clinical research organization and more than 13 years experience in the pharmaceutical industry, including senior-level international and global roles in strategic marketing, pricing and reimbursement and health economics. Jacco holds a PhD in Biology (Neurophysiology) from Vrije Universiteit in Amsterdam, a Master’s degree in Medical Biology, and an undergraduate degree in Biology, both from Utrecht. He is also visiting Professor at the Institute of Health Policy & Management at Erasmus University, Rotterdam.

Marla Kessler, MBA

• • •

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Marla Kessler is a Vice President, heads overall marketing efforts for IMS Health RWE Solutions and is an active leader of global RWE projects. She helps clients develop commercial strategies for products and portfolios, define evidence plans to support them, and coordinate implementation to ensure successful execution.

Marla has 15 years strategic and business line experience gained through previous leadership roles at McKinsey & Company and Pfizer. During her career at IMS Health she has designed and led RWE boot camps to help clients build capabilities in this area across the broader organization, and also developed thought leadership in RWE. This includes co-authoring a major IMS Health benchmarking study exploring variations in RWE supply and demand across the pharmaceutical industry’s top markets. Marla holds an MBA from Duke University’s Fuqua School of Business in Durham, North Carolina.

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Joseph Kim, PHD, MPH

• • •

Dr. Joe Kim is a Senior Principal, providing scientific direction in the design and analysis of observational studies across a wide range of projects.

A trained epidemiologist and statistician, Joe has over 20 years experience in population-based research in the US and Europe. He was previously Senior Director in Benefit-Risk Management at Quintiles assisting in the development of pharmacovigilance systems, risk management plans and benefit-risk evaluation reports, and in the design of post-authorization safety studies. Prior to this, worked in epidemiology at Roche and Amgen. For the last 10 years, Joe has taught pharmacoepidemiology and pharmacovigilance at the London School of Hygiene & Tropical Medicine, and more recently on the MPH program at the French School of Public Health in Paris. He holds a PhD in Epidemiology from the University of Minnesota, and an MPH from the Graduate School of Public Health, San Diego.

Rob Kotchie, M.CHEM, MSC

• • •

Rob Kotchie is a Vice President, with a focus on bringing innovative solutions to clients through strategic alliances, collaborations and the deployment of novel technology.

Previously with ZS Associates, Rob has more than 10 years consulting experience, specializing in the synthesis and application of RWE to facilitate market access, drug uptake and the responsible use of medicines. In his former role as Chief of Staff at IMS Health, he supported all operational and management activities related to execution of the company’s strategy, and played an integral role in its 2013 dividend recapitalizations and initial public offering in 2014.

Rob has particular expertise in the areas of oncology, respiratory, cardiovascular and CNS and has published more than 30 peer-reviewed journal articles and poster presentations. He holds a first class honors degree in Chemistry from the University of Oxford and an MSC in International Health Policy from the London School of Economics.

Stacey Kowal, MSC, MSC, BS

• • •

Stacey Kowal is a Principal, with a focus on economic modeling, value development planning and health policy research in domestic and international settings.

Stacey has more than a decade of experience in public health, health policy and health economics research. This includes a senior role at IHS Global Inc., where she guided research studies on US health policy, econometric analyses for US IPPS payment rates and the development of global launch strategies for new pharmaceuticals in more than three dozen international markets.

Stacey holds a Master’s degree in Public Health from the London School of Hygiene and Tropical Medicine, a Master’s degree in International Health Policy and Health Economics from the London School of Economics, and a Bachelor’s degree in Mathematics from Alma College.

Mark Lamotte, MD

• • •

Dr. Mark Lamotte is a Senior Principal, responsible for project management and quality assurance within his team, and for leadership of health economic modeling.

A medical doctor specialized in cardiology, Mark spent six years in clinical practice before joining Rhône-Poulenc Rorer as Cardiovascular Medical Advisor and later becoming Project Manager and Scientific Director at the Belgian research organization, HEDM. He has worked on over 300 cardiovascular, pulmonary, diabetes, urology and oncology projects, incorporating expert interviews, patient record review, modeling and report writing. Many of these projects have resulted in peer-reviewed publications. Mark holds an MD from the Free University of Brussels (Vrije Univeristeit Brussel, Belgium) and is fluent in Dutch, French, English and Spanish.

Bruno Lempernesse, BA

• • •

Bruno Lempernesse is a General Manager, providing leadership to develop longitudinal patient data capabilities in the North America region. He also has global responsibilities for the business development and organization of patient data activity. Bruno has over 20 years of healthcare industry experience, initially in Europe and more recently in the USA for Cegedim Strategic Data. He is an expert in the development of data collection and utilization of Electronic Medical Records (EMRs) and the design of studies using EMRs to support the medical and marketing research needs of local and multinational life science companies.

Bruno holds a Bachelor’s degree in Marketing and Market Research, Entrepreneurship and International Business from the Académie Commerciale Internationale, Novancia Business School Paris and an Associate degree in International Trade from the Paris Chamber of Commerce.

Claude Le Pen, PHD

• • •

Dr. Claude Le Pen is a member of the strategic committee of IMS Health and Professor of Health Economics at Paris-Dauphine University, providing expert economic advisory services to the consulting practice.

A renowned economist, leading academic and respected public commentator, Claude has served as an appointed senior member of several state commissions in the French Ministry of Health and is an expert for a number of parliamentary bodies, bringing a unique perspective and unparalleled insights into the economic evaluation of pharmaceutical technologies at the highest level.

Claude studied Business Administration in HEC Business School in Paris and holds a PhD in Economics from Panthéon-Sorbonne University.

continued on next page ACCESSPOINT • VOLUME 5 • ISSUE 10

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IMS HEALTH RWE SOLUTIONS EXPERTISE Etienne Lepoutre, MBA

• • •

Etienne Lepoutre is a Principal, with expertise in RWE and market access strategies and operations effectiveness improvement. He has managed projects for leading pharmaceutical brands focused on patient and health system value and has extensive experience of cross-functional collaboration between global, regional and local organizations within pharma. Etienne has eight years of experience in the pharmaceutical and healthcare arena, including roles at PwC, Capgemini Consulting and L’Oreal, and more than 10 years in sectors such as telco and retail, managing strategic transformation projects in sales, marketing, customer excellence and the supply chain.

Etienne holds a Master’s degree (MBA equivalent) from the IAE La Sorbonne and a degree in Engineering from ESAM.

Ragnar Linder, MSC

• • •

Ragnar Linder is a Principal, with more than 25 years experience in pharmaceutical marketing, sales and business development.

Co-founder of the Nordic-based consultancy and research organization, Pygargus AB, Ragnar has worked in various senior level industry roles. These include General Manager of Amgen Nordic AB, Director of International Marketing at Aventis/Hoechst Marion Roussel, and Head of Sales & Marketing at Hoechst Pharmaceuticals AB. He has also served on the Board of Directors for several CRO and biotech companies.

Ragnar holds a Master of Science degree in Chemical Engineering from the Royal Institute of Technology in Sweden.

Carol Lines, BA

• • •

Carol Lines is a Principal, focused on the development of RWE data platforms. With a background in the healthcare industry and consulting, and a strong grounding in both data and analytics, she brings a deep understanding of pharmaceutical business processes.

Prior to her current role at IMS Health, Carol spent seven years leading diverse client engagements for the Research Triangle Institute and the Medco Research Institute. These engagements included patient registries, large observational studies, outcomes research, data sourcing and integrated healthcare projects, including building research networks across multiple geographies. She was previously Global Head of Marketing Operations at Boehringer Ingelheim, where she also led the development and implementation of several multimillion dollar projects. Carol is a qualified psychotherapist and holds a Bachelor’s degree in Philosophy and Economics from UEA, UK.

Adam Lloyd, M.PHIL, BA

• • •

Adam Lloyd is a Senior Principal, with a focus on economic modeling and the global application of economic tools to support the needs of local markets.

A co-founder and former Director of Fourth Hurdle, and previously Senior Manager of Global Health Outcomes at GlaxoWellcome, Adam has extensive experience leading economic evaluations of pre-launched and marketed products, developing submissions to NICE and the SMC, decision-analytic and Markov modeling, and in the use of health economics in reimbursement and marketing in continental Europe. Adam holds a Master’s degree in Economics and a Bachelor’s degree (Hons) in Philosophy, Politics and Economics from the University of Oxford.

Frédérique Maurel, MS, MPH

• • •

Frédérique Maurel is a Principal, with a focus on observational research and health economics studies.

A skilled consultant and project manager, Frédérique has extensive experience in the economic evaluation of medical technologies gained in roles at ANDEM, Medicoeconomie, and AREMIS Consultants.

Frédérique holds a Master’s degree in Economics – equivalent to an MS – and completed a post-graduate degree equivalent to an MPH with a specialization in Health Economics at the University of Paris-Dauphine (Paris IX) as well as a degree in Industrial Strategies at the Pantheon-Sorbonne University (Paris I).

Joan McCormick, MBA

• • •

Joan McCormick is a Principal, leading a team providing strategic advice to companies with new products coming to market and ongoing consultation on the rules for existing drugs post launch.

Formerly Head of Price Regulation Consulting at Brogan Inc, Joan has supported many major pharmaceutical companies with the preparation of pricing submissions to the Patented Medicine Prices Review Board (PMPRB), gaining extensive insights into the operation of the Canadian pharmaceutical market.

Joan holds an MBA from the University of Ottawa, Canada and a Bachelor’s degree in Life Sciences from Queen’s University in Kingston, Canada.

Adeline Meilhoc, MSC

• • •

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Adeline Meilhoc is a Vice President, leading global operations including tactical solutions for epidemiology, safety and efficacy needs, RWE strategy development to meet challenges in the peri-approval period, and innovative technological methods.

Adeline joined IMS Health from Cegedim Strategic Data and has 20 years of experience in academia, pharma and contract research organizations, seven of which were spent at Parexel International where she built and led the Feasibility Evaluation group in the USA and EMEA. She has also created and driven both business development/pharma strategic partnerships and Medical Imaging units in various global organizations.

Adeline holds a post Master’s degree with distinction in Clinical Psychology from the Catholic University of Paris (Health & Society specialty), and a Master’s degree in Pharmaceutical Business Development & Licensing from the Pharma Licensing Group, London.

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Lisa Stockwell Morris, PHD, RPH

• •

•

Dr. Lisa Morris is a Vice President, with global responsibility for LifeLink, the company’s suite of patientcentered insights, and for developing patient-centered information capabilities within the US, EMEA, and Asia Pacific.

Lisa has many years experience in applying market research tools to answer a wide range of business questions, delivering customized solutions using LRx, medical and pharmacy claims data, EMRs and other clinically-rich secondary information sources. Previously Associate Director for Health Outcomes Assessment at Wyeth-Ayerst Research, where she incorporated health outcomes and economic information into drug development plans, Lisa has also held roles as a senior manager in the Outcomes Research group at Diversified Pharmaceutical Services (DPS) and United Healthcare Corporation (UHC), managing all aspects of customized health services research projects.

A registered pharmacist, Lisa holds a doctorate in Pharmacoeconomics with an emphasis on Marketing from the University of South Carolina, where she also received a Bachelor’s degree in Pharmacy.

Julie Munakata, MS

• • •

Julie Munakata is a Senior Principal, with a focus on global economic modeling, value development planning, and survey data analysis.

An accomplished researcher and author of more than 25 original articles, Julie has extensive experience in managing clinical trials, health economic studies and decision analytic modeling work, gained in senior roles at ValueMedics Research LLC, the VA Health Economics Resource Center and Stanford Center for Primary Care & Outcomes Research, and Wyeth Pharmaceuticals.

Julie holds an a Master’s degree in Health Policy and Management from the Harvard School of Public Health and a Bachelor’s degree in Psychobiology from the University of California, Los Angeles.

Stefan Plantör, PHD, MBA, MSC

• • •

Dr. Stefan Plantör is a Principal, with a focus on AMNOG-related projects, including benefit dossiers, as well as reference price management, health economic evaluations and health policy analyses.

Stefan’s background includes roles as a researcher and five years experience in the pharmaceutical industry. He has also served as a board member of ProGenerika, the German pharmaceutical association. Over the course of his career, Stefan has broadened his expertise to include data analyses and decision analytic modeling, authored a number of publications in international journals and presented his research at major congresses. Stefan holds a PhD in Biology from the University of Tübingen, an MBA in International Marketing from the European Business School, Reutlingen and an a Master’s degree in Microbiology from the Eberhardt-KarlsUniversity (Tübingen).

Antonella Porta, MSC

• • •

Antonella Porta is a Principal, with a focus on the RWE Solutions Quality Management Program. She brings 15 years of management experience in quality assurance, compliance and risk management in the pharmaceutical industry and highly regulated fast-moving consumer goods (FMCG) sector.

During the course of her career, Antonella has held leadership roles in operational quality, quality systems, remediation programs, auditing and compliance. She was most recently Quality & Compliance Director at Shire, heading the global Local Operating Companies’ quality team. Antonella began her management career at Procter & Gamble as Regional Head of External Operation Quality, progressing with roles of increasing responsibility to become latterly Global Head of the Microbiological Risk Management Program. Antonella holds a Master’s degree in Industrial Chemistry from Federico II University in Naples and is currently studying for an MBA at Warwick University, UK.

Christian Reich, MD, PHD

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•

Dr. Christian Reich is a Vice President, with more than 15 years of experience in life science research and medicine. He is also Principal Investigator at the Observational Health Data Science and Informatics (OHDSI) collaborative, which focuses on creating comprehensive evidence about disease, healthcare delivery and the effects of medical interventions through large-scale analysis of RWD.

Prior to joining IMS Health, Christian was Global Head of Discovery Informatics and R&D Information, Global Medicines Development North America, at AstraZeneca. He began his career as a practicing physician before moving to the European Bioinformatics Institute to work on the Human Genome Project. He subsequently joined the biotech industry where he worked in various roles on challenges in drug R&D, including gene sequence and expression analysis, clinical trial design and analysis, systems biology and outcomes research, applying computational methods to large scale biological data.

Christian holds an MD and PhD from the Medical University of Lübeck, Germany, and a Bachelor’s degree in preclinical training from Humboldt University in Berlin.

Emile Schokker, MBA, MSC

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Emile Schokker is a Senior Principal, with nearly 20 years of international pharmaceutical and consulting experience including expertise in launch, brand and portfolio strategy, commercial model redesign and postmerger integration.

Prior to joining IMS Health, Emile was a global senior expert at McKinsey’s global benchmarking service line in Belgium, where he previously served as an associate principal responsible for leading strategic engagements at board and senior management level. He has also worked in leadership roles at Unaxis/Oerlikon in Switzerland, Arthur D. Little in the Netherlands, and Unilever in various international locations.

Emile holds an MBA from IMD in Lausanne and a Master of Science degree in Applied Physics from the Delft University of Technology, the Netherlands.

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IMS HEALTH RWE SOLUTIONS EXPERTISE Jon Resnick, MBA

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Jon Resnick is a Vice President and General Manager, leading the company’s global RWE & HEOR business, including the development of RWE strategy, offerings, collaborations and foundational technologies to meet the RWE needs of healthcare stakeholders.

A former Legislative Research Assistant in Washington DC and member of the Professional Health and Social Security staff for the US Senate Committee on Finance, Jon has 10 years consulting experience at IMS. He was most recently responsible for leading the European management consulting team and global HEOR business teams of 300 colleagues, advising clients on a wide range of strategic, pricing and market access issues. Jon holds an MBA from the Kellogg School of Management, Northwestern University, with majors in Management and Strategy, Finance, Health Industry Management, and Biotechnology.

Mats Rosenlund, PHD, MPH

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Dr. Mats Rosenlund is a Principal, with long experience in epidemiology, outcomes research and health economics from academia, the pharmaceutical industry and consultancy.

Prior to joining IMS Health, Mats was Director of Health Economics at OptumInsight and Director of Epidemiology and Health Outcomes at GSK. He was previously a researcher at the Karolinska Institute, a Public Health Official at the Karolinska Hospital, and completed two post-doctoral periods in Italy and Sweden. An affiliated researcher at the Center for Pharmacoepidemiology, Clinical Epidemiology Unit, Karolinska Institutet, he has authored more than 20 peer-reviewed articles.

Mats holds a PhD in Epidemiology, a Master’s degree in Public Health and a Bachelor’s degree in Environmental Health from Karolinska Institutet. He has also completed university training in health economics in Belgium and the UK.

Daniel Simpson, M.BIOCHEM

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Daniel Simpson is a Senior Principal, with responsibility for diabetes portfolios and involvement in the UK COBIC initiative, focused on moving healthcare commissioning towards patient-based outcome measures. He also takes a leadership position on commercial analytics.

Daniel has more than 18 years experience in healthcare and pharmaceutical markets. Over the course of his career he has worked for all the top 10 pharmaceutical companies and healthcare systems in major markets, delivering insights from patient-level data to support improved decision making on resource allocation. He previously worked in the healthcare/pharmaceutical strategy divisions for both Accenture and the Monitor Group. Published in a series of conference posters and papers, Dan holds a Master’s degree in Biochemistry from St Anne’s College, University of Oxford.

Patrik Sobocki, PHD, MSC

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Dr. Patrik Sobocki is a Senior Principal, with more than 14 years experience in RWE, HEOR and market access.

Patrik’s background spans academia, consulting and the life-science industry within RWE and HEOR, including international management responsibilities in various senior roles. He was most recently a partner at the Nordic-based consultancy and research organization, Pygargus AB, where he worked with the company’s unique methodology for generating population-based RWE based on anonymous patient-level data from EMR and health registers.

Patrik has conducted numerous health economics projects, outcomes research and epidemiology studies and published more than 40 articles in international peer-reviewed journals. He holds a PhD in Health Economics from the Karolinska Institutet, a Master’s degree in Economics and Business Administration from the Stockholm School of Economics, and an Associate Professorship at the Karolinska Institutet.

Núria Lara Surinach, MD, MSC

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Dr. Núria Lara is a Senior Principal, with a focus on the design and coordination of local and international observational and patient-reported outcomes studies.

A former practicing GP and clinical researcher, Núria’s experience spans roles in outcomes research at the Institute of Public Health in Barcelona and in Catalan Health Authorities, and consulting positions within the pharmaceutical and medical device industries focusing on medical regulatory and pricing affairs, pharmacoeconomics and market access strategies. Núria holds an MD (specializing in Family and Community Medicine in Barcelona), and a Master’s degree in Public Health from the London School of Hygiene and Tropical Medicine and London School of Economics.

Massoud Toussi, MD, PHD, MSC, MBA

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Dr. Massoud Toussi is a Principal, applying his expertise to assure the quality of outcomes research and pharmacovigilance. He is also the representative of IMS Health in ENCePP.

Previously head of Global Clinical Research Operations at Cegedim, Massoud has also worked with the French High Authority for Health (HAS) and various CROs as Project Lead, Scientific Manager and Operations Director. His experience includes drug safety reporting, natural language processing, database linkage and drug utilization studies.

Massoud holds an MD from Mashad University in Iran, a Master’s degree in Medical Informatics and Communication Technology from Paris VI, a PhD in Medical Informatics from Paris XIII University, and an executive MBA from a joint program of Universities of Paris-Dauphine and Quebec à Montreal.

IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS

Arnaud Troubat, PHARM.D, MBA, MHEM

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Dr. Arnaud Troubat is a Principal, with extensive consulting experience and special expertise in the development of registration dossiers and market access strategies across a large number of therapeutic areas.

A pharmacist by training, Arnaud began his career at the French pharmaceutical industry association (LEEM). He then spent a number of years in the pharmaceutical affairs department at ICI, leading regulatory work on registration submissions and reimbursement strategies, before subsequently moving into consulting. Most recently he was Director at Carré-Castan Consultants, managing a research team.

Arnaud holds a Doctor of Pharmacy degree and an MBA from IAE Paris and a Master’s degree in Health Economics and Management from Paris-Dauphine University.

Rolin Wade, RPH, MS

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Ron Wade is a Principal and a recognized expert in the applications and limitations of using large retrospective datasets and late-phase datasets for health economics and outcomes research.

Prior to joining IMS Health, Ron served as a Healthcare Executive and Principal Investigator with Cerner Research and as a Research Director at HealthCore. He also has experience generating evidence to support value messages to managed care, government payers and public health associations, gained in leadership roles within the pharmaceutical industry. A widely published author with expertise in many therapy areas, Ron lectures at colleges of pharmacy and he has had leadership roles with the American College of Clinical Pharmacy and the Academy of Managed Care Pharmacy. He is a licensed pharmacist and holds a Master’s degree in Pharmaceutical Sciences from the University of the Pacific, California and a Bachelor of Science degree in Pharmacy.

Jovan Willford, MBA

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Jovan Willford is a Senior Principal, supporting growth strategy, offering development and commercialization of RWE solutions in the Asia-Pacific region.

Jovan’s background includes more than 10 years strategic advisory experience across payers, providers, life science organizations and technology companies, including several cross-industry collaborations to advance quality and value of care delivery.

Jovan holds an MBA from the Kellogg School of Management, Northwestern University, with majors in Management and Strategy, Managerial Economics and International Business, and an undergraduate degree from the University of Notre Dame with majors in Marketing and Philosophy.

Diana Wong, MBA, MSC, BSC

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Diana Wong is a Principal, with expertise in competitive assessments, payer pricing and access, new commercial models and value-based access decision frameworks. She leads strategy & innovation initiatives, mergers & acquisitions (M&A) and partnerships for RWE in Europe and Asia, as well as data analytics and infrastructure growth initiatives for RWE.

Prior to joining IMS Health, Diana was a management consultant in the USA and Europe, working closely with providers to set up health enablement IT platforms for leveraging data analytics to reduce costs and improve outcomes in the overall health system. She has also worked with payers, life sciences and health enablement IT companies on market entry strategies, M&A, scenario planning, spin-off companies, portfolio analysis and clinical change management. Her experience spans both North American and European healthcare systems. Diana holds an MBA in Health Sector Studies from the Richard Ivey School of Business at the University of Western Ontario, a Master’s degree in Biochemistry from the University of Toronto and a Bachelor’s degree in Biochemistry from Queen’s University.

Ashley Woolmore, D.CLIN PSYCH, MBA

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Dr. Ashley Woolmore is a Senior Principal, with a focus on developing innovative approaches to help clients reinforce differentiation through the integration of real-world data into strategic decision making. He has 20 years experience in the life sciences and healthcare sector.

Ashley leverages a uniquely diverse background in clinical, healthcare system management and life sciences strategy consulting in senior advisory roles to support clients across developed and emerging markets on a wide set of healthcare system issues. His expertise includes strategy development, healthcare analytics, RWE for strategic insight, population health management applications, and differentiated market access approaches. A thought leader with a particular interest in opportunities arising from convergence between the life sciences industry and broader healthcare system, Ashley holds a doctorate in Clinical Psychology from the University of Oxford, an MBA in Strategy from HEC in Paris, and a Bachelor of Science (Hons) degree in Natural Sciences and Psychology.

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IMS Health Real-World Evidence Solutions

is based in 20 countries worldwide with regional headquarters in

The Americas

8280 Willow Oaks Corporate Drive Suite 775 Fairfax Virginia 22031 USA Tel: +1 (703) 992 1025

Europe

210 Pentonville Road London N1 9JY United Kingdom Tel: +44 (0) 20 3075 4800

Latin America

Insurgentes Sur # 2375 5th Floor Col. Tizapan México D.F.- C.P. 01090 México Tel: +52 55 5089 5205

RWEinfo@imshealth.com www.imshealth.com/rwe

Asia Paciﬁc & Japan

8 Cross Street #21-01/02/03 Singapore 048424 Singapore Tel: +65 6412 7365 Toranomon Towers Office 4-1-28 Toranomon Minato-ku Tokyo 150-0001 Japan Tel: +81 3 5425 9541