European Hospital and Healthcare Management - Issue 02 by Ochre Media Pvt. Ltd.

Issue 02

2023

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Thomas Bartel MD, PhD, Interventional Cardiologist Flexdoc GmbH

Diagnosis Related Groups (DRG) vs. Budgetbased ones: A Healthcare Perspective PAG E

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Digital Health: Healthcare Digitization, Innovations & the Roadmap

PAG E

The Role of ML/AI in Healthcare w w w. e u r o p e a n h h m . c o m

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You’re Guide to the Frontiers of Medical Advancement “Diving Deep into Healthcare's Hidden Stories of Triumph" In the world of healthcare, where conventional conversations dominate, there exists a concealed universe beyond our daily discourse - a realm where visionary thinkers unite empathy with ground-breaking ideas, pushing the boundaries far beyond what’s achievable. Welcome to the heart of healthcare, where we forge ahead to illuminate the hidden stories that sculpt the continuously evolving medical landscape. In this edition of EuropeanHHM, we delve into the ever-evolving landscape of healthcare, exploring the critical aspects of digital transformation and its implications for healthcare providers. We jumpstart this issue by addressing a pressing health concern in “Sleep Disorders: Symptoms, Causes, and Treatment,” authored by Aarti Desai, Shriya Sharma, and Rohan Goswami of the Mayo Clinic. Their in-depth investigation into different sleep disorders, their associated symptoms, and potential treatment strategies highlights the significance of early recognition and management, which is essential for preventing long-term complications and enhancing well-being. In “The Role of ML/AI in Healthcare”, Abhinav Chandra, Executive Medical Director of Specialty Care at Yuma Regional Medical Center, outlines the growth of AI in healthcare. Abhinav Chandra emphasizes the need for cautious optimism and tailoring AI to address the unique challenges of the healthcare industry. "Digital Health: Transforming Healthcare's Future through Education, Empowerment, and Innovation" Dipu Patel, Vice Chair for Innovation at the University of Pittsburgh, explores the profound impact of digital health on healthcare education, patient empowerment, and innovation. The article highlights the transformative potential of digital healthcare in bridging traditional and digital approaches. Gaurav J. Kumar, Medical Director at Dedalus, kicks off our discussion with an insightful article that delves into the intricacies of “Digital Transformation within the healthcare industry”. Gaurav Kumar emphasizes the significance of considering strategic components beyond technology implementation, especially in

complex healthcare settings. His piece provides valuable insights into overcoming challenges and optimizing IT investments for digital transformation. Sony Prabowo, Acting Hospital Director at Ciputra Mitra Hospital, offers a glimpse into the "Future of Quality and Patient Safety in Healthcare." Prabowo discusses the evolving trends and developments that are expected to shape the future of healthcare, emphasizing the importance of patient safety and quality metrics. Dr. Thomas Bartel, an esteemed Interventional Cardiologist at flexdoc GmbH, brings to the forefront a vital discussion - the dichotomy of “Healthcare systems driven by Diagnoses-Related Groups (DRG) versus the budget-based alternatives”. His insights delve deep into the heart of this complex matter, scrutinizing the impact on patient care, economics, and beyond. As we explore these diverse perspectives and insights, it is evident that the healthcare sector is undergoing a remarkable transformation. We hope that the second edition of EuropeanHHM Magazine serves as a valuable resource for healthcare professionals. If you have a perspective, an idea, or a story to share, we welcome your voice in our upcoming issues. Whether it's an article that sheds light on an emerging trend, an interview with a thought leader, or a unique insight into the healthcare ecosystem, your wisdom can be a beacon guiding others in the healthcare journey. We want to hear from you via email: editorial@europeanhhm.com Thank you for being a vital part of the EuropeanHHM community. We eagerly anticipate the continued exchange of ideas and knowledge, as together, we are navigating the ever-evolving healthcare landscape.

N D Vijaya Lakshmi Editor

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CONTENTS HEALTHCARE MANAGEMENT 08 Digital Transformation of Hospitals Themes, Challenges and Strategic Planning for Success Gaurav J. Kumar, Medical Director, Dedalus

18 The Challenge of Clinical Care Coordination Dr DJ Hamblin-Brown, CEO, CAREFUL, UK

26 The Financial Toll of In-Patient Falls: A Study on Costs and Prevention Yogamaya Nayak, Healthcare Quality Assurance Expert Gaurav Loria, Senior Healthcare Executive Seerat Thind, Dentist, IIHMR University

CoverStory

Diagnosis Related Groups (DRG) vs. Budget-based ones: A Healthcare Perspective Thomas Bartel

Nishant Nishit, Healthcare Professional

MD, PhD Interventional Cardiologist Flexdoc GmbH

MEDICAL SCIENCES 42 Sleep Disorders: Symptoms, Causes and Treatment Aarti Desai, Research Fellow of Advanced Heart Failure and Transplant, Mayo Clinic Shriya Sharma, MBBS, Division of Advanced Heart Failure and Transplant, Mayo Clinic Rohan Goswami, MD, Director of Heart Transplant Innovation and Research, Mayo Clinic

49 Infection Control in Health Care Facilities Hassan Mostafa Mohammed, Chairman & Chief Executive Officer, ReyadaPro

FACILITIES & OPERATIONS 71 The Future of Quality and Patient Safety in Healthcare Sony Prabowo, Acting Hospital Director, Ciputra Mitra Hospital

79 Impact on the Workforce with AI in Healthcare James Doulgeris, Chairman, Population Health Advisory Board, RSDSA

INFORMATION TECHNOLOGY

SURGICAL SPECIALITY 58 Postoperative Pain Management, Esp. Thoracic Surgery Paul Swatek, OA for thoracic surgery, Medical University of Graz

64 Transforming Healthcare with AI: A Cardiac Surgical Perspective Anitha Chandrasekhar, MSc, DMSc, FIECMO, FAPACVS, Clinical Lead- Lung Bioengineering & Organ Procurement, Northwestern Memorial Hospital

88 Combating the Global Healthcare Cost Crisis with Artificial Intelligence Simon Waslander, Chief Operating Officer of Teleios Health

EXPERT TALK 94 Digital Health: Healthcare Digitization, Innovations & the Roadmap Dipu Patel, Vice Chair for Innovation, Department of Physician Assistant Studies, University of Pittsburgh

99 The Role of ML/AI in Healthcare Abhinav Chandra, Executive Medical Director of Specialty Care, Yuma regional medical center

108 NEWS 106 EVENTS LIST 112 EVENT PREVIEW 4

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INTERVENTIONAL IMAGING

GAP - P23002168 - Jun 2023

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Advisory Board

Andrey Andreevich Kapitonov CEO, Oxygen Technologies Group, UK

Aung Pyae Kyaw Executive Director, Asia Royal Hospital, Myanmar

Eiman Shafa Medical Director, Spine Surgery Abbott Northwestern Hospital, USA

David Anthony Pearce Director, Business Alliance EMEA, Asensus Surgical, Germany

Gabe Rijpma CEO, Aceso Health, New Zealand

Guglielmo Brayda CEO, Inframedica Sarl, Luxembourg

Hassan Mostafa Mohammed Chairman & Chief Executive Officer, ReyadaPro, Saudi Arabia

Likaa Najuib Medical Marketing Operational Officer, Alfacure Oncology Center, Egypt

EDITOR Vijaya Lakshmi N D EDITORIAL TEAM Sarah Richards Debi Jones Harry Callum Supraja B R ART DIRECTOR M Abdul Hannan PRODUCT MANAGER Jeff Kenney SENIOR PRODUCT ASSOCIATES Sussane Vincent John Milton Peter Thomas Ben Johnson PRODUCT ASSOCIATE Ethan Wade Jacob Higgins CIRCULATION TEAM Sam Smith SUBSCRIPTIONS IN-CHARGE Vijay Kumar Gaddam HEAD-OPERATIONS Sivala VNR

Paola Antonini Chief Scientific Officer, Meditrial Global CRO, Italy

Pinheiro Neto Joao Chief Executive Officer, Meu Doutor, Angola

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Piyanun Yenjit Managing Director, APUK Co.,Ltd, Bangkok

Predrag Ristic

Ochre Digi Media www.ochre-media.com

CEO, Pharmillennium Consulting L.L.C., Serbia

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The products and services advertised are not endorsed by or connected with the publisher or its associates. The editorial opinions expressed in this publication are those of individual authors and not necessarily those of the publisher or of its associates.

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Digital Transformation of Hospitals Themes, Challenges and Strategic Planning for Success

This article explores the themes of digital transformation in the healthcare providers’ industry particularly taking care to include dimensions which are important for success beyond acquiring and implementing a digital technology. Hospitals being complex in processes, and dependent on human stakeholders & drivers, would benefit a lot from considering these strategic components of a digital transformation plan. In this article we discuss the main challenges and ways to plan & mitigate them so as to achieve returns of IT investments made with an agenda of Digital Transformation. Gaurav J. Kumar Medical Director, Dedalus

What is Digital Transformation? Digital transformation is the process of using digital technologies to fundamentally change how an organization operates and delivers value to its customers. It involves the integration of digital technology into all aspects of an organization, which can lead to significant changes in the way the organization conducts

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business, interacts with customers, and delivers products and services. The specific goals and outcomes of digital transformation can vary from one organization to another, but in general, the aim is to stay competitive and relevant in the digital age, improve operational efficiency, and better serve customers and stakeholders using technology.

Key components of digital transformation 1. Technology adoption: The deployment of technologies such as cloud computing, data analytics, artificial intelligence, the Internet of Things (IoT), and others to enhance operations and decision-making. 2. Process optimization: Rethinking and redesigning existing business processes to leverage digital tools, streamline operations, and improve efficiency. 3. Data-driven decision-making: Utilizing data and analytics to gain insights into customer behavior, market trends, and internal operations, which can inform strategic decisions. 4. Customer-centric focus: Placing a strong emphasis on understanding and meeting the evolving needs and expectations of customers by using digital channels and tools to enhance customer experiences. 5. Cultural and organizational change: Encouraging a culture of innovation, adaptability, and continuous learning within the organization to support the adoption of digital technologies.

Innovation, Adaptability, & Continuous learning are the driving forces in an Organization's Digital Transformation

6. Agile and flexible approaches: Embracing methodologies like Agile and DevOps to quickly respond to changing market conditions and technology developments. 7. Security and compliance: Ensuring that digital transformation efforts prioritize cybersecurity and adhere to relevant data protection regulations and standards.

Key technologies to achieve Digital Transformation goals While there are organisations that still need to define their EMR/EHR requirements and fulfil these with a robust EMR, most organizations looking at Digital Transformation should already have this in place to provide the fundamental technology that has hopefully replaced to a great extent their traditional “paper-based medical records”. These systems, often looking outdated and bureaucratic, are yet key scaffolding to build upon, because they store and manage patient information, including medical history, diagnoses, treatment plans, medications, and test results, making it easier to access and share patient data among healthcare providers. EHRs w w w. e u r o p e a n h h m . c o m

improve patient care and reduce administrative tasks. A modern, robust, comprehensive EMR/ EHR is the framework over which technological innovations can be seeded for sustainable growth and benefits with the selection and implementation of the below range of technologies. 1. Cybersecurity Solutions: Robust cybersecurity measures are essential to protect patient data and maintain the confidentiality, integrity, and availability of healthcare systems and records. 2. Cloud Computing: Cloud-based solutions can provide scalable and cost-effective storage and processing capabilities, making it easier to store and manage healthcare data securely. 3. 5G Connectivity: The high-speed and low-latency capabilities of 5G networks can support real-time data transmission for telemedicine, IoT devices, and remote monitoring. 4. Patient Engagement Platforms: These platforms enable patients to interact with their healthcare providers, schedule appointments, access their health records, and receive educational materials. 5. Big Data Analytics: Hospitals can leverage big data analytics to analyze large volumes of healthcare data, identify trends, and make informed decisions for patient care, resource allocation, and operational efficiency. 6. Mobile Health (mHealth) Apps: Mobile 10

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apps for patients and healthcare providers can improve patient engagement, enable remote monitoring, and provide health education and medication reminders. 7. Telemedicine: Telemedicine technology enables remote consultations and telehealth services, allowing patients to connect with healthcare providers through video calls, phone calls, or secure messaging. It expands access to care and can be especially valuable during emergencies and in rural areas. 8. Health Information Exchange (HIE): HIE systems facilitate the secure sharing of patient health information between different healthcare providers and systems. This interoperability is crucial for coordinated patient care and for reducing redundant tests and procedures. 9. Internet of Things (IoT) Devices: IoT devices, such as wearables and medical sensors, can continuously monitor patient vital signs, providing real-time data to healthcare providers and helping in early disease detection and management. 10.Robotic Process Automation (RPA): RPA can automate administrative and repetitive tasks such as appointment scheduling, claims processing, and billing, reducing administrative burden and improving efficiency. 11.Digital Health Records Management: Efficient document management systems help hospitals store and manage digital health records securely and in compliance with regulations.

Application of Digitization for a Hospital given its functional complexity must bring Speed, Transparency and a better service stack for the patients with depreciating operational cost in the time to come 12.Artificial Intelligence (AI): AI can be used for medical imaging analysis, diagnostic support, predictive analytics, and patient management. Machine learning algorithms can help identify patterns and trends in patient data, improving decisionmaking and patient outcomes. 13.Blockchain: Blockchain technology can enhance the security and integrity of health records and ensure data privacy and interoperability, which is crucial in healthcare. Digital transformation in healthcare involves a holistic approach that integrates these technologies with proper training, cybersecurity measures, and adherence to regulatory requirements to enhance patient care, improve workflows, and optimize operational efficiency in hospitals.

Challenges in implementing digital technologies Implementing digital technologies in hospitals comes with a set of common challenges, many

of which are unique to the healthcare industry due to its complex regulatory environment, patient-centered nature, and the critical importance of patient data. Some of the challenges hospitals typically face include: 1. Cost and Budget Constraints: Digital technology adoption often requires significant financial investments, including the purchase of hardware and software, training, and ongoing maintenance. Hospitals may struggle to secure the necessary funds. 2. Interoperability: Healthcare systems often use various legacy technologies and vendors, making it challenging to achieve seamless data exchange and interoperability between different systems and departments. 3. Data Security and Privacy: Protecting patient data from breaches and ensuring compliance with healthcare regulations (e.g., HIPAA in the United States) is a top priority but also a complex and costly endeavor. 4. Resistance to Change: Healthcare professionals may be resistant to adopting new technologies due to concerns about workflow disruption, data accuracy, and usability issues. 5. Training and Education: Staff must be trained to use new technologies effectively, and ongoing education is necessary as systems and tools evolve. Training can be time-consuming and expensive. 6. Regulatory Compliance: Hospitals must adhere to a myriad of healthcare w w w. e u r o p e a n h h m . c o m

regulations and standards, and digital technology implementation must align with these requirements. 7. Vendor Selection: Choosing the right technology vendors and solutions can be challenging, as hospitals need to consider factors like functionality, scalability, and long-term support. 8. Workflow Integration: Ensuring that digital tools fit seamlessly into existing clinical and administrative workflows is crucial for minimizing disruptions in patient care and operations. 9. Data Management: Handling the influx of digital data and ensuring its accuracy and relevance can be a significant challenge. Hospitals need robust data management strategies. 10.Staffing and Resource Shortages: A shortage of skilled IT professionals and limited IT resources can hinder the successful implementation and maintenance of digital technologies. 11.Patient Engagement: Encouraging patient engagement with digital tools can be challenging. Many patients, particularly older individuals, may be uncomfortable or unfamiliar with technology. 12.Change Management: Successfully managing change within the organization, including overcoming resistance to new technologies and new processes, is essential for adoption. 13.Workflow Optimization: Achieving the expected efficiencies and improvements in 12

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patient care requires a re-evaluation and, in some cases, an overhaul of existing workflows and processes. 14.Patient Safety and Clinical Validation: Ensuring that new technologies meet high standards of patient safety and that they have been clinically validated can be timeconsuming and costly. 15.Scalability and Sustainability: Hospitals need to ensure that their digital technologies are scalable to meet future demands and that they can be sustained over the long term. Addressing these challenges requires careful planning, strong leadership, effective change management, and a commitment to ongoing innovation and improvement. Collaboration with healthcare IT experts and vendors, as well as continuous monitoring and evaluation, can help hospitals navigate the complexities of digital technology implementation successfully.

Developing a strategy for the adoption of digital technologies Developing a strategy for the adoption of digital technologies in hospitals is a complex but crucial endeavour. It involves careful planning, commitment from stakeholders, and a focus on improving patient care and operational efficiency. Here's a framework for creating a strategy for digital technology adoption in hospitals:

1. Assessment and Needs Analysis: a. Current State Assessment: Begin by

evaluating the hospital's current technology infrastructure, processes, and challenges. Identify areas that need improvement or optimization. b. Stakeholder Input: Involve clinicians, administrators, IT staff, and other key stakeholders in identifying specific needs and pain points. Their input is valuable for aligning technology adoption with realworld hospital requirements.

2. Vision and Objectives: a. Define a clear vision for what the hospital aims to achieve through digital transformation. This could include improving patient care, reducing operational costs, or enhancing data security. b. Establish SMART (Specific, Measurable, Achievable, Relevant, Time-bound) objectives that align with the vision. For example, a goal might be to reduce patient wait times by a certain percentage within a specific timeframe.

3. Governance and Leadership: a. Appoint

dedicated

digital

transformation team or a Chief Digital Officer (CDO) responsible for overseeing and driving the transformation effort. b. Ensure buy-in from top hospital leadership, including the board of directors, CEO, and department heads, to ensure support and resources for the initiative.

4. Budgeting and Resource Allocation: a. Develop a budget that accounts for hardware, software, training, and ongoing maintenance costs. Ensure resources are allocated in line with the priority of various digital projects.

5. Technology Selection: a. Evaluate and select appropriate digital technologies that align with the hospital's goals and objectives. This may include EHR systems, telemedicine platforms, data analytics tools, and more. b. Prioritize technologies that enhance patient care and safety, streamline operations, and improve clinical outcomes. w w w. e u r o p e a n h h m . c o m

6. Change Management and Training:

10. Monitoring and Evaluation:

a. Implement a comprehensive change management plan to prepare staff for the adoption of digital technologies. This should include training programs, workshops, and ongoing support. b. Ensure that healthcare providers and staff are comfortable with the new technologies and understand their benefits.

a. Implement key performance indicators (KPIs) to assess the impact of digital technologies on patient care and operational efficiency. Regularly monitor progress and make adjustments as needed.

7. Data Security and Compliance: a. Develop robust data security and privacy protocols to protect patient information and ensure compliance with healthcare regulations (e.g., HIPAA in the United States). b. Regularly update and audit security measures to adapt to evolving threats and compliance requirements.

11. Scaling and Expansion: a. Gradually scale up the adoption of digital technologies across the hospital, department by department, as needed. Ensure proper support and training are in place as new areas come on board.

12. Patient and Stakeholder Engagement: a. Communicate the benefits of digital transformation to patients and involve them in the process where applicable. Solicit their feedback to continuously improve the patient experience.

8. Integration and Interoperability: a. Ensure that new technologies integrate seamlessly with existing systems, particularly EHRs and other critical healthcare platforms. Interoperability is vital for data sharing and continuity of care.

9. Pilot Programs: a. Before full-scale implementation, conduct pilot programs in select departments to test technology functionality and gather feedback. This allows for adjustments and refinements before hospital-wide deployment.

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13. Continuous Improvement: a. Commit to an ongoing process of innovation and adaptation to stay current with technology trends and evolving healthcare needs. Digital transformation in hospitals is an ongoing journey. Hospitals should remain agile and open to change, continually seeking ways to leverage technology to enhance patient care and streamline operations.

Calculating ROI on Digital Transformation Calculating the Return on Investment (ROI) on digital transformation initiatives is essential

2. Determine the Baseline Measurements:

The ROI formula is relatively straightforward, but the challenge lies in accurately quantifying the benefits and costs associated with digital transformation

to assess the effectiveness and impact of these projects. The ROI formula is relatively straightforward, but the challenge lies in accurately quantifying the benefits and costs associated with digital transformation. Here's a step-by-step guide on how to calculate ROI for digital transformation:

1. Define the Objectives and Key Performance Indicators (KPIs): a. Clearly outline the specific objectives of your digital transformation project. What are you trying to achieve? Examples include improving operational efficiency, increasing revenue, reducing costs, or enhancing customer satisfaction. b. Identify the KPIs that are relevant to your objectives. These could be metrics like revenue growth, cost reduction, improved customer retention, or increased productivity.

Before implementing the digital transformation project, establish baseline measurements for the KPIs you identified. These measurements represent the current state of your business processes.

3. Calculate Costs: Quantify the total costs associated with the digital transformation project. These costs may include technology investments, software development, hardware purchases, training, consulting fees, and ongoing maintenance.

4. Quantify Benefits: Measure the improvements in the chosen KPIs resulting from the digital transformation. This could involve comparing post-implementation KPI data to the baseline measurements. For example, if you aimed to reduce customer service response times, measure the actual reduction achieved.

5. Calculate ROI:

Use the following formula to calculate ROI: ROI = [(Net Benefits - Total Costs) / Total Costs] * 100 Net Benefits: The difference between the benefits (improvements in KPIs) and the total costs.

Total Costs: The sum of all costs associated with the digital transformation project.

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6. Account for the Time Frame:

7. Factor in Risk and Uncertainty:

References are available at www.europeanhhm.com

Consider the potential risks and uncertainties associated with your digital transformation project. Assess how these risks may impact the ROI calculation. It's advisable to perform sensitivity analysis to account for different scenarios.

AUTHOR BIO

Consider the time frame over which you want to measure the ROI. Depending on the project, this may be short-term (e.g., within a year) or long-term (e.g., over three to five years). Ensure that the time frame aligns with the objectives and KPIs.

cases, it's essential to use qualitative data alongside quantitative metrics to provide a comprehensive view of the project's success. Additionally, it's advisable to consult with financial and technology experts to ensure that your calculations are accurate and comprehensive.

8. Present the ROI Analysis: Clearly present the ROI analysis to stakeholders and decision-makers, using easily understandable visual aids like graphs, charts, and a narrative of the findings. This ensures sustained buy-in.

9. Continuous Monitoring and Adjustments: ROI is not a one-time calculation. It's essential to continuously monitor the project's performance against the established KPIs and adjust the strategy as needed. Digital transformation is an ongoing process, and adjustments are often required to maximize ROI. Remember that ROI calculations for digital transformation can be complex due to the intangible benefits, such as improved customer satisfaction or competitive advantage. In these 16

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Dr. Gaurav J Kumar, is a surgeon and Health IT leader with over 20 years of experience in patient care and managing hospitals in medical services, hospital operations and digital transformation. He currently serves as Medical Director at Dedalus Healthcare for the India region. His expertise is in the digital transformation of hospitals, change management & adoption of technologies to achieve efficiencies and improve the quality of healthcare delivery.

EUROPEAN HOSPITAL & HEALTHCARE MANAGEMENT EUROPEANHHM with its keen interest across the length and breadth of the healthcare world aims to provide premium, cutting-edge & reliable healthcare content to its subscribes base in the European region.

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These days, healthcare management is in extremely high demand

As a result of the development of medial sciences, we are now enjoying better and long lives.

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THE CHALLENGE OF CLINICAL CARE COORDINATION Recent decades have seen increasing complexity of patient pathways especially for patients with chronic diseases and co-morbidities. This has led to information gaps and silos, with implications for safety, access, and outcomes. This article examines examples of how care coordination can fail and how health systems, governments and entrepreneurs are approaching the problem of care coordination. Dr DJ Hamblin-Brown CEO, CAREFUL, UK

linical care coordination is the process of organising and coordinating healthcare and related services for patients, particularly those with complex medical conditions. It involves ensuring that all necessary medical services, tests and treatments are provided in a timely and efficient manner ensuring that patients receive the right care at the right time, in the 18

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right place, and from the right provider. Effective clinical care coordination is therefore crucial for improving patient outcomes and reducing healthcare costs. It requires a multidisciplinary approach, from doctors, nurses, allied health professionals, social workers and others. The author is an emergency medicine doctor with senior management experience in the acute sector. This article builds on his direct experience of problems of care coordination as both a physician, a relative and carer, as well as a healthcare leader.

Three cases CASE 1 A 45-year-old man with crushing central chest pain is admitted to the emergency room with suspected MI. The patient's blood sugar level of 29 mmol/l suggests that type 2 diabetes is a likely precipitating factor. The patient’s relatives report that his HbA1c was measured at 6% 3 years ago but had not been repeated, as required by guidelines. Discussion: The prevalence of T2 diabetes is growing exponentially worldwide and presents a significant public health problem in many countries as they develop and age. Who was responsible for ensuring that this test was repeated? Had the patient moved under the care of different care organisation? How the patient was made aware of the original test result.

Effective clinical care coordination is crucial for improving patient outcomes and reducing healthcare costs.

CASE 2 A 29-year-old woman, 23 weeks into her second pregnancy is admitted to the ED with collapse and sepsis. She has a positive ‘flu test. Her baby was born with extreme prematurity, and she spent two weeks in ICU. Her family remember that she was offered a ‘flu vaccine but failed to attend her appointment. Discussion: Pregnant women have poorer outcomes with influenza, as do their babies. No adverse effect at the population level has been observed from the vaccine. Who knew that this woman had failed to attend her vaccination appointment? Whose responsibility was it to follow up?

CASE 3 A 75-year-old bed- and chair-bound man is re-admitted to hospital with sepsis caused by a worsening of a large sacral bed sore. He had been discharged three weeks earlier following an admission for a fall. The dressing had not been changed while he was at home. w w w. e u r o p e a n h h m . c o m

Discussion: Frail elderly patients are at risk of deterioration following discharge for a number of reasons. Discharge instructions can be confusing or absent in many cases. Community nursing colleagues and families are often not aware of the care plan put in place by the discharging hospital. Who was responsible for managing the pressure ulcer?

The core challenges 1) Lack of visibility of information across boundaries All patients, but especially those suffering from chronic diseases and significant co-morbidities, often see multiple providers across different settings, which makes their care fragmented and disconnected. The core challenge is that the information visible to one team may not be visible to another. These information gaps can lead to lapses of care, such as the cases given above, but also to additional ‘care’ such as repeated tests or unnecessary visits to practitioners.

2) Lack of accountability of action As emphasised in the examples above, much of the problem of clinical care coordination comes from a lack of clarity about who is to do what, by when. We are all commonly aware that without individual accountability (such as when we use ‘all’ in meeting notes) there is ultimately a loss of action. Most electronic medical records, if they record actions at all, store these either as 20

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appointments or as lists, with little regard for who is responsible.

3) Complexity of care pathways As care becomes more complex, more interrelated actions are required to effect good outcomes. For example, the pathway for a fractured neck of femur when printed in ‘booklet form’ may run to several tens of pages, involving actions over many days of care from preparation for surgery, catheter removal, mobilisation and more.

4) A lack of patient involvement Many patients want to be involved in their care but are either excluded or find it difficult to understand what is needed. When highly activated patients or their families are involved, this can help reduce errors and omissions. For the frail or elderly, or patients who live alone, this can be challenging.

Impact of poor clinical care coordination Poor care coordination can have a number of negative consequences for patients, including: • Delayed or missed care: Patients may not receive the care they need in a timely manner, or they may miss appointments altogether. • Medication errors: Patients may be prescribed the wrong medications, or they may take medications incorrectly. • Duplication of services: Patients may take the same tests or receive the same procedures multiple times.

and other healthcare professionals. • Case management: Case managers are healthcare professionals who work with patients and their families to coordinate care. Case managers can help patients navigate the healthcare system, schedule appointments and communicate with providers. • Health information technology (HIT): HIT can be used to improve care coordination by providing providers with access to patient information, such as medical records and medication lists. HIT can also be used to track patient progress and communicate between providers.

Health systems, governments and entrepreneurs • Hospital readmissions: Patients with chronic diseases are more likely to be readmitted to the hospital if their care is not coordinated effectively. • Higher healthcare costs: Poor care coordination can lead to higher healthcare costs due to unnecessary duplication of services and hospital readmissions.

Approaches to care coordination There are a number of different approaches to care coordination. Some common approaches include: • Care teams: Care teams are groups of providers who work together to coordinate care for a patient. Care teams may include doctors, nurses, social workers, pharmacists

Health systems, governments and entrepreneurs are all taking steps to address the challenge of care coordination. Health systems are developing new care models, such as patient-centred medical homes and accountable care organisations that focus on coordinating care for patients with chronic diseases. Governments are investing in HIT and other technologies to improve care coordination. Entrepreneurs are developing new products and services to help providers coordinate care more effectively.

The future of care coordination The future of care coordination is likely to be shaped by a number of trends, including: • The rise of value-based care: Valuew w w. e u r o p e a n h h m . c o m

based care is a healthcare delivery model that focuses on improving patient outcomes while reducing costs. Care coordination is essential for value-based care to be successful. • The increasing use of technology: Technology will play an increasingly important role in care coordination. For example, electronic health records (EHRs) can be used to share patient information between providers. Telehealth can be used to provide care to patients in remote locations. And wearable devices can be used to collect data about patients' health and activity levels. • The shift to population health management: Population health management is an approach to healthcare that focuses on improving the health of entire populations, rather than individual patients. Care coordination is essential for population health management to be successful.

Considerations To ensure that patients receive the best possible care, health systems, governments and entrepreneurs are all taking steps to address this challenge. By working together, these approaches can improve care coordination and deliver better outcomes for patients. One important issue is the role of the patient. Patients are increasingly being recognised as active partners in their own care coordination. Patients can play a role in 22

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By working together, we can create a healthcare system where all patients receive the coordinated care they need to achieve the best possible health outcomes.

their own care coordination by: • Communicating their needs and goals to their providers. • Organising their medical records. • Keeping track of their appointments and medications. • Asking questions and advocating for themselves. Another important issue is the use of data and analytics to improve care coordination. Data and analytics can be used to identify patients who are at risk of poor outcomes, such as hospital readmission. This information can then be used to develop interventions to improve care coordination for these patients. In addition to the things mentioned above, there are a number of other emerging technologies and approaches that have the potential to transform care coordination in the future. These include: • Artificial intelligence (AI): AI can be used to develop tools that can help providers identify patients who are at risk of poor

Conclusion Despite the challenges, there is a growing recognition of the importance of care coordination. Health systems, governments and entrepreneurs are all investing in new technologies and approaches to improve care coordination. By working together, we can create a healthcare system where all patients receive the coordinated care they need to achieve their best possible health outcomes. AUTHOR BIO

outcomes and develop and implement interventions to improve care coordination for these patients. • Blockchain: Blockchain is a distributed ledger technology that can be used to securely share patient information between providers and organisations. • Patient portals: Patient portals are online platforms that allow patients to access their medical records, schedule appointments and communicate with their providers. These technologies and approaches have the potential to make care coordination more efficient, effective and patient-centred. While there are many opportunities to improve care coordination, there are also a number of challenges that need to be addressed. These challenges include: • Data silos: Patient information is often siloed in different EHR systems and other databases. This makes it difficult for providers to access the information they need to coordinate care effectively. • Lack of interoperability: EHR systems and other healthcare IT systems often do not communicate with each other effectively. This makes it difficult to share patient information between providers and organisations. • Patient engagement: It is important to involve patients in their own care coordination. However, many patients are not comfortable using technology or engaging with the healthcare system.

DJ Hamblin-Brown qualified as a doctor in the UK in 1996, and practised as a Consultant level Emergency Medicine Doctor in the NHS for many years. He was Group Medical Direct of Aspen Healthcare in the UK and VP of Medical Affairs at United Family Healthcare in Beijing. He now is CEO of CAREFUL - a clinical care coordination platform.

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SAFER BLOOD COLLECTION PRODUCTS AND VALUE-BASED CARE GO HAND-IN-HAND In the last decade, regional and global health organisations have pushed for making safety a central pillar of procurement, with a directive that cost should not be a barrier. The crucial question is: How easy is that to implement? How can a confident decision be reached that protects patients and healthcare workers without straining costs?

Prevention is less expensive than treatment and recovery A Royal College of Nursing project reported that 100,000 needlestick accidents occur in the UK every year, and Bevan Brittan, a legal firm representing the

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NHS, estimates the cost of needlestick injuries to each UK NHS trust to be around £500,000 each year in legal costs.1 And in the US, the initial treatment of a needle1 https://www.supplychain.nhs.uk/programmes/safer-sharps

healthcare worker input, ease of use and protecting patient safety and comfort5.

How does a reliable supply chain support safety?

stick injury (NSI) can cost between 800 - 6000 USD each2, with initial costs of medication for the Hepatitis C virus starting at around 25,000 USD3, and fines from OSHA beginning at 13,260 USD4. It should be noted that this is before associated costs are taken into consideration; staff absence interrupts the efficiency of already heavily burdened departments, and reputational damage and morale pose a considerable challenge to a sector that is struggling with staff retention. The takeaway is that indirect costs exceed the direct costs. The EU and OSHA are rigorous in their safety directives with regards to NSI, and arriving at a decision in selecting a safety device that balances costs without sacrificing safety need not be a complicated process.

Which criteria should be used to evaluate a safety device? An established culture of safety feeds into the selection process. But with a vast inventory of products available, how can this process be simplified? The decision should be based on the three pillars frontline 2 AOHP, 2014 3 HealthDay, 11/6/18 4 OSHA, 2018

The culture of safety is in place, a short list of prospective manufacturers has been identified, fulfilling the code of conduct and sustainability criteria and the costs are clear. Should the cheapest option then be chosen? This is where a reliable supply chain can really add value in blood collection. Logistics have been transformed and optimised due to the pandemic, but still face a host of challenges; the costs of raw materials continue to increase and global events impact the availability and delivery of goods. So how does one manufacturer’s offering compare to a competitor’s?

Go with the safety flow We know that the small details of blood collection kit matter in the lab, just as much as they do on the ward. It is why every detail of our products and services are designed with that safety approach in mind. From the moment a blood sample is drawn, to the moment it becomes data.

The right safety product for every situation Greiner Bio-One offers an extensive range of safety products, allowing the most suitable products to be selected for every market and customer. The VACUETTE® QUICKSHIELD Safety Tube Holder is especially suitable for routine blood collection. There is no change to the usual collection technique, and the safety shield is activated one-handed. This product can provide the user with the simplest handling and reliable infection protection. The VACUETTE® EVOPROTECT SAFETY Blood Collection Set is the next stage in blood collection. The semi-automatic click mechanism protects the user from the risk of needlestick injuries and makes the daily task of blood collection easier. 5 https://www.jhsph.edu/research/centers-and-institutes/johns-hopkins-education-andresearch-center-for-occupational-safety-and-health/ce/preventing-occupational-exposurebloodborne-pathogens-healthcare

Read the full article and other interesting stories on our Safety Blog https://www.gbo.com/en-int/safe-blood-collection/safety-blog

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The Financial Toll of In-Patient Falls: A Study on Costs and Prevention The purpose of this research study is to examine the consequences of falls that occur while patients are admitted to the hospital. It emphasizes the importance of implementing strategies to prevent incidents. The study was conducted retrospectively examining fall data from January to June 2023 in more than 40 multi-speciality hospitals. The data sources used included incident reports from hospitals and medical records. This study provides an understanding of how falls impact healthcare by considering immediate medical costs and prolonged hospital stays. It underlines the need for targeted prevention measures that can effectively reduce fall incidents and their associated expenses. Healthcare professionals and policymakers can utilize this study as a resource when developing strategies, for fall prevention.

Yogamaya Nayak DGM, Quality & Operations, Apollo Hospitals

Gaurav Loria Chief Quality Officer & Head Operations Sr. VP, Apollo Hospitals

Seerat Thind Dentist, IIHMR University

Objective

Nishant Nishit Assistant Manager, Quality & Operations Apollo Hospitals

n-patient falls pose a significant risk to patient safety and impose a substantial financial burden on healthcare institutions. By comprehensively analyzing

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the direct and indirect costs associated with patient falls, this research aims to shed light on the economic impact and inform healthcare providers and policymakers about the urgency of implementing effective fall prevention strategies.

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This study aims to identify and evaluate the cost implications of in-patient falls in hospitals.

Design, Setting & Methodology A retrospective observational study was conducted at more than 40 multi-speciality hospitals. Patients with a history of falls

the in-patient fall rate among patients of the vulnerable category was higher. Among the patients who had a fall, 59% had to undergo at least one radiological investigation such as NCCT head, an x-ray of arm, foot, shoulder, pelvis, etc., amongst which 31% of investigations done were NCCT head. Results from this study have provided a comprehensive understanding of the financial impact of in-patient falls, including the immediate medical costs and the cost of extended hospital stays.

Introduction

in the hospitals were considered from 1st January to 30th Jun 2023. In-patient falls data was collected from hospital online incident reporting data base and medical record reviews. A primary data collection method was employed, using datasets already available for patient medical records. The medical records of in-patients were studied to find out the cause, consequence, and management of patients. Patient bills were linked to the falls to calculate the cost of each fall.

Results A total of 246 in-patient falls occurred during the specified period. Our study indicates that

According to the World Health Organisation, a fall is an event that results in a person coming to rest inadvertently on the ground, floor, or other lower levels. Such falls may become deadly for several individuals, such as the elderly, physically disabled, mentally challenged, etc. Consequences of a fall include both direct and indirect costs. Direct costs include increased length of stay, medicines, investigations such as an x-ray, CT, etc., while the indirect costs include transportation and lodging of patient’s attendants, absence from work resulting in loss of wages, cost of food services, prolonged fear of fall, mental distress, etc. The financial impact of fall-related injuries is substantial, however, there is insufficient research on the costs of patient falls in healthcare systems. w w w. e u r o p e a n h h m . c o m

Direct Costs

Additional Referrals

Additional Medicines

Additional Equipment

Additional Investigations

Surgery & Rehabilitation

Additional Manpower

Litigation

Loss of Reputation

Increased LOS

Psychological Distress to Staff

Patient Fall

Indirect Costs

Data Analysis Incidence of falls Our study included 246 unique patients and a total of 3,59,344 patient hospital admissions over a period of January to Jun 2023. (Table 1) Age group

Total falls

>65 years

59%

<65 years

41%

Table 1: Breakdown of total reported falls by age

1. Incidence of falls by age and gender In our study, it was observed that 65 years and older patients suffered more falls. 85.7% of these patients had pre-existing co-morbidities such as hypertension or diabetes mellitus. 28

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• The study indicates that there is higher occurrence of falls among male patients. This observation may be attributed to a higher number of hospital admissions for males. • The data reveals that 89% of men who fell had underlying health issues that may cause weakness, impaired balance and an increased likelihood of falling. • Around 76% of all male patients who experienced falls were prescribed medications known to have a high risk of causing falls, such as antihypertensives, benzodiazepines, antidepressants, etc.

2. Incidence of falls by the vulnerability of patients Vulnerable patients are the ones who are:

• Chronically ill or disabled • Patients <16 years and >65 years • Patients admitted in ICUs • Patients suffering from a mental condition/ disability (Table 2) 67% of all patients with a history of falls were vulnerable (because of old age, weak limbs and muscles, underlying comorbidities, heavy doses of medications, reduced immunity, chronic disabilities, etc.), hence, at a higher risk of falls. Patient Vulnerability Criteria

Percentage of patients

Patients <16 years of age

Patients > 65 years of age

Patients suffering from a mental 9% condition/disability

40%

Patients admitted in ICUs

Table 2: Breakdown of patient falls by patient's vulnerability

3. Incidence of falls per 1000 bed days The average number of admissions per month was reported to be ~59890, while the average occupied bed days were ~9678 from January to Jun 2023. From this data, we calculated the monthly fall rates per 1000 bed days. Falls per 1000 bed days = (Number of falls * 1000) / occupied bed days (Figure 2) • The fall rate per 1000 bed days is the highest in March because of higher number of hospital admissions, and lowest for January. • The average length of stay (LOS) for the period was 3.92.

4. Incidence of falls based on the place of occurrence (hospital setting) At least 77% of patient falls took place in the general wards. Other hospital areas include the emergency wards and intensive care units. (Figure 3)

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STRATEGY

5. Incidence of falls based on time of occurrence of falls

Intensive care units Emergency wards

14% 77% General wards

Figure 3: Breakdown of patient falls by place of occurrence (hospital setting)

• This study found that the maximum falls occurred in the general wards because 64.7% of patients admitted to these wards were unassisted. • Irrespective of fall prevention measures being followed, 78% of falls occurred when the patient did not ring the call bell to ask for assistance. • Amongst those unassisted patients, 63% of falls occurred inside the washroom, while the rest occurred when the patient tried to move out of bed or perform an activity on the bed. (Table 3)

The study indicated that most numbers of falls occurred during 12 - 6 am, i.e., approximately 42%. • It was interpreted that falls during this period occurred because 68% of patients were unassisted at the time of fall. • The reason could be the patient’s unwillingness to request assistance at night or early morning hours. • Before bedtime, most patients were given medicines such as sedatives, benzodiazepines, anti-hypertensives, etc. These drugs may cause sleepiness and dizziness and can lead to falls. (Figure 4)

6. Incidence of falls based on the severity of harm caused A report by the National Patient Safety Agency (NPSA) in 2007 applied falls definitions to these categories: a) No harm: where no harm came to the patient, e.g., no visible bruising. b) Low harm: required first aid, minor treatment, or medication, e.g., graze on the right hand. c) Moderate harm: likely to require outpatient treatment, surgery, or a longer stay in the hospital, e.g., fractured pubic rami. d) Severe harm: where permanent harm, such

Patient Category

Assisted falls

Unassisted falls

Non-vulnerable patients

43%

57%

Vulnerable patients

27%

73%

Table 3: Breakdown of total falls into assisted and unassisted falls 30

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as brain damage or disability occurred e.g., fractured neck of femur. e) Death: where fall resulted in death. (Table 4) • As per falls by severity, 68.2% of total falls occurred among vulnerable patients. • The vulnerable patients are more likely to suffer moderate to severe harm, as these patients are weaker, and more susceptible to harm. (Table 5) • Rehabilitation services mainly included physiotherapy. • The surgery done for patients with a history of falls was to treat fractures of arms and legs. Age groups

• The maximum number of services, including surgery and rehabilitation were provided to the vulnerable patients. • For further management of falls, patients were referred to specialists in neurosurgery, general surgery, and orthopedics. • Additional referrals and investigations for fall account for the highest number of services provided.

7. Additional medical costs by services Our study indicated that among all the clinical services provided to fall patients, imaging services and referral to specialists were the most

Total falls (in

Breakdown by severity (in percentage) No harm

Low harm

Moderate harm

Severe harm

Death

Non - vulnerable patients

31.8%

57.14%

42.86%

Vulnerable patients

68.2%

33.3%

53.3%

13.4%

Table 4: Breakdown of reported falls within age groups by severity

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Additional services for fall management

Vulnerable patients

Non-vulnerable patients

Investigations

31.8%

27%

Medications

27%

Surgery

4.5%

Rehabilitation

4.5%

Referrals to specialists

100%

98.2%

Table 5: Types of medical services provided post-fall

used services, followed by medical services. • Imaging services were used in 59%, while medication services were used in 50% of all cases. • NCCT or Non-Contrast Computed Tomography head/brain was the most used imaging service. 30.7% of all investigations done were NCCT head, followed by X-ray pelvis which was 19.2% of all investigations. Other post-fall investigations included an X-ray of the spine, arm, foot, knee, shoulder, MRI, etc. • Each patient was referred to at least 3 specialties for the management of falls, i.e., surgery, neurosurgery, and orthopedics. The maximum number of referrals given was 6, while the mean or average was 5 referrals.

8. Estimation of the average total cost of fall On the estimation of the average cost of fall per patient, these assumptions were made a. Each patient who suffered a fall, stayed in the facility for one additional day (additional LOS). 32

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b. The average number of monthly falls that occur was assumed to be 41. Around INR 74,000 is spent on managing one fall over six months from January to Jun 2023. • It was further interpreted that indirect costs such as additional LOS constitute the major part of expenditure as indirect costs account for 7 times the direct costs in the total expenditure. • On the further breakdown of cost analysis per patient per fall, we found that patient falls that resulted in low harm incurred the maximum expenditure on the management of a single fall. (Table 6, 7) • Furthermore, the monthly expenditure on the management of falls is approximately INR 30,25,787. • Thus, in a year the facility spends approximately INR 3,63,09,452 on the management of falls.

Discussion In a healthcare facility, patients are regularly monitored for risk of falling. A fall risk assessment tool is used to assist in the same. The fall risk assessment tool consists of a scoring system on the patient’s details, such as

Total falls (in

Breakdown by severity (in percentage) No harm

Low harm

Moderate harm

Severe harm

246

8833.16

18698.75

16141

Table 6: Average estimates of cost of patient fall per patient Average cost per patient in INR (direct costs only)

Average total cost per patient in INR (direct + indirect costs)

10299.7

73799.7

Table 7: Total average cost of fall per patient based on the severity

vulnerability criteria, clinical history, diagnosis, mental health condition, prescribed medications, etc. All these criteria are given a score and the total score is calculated. If the score is equal to or greater than 45, the patient is at a higher risk of falls, and thus needs to be monitored intensively. Patients and their family members/ attendants are also given periodic education on fall prevention measures. These measures include the usage of a call bell for assistance, keeping bedside rails raised, instructions given on– raising, sitting, and moving out of the bed, etc. Additional measures taken by the hospital staff include placing a ‘safety first’ sticker, a fall risk band application, assisting with toilet needs, frequent visits to check the patient, etc. Category

AVERAGE COST (INR)

Per patient

73,799.7

Monthly

30,25,787.7

Yearly

3,63,09,452.4

Table 8: Average cost of fall per patient

Stringent measures are being followed along with patient-family education to prevent falls however, patient falls still pose a risk. The environment or methodology of implementing fall prevention measures may not give desired results for which there are several possible reasons. Firstly, the method of education is standard for all, thus it does not communicate to each patient individually. Secondly, it is generalized for all categories of patients, irrespective of the patient’s vulnerability to falls. Lastly, these measures are communicated without understanding if the patient is receptive to these measures because of the patient’s condition or literacy, or cognition. More robust preventive measures to strengthen patient education in such a way that it brings out the desired results is the need of the hour. The potential savings from reducing falls in hospitals are also substantial. Over the course of a year, the facility spent around INR 3,63,09,452 on fall-related expenses. Strategically reinvesting the savings generated from reducing patient falls can greatly improve healthcare technologies that aim to prevent w w w. e u r o p e a n h h m . c o m

falls. One such technological advancement involves using sensor-based alarms and remote monitoring systems. These innovative solutions utilize sensors and smart devices to detect movements and instantly alert nurses and attendants enabling them to respond quickly and prevent falls. Additionally implementing

these cutting-edge solutions can result in long-term cost savings by reducing fallrelated injuries minimizing hospital stays and improving efficiency in care. References are available at www.europeanhhm.com

AUTHOR BIO

Yogamaya Nayak is a Six Sigma Green Belt certified healthcare quality assurance expert, dedicated to improving patient experience and safety measures. With a proven track record of coordinating, auditing, and solving problems in various hospital settings, she is committed to ensuring compliance and excellence in healthcare delivery.

Nishant Nishit is a healthcare professional and an author. He uses his expertise to educate and empower patients and healthcare providers. He is passionate about improving patient safety, quality of care, and health outcomes through evidencebased practices and communication.

Gaurav Loria is a senior healthcare executive with over 16 years of experience in leading and transforming hospitals, clinics, and healthcare IT. He's a visionary leader who is committed to uplifting global healthcare standards and prioritizing patient safety.

Dr Seerat Kaur, a dedicated dentist, is on a transformative journey. Her passion for patient care led her to pursue an MBA in Health and Hospital Management at IIHMR University, Jaipur. Balancing dentistry with healthcare leadership, Dr Seerat aims to leave a lasting impact on the industry, bridging care and management.

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EUROPEAN

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CoverStory

Diagnosis Related Groups (DRG) vs. Budget-based ones: A Healthcare Perspective Financing of health care systems based on diagnoses-related groups (DRG) is commercially driven, whereas budget-based approaches pursue a planned economy attempt. Typical DRG-based systems can be found in the United States and Germany. The National Health Service (NHS) of the United Kingdom (UK) represents a classic budget-based system, variants of which are also in use in other European countries, e. g. Austria. Both ways have not just economic squeal but also a lot of implications for patient care. Although DRG and budget-based systems are subject to national or even regional regulations, there are specific advantages and disadvantages for patients inherent to both approaches.

1. What do you perceive as the primary advantages and disadvantages of a diagnosesrelated group (DRG) system compared to a budget-based healthcare system from a medical perspective?

Thomas Bartel MD, PhD, Interventional Cardiologist Flexdoc GmbH

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The crucial advantage of DRG-based system is very simple: Just the medical output counts and is paid regardless of how much efforts had to be made to achieve it. In a budget-based healthcare system, the healthcare providers are paid for their presence regardless of their output. This implies that DRG-based system are economically but not necessarily medically

CoverStory

more effective compared to budget-based ones. The reason why economic efficacy not always parallels best practice in medicine is the financial incentive, e. g. to perform more procedures of higher value. This incentive is transmitted from the institution down to doctors by bonus payments. Thus, DRG-based healthcare systems are prone to oversupply what must be considered a clear disadvantage. Orthopedic joint replacement is a very good example of this: Threshold for such an indication is significantly lower in DRG-based system. Of course, adequate regulation, e. g. by implementing “best practice guidelines” and monitoring can attenuate this adverse effect. Shortage of care in remote areas can also be a result in DRG-based system, since healthcare may be unprofitable in areas with low density of population. That is why Germany tries to put budgets on top of its DRG-based system in order to maintain critical care in those areas.

societies can launch specific programs in order to achieve such top performances what usually implies an extra budget. In general, DRG-based systems are more innovationoriented compared to budget-based ones, since new procedures prompt market expansion. In a budget-based system, any new procedure just triggers and is perceived as new and higher costs. Consequently, incentive to implement a new procedure in such a system is low. As we

2. How do you think the DRG system impacts the quality of patient care and outcomes compared to budget-based systems? Economic characteristics of both, commercial and planned economy approaches, translate into quality of patient care at various levels. It’s important to emphasize that there is much less competition in budged-based systems rather than DRG-based ones. As a result, cutting-edge medicine can scarcely evolve in budget-based systems. However, regulators and professional w w w. e u r o p e a n h h m . c o m

CoverStory

all know, planned economy can hardly meet the needs. This translates into a problematic feature of budget-based healthcare systems as are waiting lists. This represents an imposition to the patients and is not the only feature of shortage management. Non-privileged patients often wait, e. g. for computed tomography (CT) exams, coronary angiography and specific surgery for months and sometimes even longer than a year. The higher procedural costs are, the longer is usually the waiting list what has a lot of medical implications as are delayed diagnosis and therapy and potentially worse outcome. DRG-based systems are much less delicate in that regard.

3. In your opinion, what are the key challenges in implementing and maintaining a diagnoses-related group system in a healthcare setting, particularly in terms of patient care and access to services? Those who implement a DRG-based healthcare system must be aware that challenges of DRG driven systems include but are not limited to tendency of oversupply as mentioned above. Professional focus of physicians may shift from patient care to financial interests. When implementing such a system, one of the most important regulatory goals is to keep doctor’s focus on patient care. DRG-based healthcare systems require complete documentation and proper coding, since payment is just provided for documented 38

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Contrasting DRG and budgetbased healthcare highlights economic and patient care impacts, revealing the pros and cons of each approach.

services. Particularly, coding binds considerable resources. In that regard, electronic hospital information systems are much more suitable rather than classic paper-based documentation. That also facilitates monitoring. Usually, there is a monitoring body which verifies invoiced services to be accurately done and documented. This way, check and maintenance of healthcare quality can be guaranteed. Patient access does not depend on the system itself but is provided by insurances. In some countries, not all insurances cover all DRG what may limit access to full benefits of those systems.

4. Can you elaborate on any potential ethical concerns or issues that may arise in the context of a DRG-based healthcare system, especially in relation to patient treatment and resource allocation? Ethical concerns may arise if economic interests are put before patient welfare. Responsibility to disallow is in the hands of hospital leadership, regulators and physicians. Not just patient’s

CoverStory

safety should never fall victim to savings. Quality of care in general should never be neglected for economic benefit. Again, regulators, professional bodies and specialist societies are asked to prevent patients from violation of their interests for profit. They are obligated to closely monitor what happens in the field. That also includes full transparency of the quality of care in hospitals and patient education. Patients have rights they need to be informed about. One of these rights is to know about treatment outcomes of hospitals and departments before making a decision where to go for diagnoses and treatment. Just emancipated patients can exercise their rights in an adequate way to avoid profit-maximizing on their costs.

5. How does the budget-based healthcare system affect the decision-making process for medical practitioners, and what impact does this have on patient care and treatment options? Since availability of high-end medicine is partly limited in budget-based healthcare systems, threshold for specific therapies may be higher. Indications are frequently very much scrutinized what is not necessarily a disadvantage for patients. Once shortages occur, medical practitioners often look for alternatives, e. g. a limited number of British patients was put in contact with Indian healthcare providers for surgery, since the NHS was unable to cover and waiting time for surgical procedures reached up

to eighteen months. In other European countries, older standard procedures were continuously done instead of newer state of the art therapeutic approaches, e. g. conventional open-chest heart valve surgery was performed even in high-risk patients instead of transcatheter valve replacement, as long as there was just a limited budget for the advanced therapy. Even more significant ethical problems may arise if specific procedures and therapies are rationed, as it has been repeatedly reported from some European countries with a budgetbased healthcare system.

6. Based on your experience, what strategies or best practices can be employed to optimize patient care within a DRG-based healthcare system without compromising financial sustainability? In DRG-based systems, there is a potential risk of adverse economic implications right up to insolvency. That’s why best practice could be potentially violated for profit if there were no regulations and quality checks. Expert associations and regulators are obligated to implement transparent systems of licensing, quality inspection and certification of institutions and departments. As a result, standardization of therapies is a powerful tool to improve compliance of healthcare providers. Nevertheless, examples of profitdriven overtherapy have been reported in the past, e. g. barely indicated percutaneous coronary intervention (PCI), although a lot has w w w. e u r o p e a n h h m . c o m

CoverStory been done to bring healthcare providers up to be fully compliant with existing standards for accurate PCI. In terms of accuracy, the need for complete documentation inherent to DRG-based systems helps as well to pursue any violation of best practice.

7. Could you provide examples of successful implementations of DRG-based systems in other countries and how these systems have evolved over time to address challenges related to patient care and overall health outcomes? A very good example of success is the DRG-based system in Switzerland. SwissDRG represents the fare system for all hospital services and was implemented more than ten years ago. The SwissDRG Stock Corporation is responsible for maintenance and further development of diagnoses groups and for their attribution to cases. Therefore, dedicated grouper software is continuously adjusted in order to standardize services, to track medical progress and regulatory changes, e. g. new guidelines and experts’ recommendations.

8. In your view, what role does technology play in supporting and enhancing healthcare systems driven by diagnosis-related groups? How does this differ from its role in budget-based healthcare systems? Digitalization is crucial in order to take full advantage of DRG-based healthcare system 40

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and to cope with disadvantages and risks inherent to this kind of system, too. Artificial intelligence (AI) represents another evolving tool which for example can be used to obtain a computer generated second opinion, e. g. for cancer check-up. As outlined above, implementation of new technology is easier in DRG-based systems compared to budgetbased ones.

9. From a medical standpoint, what policy recommendations would you suggest for countries considering transitioning from a budget-based healthcare system to a DRG-based one, or vice versa, to ensure both the financial viability and quality of patient care? Generally, regulators and healthcare providers are obligated to make up arrangements for complete documentation what may be a challenge. Regulatory policies can be complemented by institutional ones and even by department standards to be guided by diagnoses and treatment guidelines. Expert societies and regulators should surveil strict compliance of all care providers with guidelines and best practice recommendations. Therefore, reporting systems can provide with transparency and may help those who are responsible to pointedly intervene in order to guarantee highest quality allover system’s sphere of influence. That’s the best way to create trust of a population into their healthcare system what is finally the basis of economic success, too.

CoverStory 10. How do you foresee the future of healthcare systems evolving in terms of their financing models, considering the ongoing advancements in medical technology and changing patient needs? What implications might these changes have on both DRG and budget-based systems? The trend is towards DRG-based systems. However, regulators and political decision makers are continuously trying to mitigate disadvantageous consequences which may result from specific characteristics of those systems, e. g. to be driven by financial incentives as explained above. That is why, budget-based components may be increasingly added to DRG-based systems in order to make healthcare even more robust, e. g. in terms of services for rare diseases and in remote areas. Patient’s needs will expand but won’t fundamentally change. In that respect, DRG-based systems seem to be all set for rapid advancements including utilization of new techniques, e. g. less invasive therapeutic approaches, new strategies in oncology or AI based diagnoses and therapeutic conceptualization. Pure budget-based systems are prone to keep after all these developments what makes disadvantages of these systems even more obvious compared to the past.

11. In your professional opinion, what do you believe is the most critical factor that policymakers and healthcare administrators should prioritize when designing

or modifying healthcare systems, whether based on DRGs or budget allocations, to ensure the best possible outcomes for both patients and the overall healthcare ecosystem? Policymakers, healthcare administrators and other regulatory bodies must take care that the system serves patients and not vice versa. Healthcare systems should be adapted to regional or national conditions which may differ a lot from country to country and sometimes even between regions inside a country. Incentives must result in an optimal solution for the patients and so are any measures initiated by the regulators. Of course, interests of healthcare providers should get attention and mustn’t be disregarded. Although the system does not serve them, doctors, nurses, technicians and many others are those who provide patients with the care they need. Healthcare providers are crucial in terms of success of a system and should always be included in decision-making. AUTHOR BIO

Dr. Thomas Bartel is an interventional cardiologist with about 35 years of professional experience. He finished Charité Medical School in Berlin in 1987. He worked at different academic institutions in Germany, the United States, Austria and the United Arab Emirates. In that regard, he was confronted with a broad spectrum of healthcare conditions and systems.

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Sleep Disorders Symptoms, Causes and Treatment Sleep disorders, including Insomnia, Narcolepsy, Sleep apnea, Restless legs syndrome, and Parasomnias affect up to a third of the global population. These disorders disrupt sleep quality and structure, leading to cognitive issues and cardiovascular health risks. Early recognition and management are essential for preventing long-term complications and enhancing well-being.

Aarti Desai MBBS, Division of Advanced Heart Failure and Transplant, Mayo Clinic

Shriya Sharma MBBS, Division of Advanced Heart Failure and Transplant, Mayo Clinic

Rohan Goswami MD, Director of Heart Transplant Innovation and Research, Mayo Clinic

leep disorders encompass a spectrum of conditions disrupting typical sleep patterns, the consequences of which extend to one's overall health, safety, productivity and the quality of life in general. Unprecedented rise in the cases of sleep disorders over the last two decades presents a significant challenge to the clinical healthcare domain. In the 2023 revision of International Classification of Sleep Disorders, ISCD-3, sleep disorders are classified into 6 different 42

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categories with numerous subtypes but the most prevalent are insomnia, narcolepsy, sleep apneas, restless legs syndrome, and parasomnias such as nightmares, night terrors and sleepwalking. There are two distinct stages of sleep that are identified by typical changes in EEG and eye movements: Non-Rapid Eye Movement (NREM) and Rapid Eye Movement (REM) stage. Each cycle lasts 90-120 minutes and 4-8 cycles are required to ensure adequate rest.

Insomnia Insomnia, the most common sleep disorder experienced either in short-term episodes or as a chronic condition, is marked by challenges in both initiating and maintaining sleep. Patients suffer a much lower quality of life due to daytime sleepiness, fatigue, and lack of concentration at work resulting in reduced productivity, increased frequency of errors and accidents in day-to-day activities such as driving. The estimated prevalence of insomnia

is around 10%. Furthermore, insomnia is identified as a persistent condition, lasting for more than five years, and impacts more than 40% of individuals who initially experience severe symptoms of insomnia. It is most commonly precipitated by psychosocial factors such as work-related stress, major life changes (menopause, relocation, medical conditions), relationship difficulties, domestic abuse, and can be caused by substance abuse (alcohol, caffeine). The risk increases with age, female sex (17.6% in females versus 10.1% in men) and psychiatric conditions such as depression, mania, anxiety, and PTSD. COVID-19, its comorbidities and long-term implications have also resulted in an increased incidence of Insomnia worldwide. Clinicians use various scales and questionnaires to assess and diagnose insomnia along with an assessment of medical conditions, psychiatric history and substance use.

The treatment of Insomnia is a huge burden for the healthcare system as it accounts for the loss of more quality-adjusted life-years than any other psychiatric condition or chronic medical condition like hypertension and the direct and indirect costs are in the billions. The most commonly used prescription medications are benzodiazepines such as alprazolam (Xanax), diazepam (Valium), Non-benzodiazepines such as zolpidem (Ambien), eszopiclone (Lunesta). Ramelteon, suvorexant, and doxepin are also used. In addition to medications or as monotherapy, Cognitive Behavioural Therapy for Insomnia (CBTI) remains the first line of treatment and the most comprehensive and here lies the burden. With increasing prevalence of insomnia, cost of mental health services and continuing lack of trained health care personnel, in-person CBT needed to evolve to be more scalable and sustainable. The rise of cell phone apps that offer mindfulness exercises and customer sleep technology such as fitness trackers made this possible and now we have digital CBT for Insomnia (dCBTI) which is fully automated and has the potential to address these issues. dCBTI reduces the frequency of clinic visits and has the potential to reach vulnerable patient groups that may not be able to afford or have access to physicians and psychologists. While in-person CBT outperforms dCBTI, clinical trials have shown significant improvements in sleep, daytime functioning and overall psychological health. w w w. e u r o p e a n h h m . c o m

While numerous forms are available, Somryst is the only FDA approved prescription dCBTI available for the treatment of chronic insomnia which is a 9-week program administered via a cell phone application.

Narcolepsy Narcolepsy, a REM-sleep disorder, is a result of the body’s inability to regulate sleep-wake cycles resulting in excessive daytime sleepiness and may be accompanied by cataplexy (sudden muscle weakness), hallucinations, and sleep paralysis (being awake but unable to move). Normally in an awake state, a neurotransmitter called hypocretin leads to the release of wakestate inducing hormones. Hypocretin levels decrease during sleep leading to atonia. Patients with narcolepsy have reduced levels of hypocretin and it leads to irregular changes between sleep and wake states. Narcolepsy is diagnosed with a detailed history in patients reporting uncontrollable lapses of daytime sleepiness more than 3 times per week for more than 3 months. Short REM latency and hypocretin deficiency are also seen. Children commonly notice poor school performance, falling asleep in class, irritable or antisocial behavior, while adults may experience job impairment, reduced productivity and lower quality of social interactions, which may lead to embarrassment and social isolation. Close to 50% patients have symptoms in their teenage years but diagnosis is delayed 10-15 years in most cases. The stigma and lack 44

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of public awareness of this disorder results in delayed diagnosis and treatment, mainly due to misinterpretation of symptoms as laziness, carelessness or malingering and diagnosis is especially difficult in children and adolescents who may not recognize signs of cataplexy. Early diagnosis and treatment are essential due to an increased risk of aggressive behavior and emotional distress in younger patients, depression, diabetes, headaches, hypertension, obesity, and other sleep and medical disorders in patients with untreated narcolepsy. Fortunately, patients respond well to medication and numerous other strategies are used to establish a healthy sleep routine including strategically scheduled naps, regular exercise and counseling for psychosocial support. To decrease daytime sleepiness Modafinil and Amphetamines are used. In addition to daytime sleepiness, Sodium Oxybate helps with cataplexy. For decades, these were the only medications available and were used in combination with other

antidepressants and hypnosedatives. Recently, the FDA approved the use of Solriamfetol, a phenylalanine derivative, for excessive daytime sleepiness and Pitolisant, H3 receptor antagonist, for narcolepsy with or without cataplexy. Clinical trials have shown promise for a medication that directly modulates hypocretin receptors and Reboxetine, an SNRI for Narcolepsy in adults.

Sleep Apneas: Obstructive and Central Obstructive sleep apnea (OSA), which is due to recurrent upper airway collapse during sleep and Central sleep apnea, resulting from impaired respiratory drive, both cause awakening in an attempt to restore breathing and lead to a significantly reduced quality of sleep and have a strong association with obesity and cardiac health. OSA is far more common, affecting over 900 million adults between the ages of 30-69. It is recognized by loud snoring, choking or gasping at night, drooling, daytime fatigue and sleepiness and headaches. Patients with OSA are also more likely to be involved in driving accidents. Polysomnography remains gold standard and is used to measure ApneaHypopnea Index (AHI), or apneic episodes per hour, that guides the diagnosis. The risk is significantly greater in men, obese individuals, those over the age of 50 and individuals with acromegaly. Numerous processes such as chronically elevated inflammatory markers, oxidative stress, endothelial dysfunction,

atherosclerotic changes, and metabolic derangements have established a multifactorial link between OSA, obesity, diabetes, systemic and pulmonary hypertension, acute coronary events and arrhythmias. Continuous Positive Airway pressure (CPAP) is the primary and most effective treatment for OSA. It prevents upper airway collapse and hence the number of apneic events thereby restoring sleep. Due to its association with obesity, weight loss, healthy diet, exercise and smoking cessation contribute significantly. Rarely surgery may be required and options include adenotonsillectomy, tongue surgery, uvula and palate surgery and other anatomical corrections. There is increased emphasis on the use of CPAP and non-pharmacological treatment but this often leads to decreased patient compliance mostly due to the discomfort experienced when using CPAP while sleeping. Obesity and therefore OSA continues to remain one of the most prevalent disorders globally and hence, new techniques using AI or machine learning will be required in the near future to reduce costs and burden on the healthcare system.

Restless legs syndrome RLS is diagnosed when patients describe a creeping, somewhat stretching or itching sensation followed by an irresistible urge to move their legs. It can occur throughout the day but is reported to be worse at night resulting in jerking movements and therefore insomnia. These urges are worsened by rest w w w. e u r o p e a n h h m . c o m

and improved with exercise such as walking. While the exact mechanism is not known, it is associated with iron deficiency, renal disease, magnesium, vitamin D and folate deficiency, calcium imbalance and certain medications such as antidepressants, diphenhydramine, alcohol, caffeine, and lithium among others. It affects up to 15% of the population and up to a third of all pregnant patients. Though it resolves after delivery, there is a 4 fold risk of developing chronic RLS indicating an association with high estrogen levels. An electromyography or nerve conduction studies help rule out organic causes but history is usually sufficient to make a diagnosis. Treatment with medications is unnecessary unless there is a significant reduction in the quality of life primarily due to sleep disturbances. Exercise, massage, vitamin supplements and eliminating stimulants such as caffeine and alcohol help alleviate symptoms in most cases. There are two devices currently approved by the FDA, the Restiffic foot wraps and the NTx100 Tonic Motor Activation (TOMAC) System, which stimulates the patient's legs with the help of vibrations has shown significant improvement in symptoms and quality of life. For severe cases, dopamine agonists such as pramipexole and ropinirole, rotigotine, and cabergoline have reduced symptoms and improved sleep. Gabapentin and pregabalin can be used initially for patients with severe sleep disturbances, anxiety, and pain. It must be noted that all of these pharmacological options have adverse 46

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effects with long term use for RLS. The data is limited but numerous medications have shown improvements in clinical trials including clonidine which causes a reduced adrenergic response, dipyridamole which affects adenosine levels, glutamate receptor modulation with perampanel, amantadine and ketamine, as well as other anticonvulsants, steroids, bupropion, and cannabis. The treatment aspect of RLS has been gaining momentum due to its decadeslong duration of symptoms in severe cases even with treatment and a significantly reduced quality of life.

Parasomnias: Sleepwalking, Nightmares, and Night terrors Sleepwalking, a form of somnambulism or undesirable movements during sleep, is a NREM sleep disorder which occurs in the first third of the night. There is a complete lack of awareness of the event as it occurs and inability to recall the event afterwards. Patients may run into furniture causing bruises, relocate items around the house, and fall off steps. Very rarely they may exhibit violent or sexually inappropriate behavior. The research into sleepwalking is in its early stages but, the current studies have shown multiple etiologies including a genetic component, excessive sleep deprivation, an association with medications such as Zolpidem, antipsychotics, anticonvulsants, and lithium among others, and hyperthyroidism. While a detailed history is sufficient for diagnosis in most cases, video

polysomnography is used in complex and medicolegal cases. Current treatment options are limited and immediate focus is the safety of the patient while they sleepwalk. Locking interior and exterior doors and windows, removing sharp objects from sight help prevent injuries. Scheduling awakening before usual sleepwalking time helps in some cases, along with counseling. No medication has been approved but clonazepam or gabapentin may help if taken one hour before sleep. Research is underway to gain a deeper understanding of the pathophysiology of sleepwalking and the use of psychotherapy for treatment. Medications currently under research are clonazepam for adults and tryptophan for children. Nightmares occur during REM sleep and are strongly associated with psychiatric disorders such as PTSD with a detailed recall of the actual dream. When associated with trauma and PTSD, the nightmare is related to the event causing PTSD which causes further stress and

sleep resistance where patients fear going to sleep in attempts to avoid the experience. Once awake, patients become alert quickly. Reduced sleep quality and quantity lead to daytime fatigue, reduced attention and performance and psychosocial impairments. Stigmatized, undiagnosed, and untreated, nightmares can persist for decades. Prazocin shows significant improvement in nightmares associated with PTSD. Therapeutic approaches that aim to understand the nightmare and reform maladaptive beliefs, such as CBT, imagery rehearsal therapy (IRT), lucid dreaming, exposure therapy, and desensitization therapy have been very successful. Night terrors occur most commonly in children below the age of 12 during NREM sleep and result in inconsolable screaming or crying with autonomic hyperactivity, feeling helplessness, intense fear, and variable recollection of the event. Most cases are benign fortunately and will outgrow these episodes by adolescence. No specific treatment is required other than reassurance and education. Counseling may help in some cases. Parents are educated to provide support, maintain sleep hygiene and prevent predisposing circumstances such as sleep deprivation and stress. There is also emphasis on avoiding any attempts at interrupting an episode which can result in extreme panic for the child. Benzodiazepines like Clonazepam are used on a short-term basis during periods of elevated terror frequency and intensity causing functional impairment. w w w. e u r o p e a n h h m . c o m

Conclusion: Addressing sleep disorders and promoting healthy sleep habits are essential for individual well-being. Educating patients about good sleep hygiene practices is a fundamental step towards improving sleep quality and preventing longterm complications. Sleep hygiene includes consistent sleep schedules, regular exercise,

the reduction of caffeine, alcohol and nicotine, reducing screen exposure before bedtime, and embracing healthy bedtime routines contribute to more restful sleep. It is imperative to document relevant medication and substance usage and emphasize a holistic approach to sleep management to ensure the overall health and safety of patients.

AUTHOR BIO Dr. Desai is a Research Fellow in the Advanced Heart Failure and Transplant division at the Mayo Clinic in Jacksonville, Florida. She is from Canada and received her medical degree from Surat Municipal Institute of Medical Education and Research (SMIMER), India. She looks forward to making an impact in the primary health care sector with prevention and management of chronic illnesses such as cardiac health and mental health disorders and anticipates starting residency training in 2024.

Dr. Goswami is a Transplant Cardiologist practicing at Mayo Clinic in Florida. He is a graduate of the American University of the Caribbean School of Medicine and completed his internal medicine residency at Columbia University College of Physicians and Surgeons – Stamford Hospital, a cardiology fellowship at The University of Tennessee Memphis, and a Transplant Fellowship in 2017 at Mayo Clinic in Florida. He has a keen interest in clinically focused artificial intelligence research to improve outcomes in patients with advanced heart failure. He has published articles in the field of both heart transplantation and artificial intelligence, as well as presented at Ai4 in 2020 on the future impact of AI in healthcare and invited lectures at the International Society of Heart and Lung Transplantation from 2021 to 2023. He looks forward to one day utilizing AI integration to prevent organ failure.

Dr. Sharma, originally from Kathmandu, Nepal, is a Nepalese Army Institute of Health Sciences - College of Medicine graduate. She is currently a Research Fellow in the Division of Advanced Heart Failure and Transplant at the Mayo Clinic in Jacksonville, Florida. She is interested in staying current with the latest developments and contributing to the advancement of medicine with her clinical research in heart failure, artificial intelligence, and transplant medicine. Her aspirations are directed toward a future practicing cardiology, and she eagerly anticipates commencing her Residency training in internal medicine in 2024.

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Infection Control in Health Care Facilities Implementing infection prevention and control (IPC) practices is paramount in minimizing the spread of infections in healthcare settings. Key IPC measures encompass rigorous hand hygiene, proper utilization of personal protective equipment (PPE), regular environmental cleaning, safe injection practices, and staying up-to-date with immunizations. Furthermore, tailored IPC guidelines exist for diverse healthcare environments and specific infectious diseases, including healthcare-associated infections (HAIs), tuberculosis, and measles. These practices collectively safeguard the well-being of healthcare workers, patients, and the broader community from the transmission of infections. Hassan Mostafa Mohammed Chairman & Chief Executive Officer, ReyadaPro

Infection prevention and control (IPC) Infection prevention and control (IPC) is a set of evidence-based practices and procedures that, when applied consistently, can prevent, or reduce the risk of transmission of microorganisms to health care providers, clients, w w w. e u r o p e a n h h m . c o m

patients, residents, and visitors. IPC is essential for ensuring the safety of healthcare workers and patients. Healthcare facilities are at a high risk for the spread of infection because they care for people who are sick or injured. HCWs should wear PPE as required, following the approved SOP to protect themselves from exposure to infectious diseases during performing their duties. Healthcare workers (HCWs) are at risk because they are exposed to blood, body fluids, and other potentially infectious materials. Healthcare facilities are equipped should be equipped with competent personnel from different disciplines such as physicians, dentists, nurses, laboratory professionals and technicians, facility maintenance engineers and technicians, human resources specialists, social responsibilities staff, cleaning labors, morgue support labors and specialists, kitchen and food services labors and technicians, and Quality and patient safety staff. HCWs can be found in a variety of workplace settings, including hospitals, nursing care facilities, outpatient clinics (e.g., medical, and dental offices, and occupational health clinics), ambulatory care centers, and emergency response settings.

Why IPC is important: • It protects patients from infection: Healthcare-associated infections (HAIs) are infections that patients acquire while they are in a healthcare facility. HAIs can be serious and even life-threatening. IPC 50

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programs help to prevent HAIs by reducing the spread of infection. • It protects healthcare workers from infection: HCWs are at risk for infection because they are exposed to blood, body fluids, and other potentially infectious materials. IPC programs help to protect HCWs from infection by providing them with the training & resources they need to stay safe. • It saves lives and money: HAIs can be costly to treat and can lead to longer hospital stays. By preventing HAIs, IPC programs can save lives and money. IPC is a critical part of healthcare safety. By following IPC guidelines, healthcare workers can help to protect themselves, their patients, and their communities from the spread of infection.

What case infection: Germs are found in everywhere in the healthcare facilities and environment, such as air, soil, drinking water, waste water. Germs live on and inside our bodies. Fortunately majority of them are non-harmful and little percent can cause infection if the conditions are suitable for that. Germs are also found in the healthcare environment. Only a small portion of germs are known to cause infection. For example: Germs need three or four elements to flourished and reproductive according to their types “aerobic and non-aerobic]. They need warmth, moisture, and food, air “as pr the type of germs].

Germs distribution and dispersion can be controlled if we control the environment, personnel and ensure the cleanability and sanitization and/or sterilization of machine, equipment, gauges and apparatus used.

Some examples where we can find germs: • Dry and wet surfaces at the healthcare environment such as wall, floors, beds, trolleys, e.tc • Medical devices/equipment, tools and other items used during patient care and/ or performing operation and if not cleaned and/or sterilized and packed as required following approved SOP. • Germs do not move themselves Germs travelled/transferred through air, personnel, machines, equipment and other items. • We need to pay great attention to control our behaviours withing healthcare facility and environment to minimize/reduce germs dispersion. • All personnel working within healthcare

environment should avoid touching tools, medical equipment, and other items without proper gowns [wearing suitable gloves]. • All need to follow the right and correct behaviour while presenting medication to patients, using needle and/or sharp items to avoid contamination. • All should avoid sneezing, coughing and keep wearing proper mask within the healthcare facility as required.

How do infection occur? 1. Bacteria, virus. Other microbes are types of germs. 2. Germs can cause infectious to patient and/ or visitors and even to healthcare provider when following improper procedures within healthcare facility. 3. Germs cause infection. Germs can be transferred from ill personnel to healthy one while talking, shake hands, sneezing, coughing, touching surfaces. 4. To avoid that, we need to follow strict w w w. e u r o p e a n h h m . c o m

regime in cleaning, sanitation, sterilization as per approved SOP, following the approved SOP, following the instructions of infection control department & Quality and patients safety department 5. We need to apply approved measure to insulate patient with infection diseases in insulation rooms, consideration the type of infection and applying the approved protocol in dealing with them till complete treatment.

Three things are necessary for an infection to occur: • Source: Places where infectious agents (germs) live (e.g., sinks, surfaces, human skin). • Susceptible Person with a way for germs to enter the body. • Transmission: a way germs are moved to the susceptible person, Source is an infectious agent or germ and refers to a virus, bacteria, or other microbe.

Infections spread through: • Direct contact: The most common way that infections spread. It occurs when a person comes into direct contact with an infected person or with an object that is contaminated with an infectious agent. • Indirect contact: This occurs when a person comes into contact with an object that is contaminated with an infectious agent and then transfers the infectious agent to their own body. 52

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• Airborne transmission: This occurs when a person inhales droplets that contain an infectious agent. To avoid that, ill patient shall avoid sneezing and coughing, wearing proper mask all the times, avoid direct contact with healthy persons. When ill patient make sneezing and/or coughing, cleaning, and sanitation protocol should be applies from housekeeping personnel under complete supervision from nurse to assure proper operation. Change the mask to a new one, keep a distance between patient and staff, visitors, unless wearing PPE.

Best practices in IPC: • Hand hygiene: Practicing Hand hygiene is the utmost important practice to prevent the spread of infection. It is important to wash your hands with running water for at least for 20 seconds, followed by soap/ detergent and finally applying sanitizing

agent preferable to be in the form of gel, let it dry off. Before and after patient care, after visiting the bathroom, and after blowing. Rubbing your nose, coughing, or sneezing, following WHO guidelines for hands hygiene. • Personal protective equipment (PPE): wearing PPE will protect healthcare workers and patients from exposure to infectious agents. PPE may include gloves, masks, gowns, and eyewear. PPE types depend on each situation and proceeding conditions. • Environmental cleaning and disinfection: performing required and thorough environmental cleaning and disinfection surfaces, such as countertops, bedrails, tables, chairs, and equipment, should be done regularly and as prescribed in the approved SOP “standard operating procedures to prevent/reduce the possibilities of infection spreading. • Safe injection practices: Practicing safe injection practices are essential for preventing the transmission of bloodborne infections. This includes using sterile needles and syringes for each injection and disposing of sharps safely with adherence of SOP application. • Immunization: Immunization considered is the best recommended ways to protect yourself, families and others from infectious diseases- following the protocols of vaccinations. It is recommended for HCP “Healthcare Providers “to stay up-to-date on all recommended vaccinations in time.

The chain of infection Such as facility, environment, people, animals, tools, machines, equipment, etc. : 1. Infectious agent: The infectious agent is the microorganism that causes the infection. This can be a virus, bacterium, fungus, or parasite. 2. Reservoir: The reservoir is the place where the infectious agent lives and multiplies. This can be a person, animal, plant, or object. 3. Portal of exit: The portal of exit is the way that the infectious agent leaves the reservoir. This can be through coughing, sneezing, vomiting, diarrhea, or contact with blood or other body fluids. 4. Mode of transmission: The mode of transmission is the way that the infectious agent travels from the reservoir to the new host, such as direct contact, indirect contact, airborne transmission, .etc. 5. Portal of entry: The portal of entry is the way that the infectious agent enters the new host. This can be through the mouth, nose, eyes, skin, or wounds. 6. Susceptible host: The susceptible host is the person who is at risk for getting the infection. Some people are more susceptible than others due to factors such as age, health status, and vaccination status.

Examples of how to break the chain of infection: • Infectious agent: Immunization can help to prevent infection by exposing the body w w w. e u r o p e a n h h m . c o m

to a weakened or inactive form of the infectious agent, which helps the body to develop antibodies against the infection. • Reservoir: Treating infected people and animals can help to reduce the number of reservoirs of infection. • Portal of exit: Covering the mouth and nose when coughing or sneezing can help to prevent the spread of airborne droplets. We should wear the proper gloves when handling blood and either body fluids can help to prevent the spread of infection through contact. • Mode of transmission: Washing hands frequently can help to remove infectious agents from the hands and prevent the spread of infection through contact. Avoiding contact with infected people and animals can also help to prevent infection. • Portal of entry: Wearing a mask can help to prevent the inhalation of airborne droplets. Covering wounds can help to prevent the entry of infectious agents through the skin. • Susceptible host: Getting vaccinated is one of the best ways to protect yourself from infection. Eating a healthy diet and getting enough sleep can also help to boost the immune system and make the body more resistant to infection.

Environmental cleaning and disinfection of healthcare It is essential for preventing the spread 54

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and/or help to reduce the risk of infection. Healthcare workers, patients, and visitors can all be exposed to infectious agents on surfaces in the environment. • Cleaning: Cleaning removes dirt, debris, and some microorganisms from surfaces. Cleaning is typically done with soap and water or a detergent solution. • Disinfection: Disinfection kills or inactivates microorganisms on surfaces. Disinfection is typically done with a chemical disinfectant. High-touch surfaces, such as doorknobs, bedrails, and countertops, should be cleaned and disinfected frequently. Surfaces that are contaminated with blood, body fluids, or other potentially infectious materials should be cleaned and disinfected immediately.

Safe injection practices Safe injection practices are essential for preventing the transmission of bloodborne infections, Such as HCV, HBC, and HIV include: • Using sterile needles and syringes for each injection: This is the most important practice for preventing the transmission of bloodborne infections. Needles and syringes should be sterile and unopened before each injection. • Disposing of sharps safely: Sharps, such as needles and syringes, should be disposed of in a puncture-resistant container immediately after use. • Avoiding the reuse of needles and

syringes: Needles and syringes should never be reused, even if they are used on the same patient. • Using single-dose vials for medication: Single-dose vials should be used for medication. Multi-dose vials should only be used if there is no alternative. • Recapping needles safely: Needles should be recapped as little as possible. If a needle must be recapped, it should be done using a one-handed technique. Healthcare-associated infections (HAIs) are infections that patients acquire while they are in a healthcare facility. HAIs can be serious and even life-threatening. Examples of HAIs: • Catheter-associated urinary tract infections (CAUTIs) • Central line-associated bloodstream infections (CLABSIs) • Surgical site infections (SSIs)

• Ventilator-associated pneumonia (VAP) • Clostridium difficile infections (CDIs)

Microorganisms, including bacteria, viruses, and fungi are the reason of healthcare associated infection withing the healthcare facility and environment. To prevent HAIs, HCWs should follow: • Hand hygiene regime, wearing PPEs, performing environmental cleaning and disinfection, and practicing Safe injection practices. • Follow antimicrobial stewardship: Antimicrobial stewardship is a coordinated program that promotes the appropriate use of antibiotics. Development and the spread of antibiotic-resistant bacteria. • Educating patients and their families about HAIs and how to prevent them. • Screening patients for risk factors for HAIs. Using surveillance systems to track HAIs and identify areas where improvement

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is needed and implementing quality improvement initiatives to reduce the risk of HAIs.

Outbreak management: Outbreak management is the process of identifying, investigating, and controlling outbreaks of infectious disease. Outbreak management is essential for protecting public health and preventing the spread of disease. The first step is to identify the outbreak. By monitoring surveillance data for unusual patterns of disease. The next step is to investigate the outbreak. Via determining the etiology of the outbreak, the mode of transmission, and the risk factors for infection. Then control the outbreak. This occurred due to the following measures: • Isolation and quarantine: Isolation and quarantine are used to separate infected individuals from the uninfected population.

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• Vaccination: Used to protect individuals from infection. • Treatment: Treatment of infected individuals can help to reduce the severity of the illness and the risk of transmission. • Environmental cleaning and disinfection: Help to remove infectious agents from the environment and prevent the spread of disease. • Public health education: Used to inform the public about the outbreak and how to prevent the spread of disease.

IPC measures that can be taken to prevent the spread of specific types of infections: • Respiratory infections: Influenza and COVID-19, are spread through the air when an infected person coughs or sneezes. This occurred due to the following measures, healthcare facilities should:

STRATEGY

o Use universal precautions, such as wearing gloves and gowns, when caring for all patients. • Screen patients for risk factors for infection, such as recent travel to areas with outbreaks of infectious disease. • Implement surveillance systems to track infections and identify areas where improvement is needed. • Develop and implement quality improvement initiatives to reduce the risk of infection. By following these and other IPC measures, healthcare facilities can help to protect patients, staff, and the public from the spread of infection. References are available at www.europeanhhm.com

AUTHOR BIO

o Implement respiratory hygiene and cough etiquette practices, such as encouraging patients and staff to cover their mouths and noses when coughing or sneezing. o Use airborne precautions, such as negative pressure isolation rooms, when caring when handling suspect patient with respiratory infection. • Wear appropriate PPE, such as N95 respirators, when caring For suspected patient with infection • Gastrointestinal infections: Norovirus and Clostridium difficile, are spread through contact with contaminated food, water, or surfaces. To prevent the spread of gastrointestinal infections, healthcare facilities should: o Implement hand hygiene practices, such as encouraging patients and staff to wash their hands frequently with soap and water. o Clean and disinfect environmental surfaces regularly. o Use contact precautions, such as wearing gloves and gowns, when caring for patients with known or suspected gastrointestinal infections. • Bloodborne infections: HIV, hepatitis B, and hepatitis C, are spread through contact with infected blood or body fluids. To prevent the spread of bloodborne infections, healthcare facilities should: o Implement safe injection practices, such as using sterile needles and syringes for each injection and disposing of sharps safely.

Dr. Hassan Mostafa Mohamed, Chairman & Chief Executive Officer at ReyadaPro is an entrepreneurial and growth-driven executive with more than 25 years Of experience in pharmaceutical industries, including, Technical, sales & marketing, Production, Supply chain, Engineering/utilities, Quality, and regulatory issues. Mr. Hassan is an expert in driving pharmaceutical facilities to accomplish corporate goals, Building and leading technical &amp; quality aspects with market consideration for rapid Growth, and efficient operational excellence.

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Postoperative Pain Management, Esp. Thoracic Surgery

Postoperative pain is one of the biggest problems in surgery, esp. in thoracic surgery. There are currently many guidelines for postoperative management available, such as the one of the American pain society. These guidelines provide a good standard, but they cannot reflect the individual situations in every surgical procedure and therefore sometimes they have to be adopted especially for the individual person. Besides medication, local anesthesia and line block, minimal invasive surgery and robotic assisted surgery is performed to achieve better pain management. Paul Swatek OA for thoracic surgery Medical University of Graz

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hoosing the correct setting in pain management suitable to the patient is key to rapid recovery after surgery. Postoperative pain in surgery, especially in thoracic surgery, is one of the main reasons for Immobility and therefore postoperative complications such as pneumonia or prolonged hospitalization. There are several guidelines available, such as the American pain society ISSUE 02 - 2023

or the American society of anesthesiologists. They suggest a wide arrange of drugs and procedures such as regional nerve blocks to manage the pain in postoperative patients. After surgery, up to 75% of the patients suffer from acute postoperative pain of a medium to high intensity. More than 50% of those patients report an inadequate pain relief in the treatment of the pain. These patients are at risk of developing a chronical pain syndrome associated with surgery. Up to 10% of the patients undergoing surgery suffer from severe persistent postoperative pain, which is verry difficult to treat.

Anatomy and Physiology There are afferent nerves that mediate the pain sensation towards the central nervous system. Postoperative pain can be categorized as nociceptive, inflammatory, or neuropathic pain, all meditated by a different kind of neural pathways. Neuropathic pain is getting mediated by activated unmyelinated C-fibers, thinly myelinated A-delta-fibers, and myelinated A-beta-fibers. It occurs as a result of a noxious stimuli such as tissue damage performed for example by the incision of the skin during the operation. Inflammatory pain occurs when nociceptive nerval fibers get sensitized in the response to the release of inflammatory mediators such as cytokines. This is usually associated with the clinical signs of inflammation, as there would be clinical evidence of heat, pain, erythema and swelling in or near the operation field. The pain sensation

can last from several hours to days and usually improves when the inflammation is gone. Usually, there will be no persisting pain as a result of an inflammation. Neuropathic pain is the result of an injury of the nerval structure, which leads to an increased axonal sensitivity to stimuli of the peripheral nerve. This kind of pain will manifest shortly after surgery and has the potential to persist as chronic postoperative pain over several months and in worst case even longer. In addition to the categorization above postoperative pain is also characterized as somatic or visceral. Somatic pain is the input of nociceptive myelinated, rapidly conducting fibers found in cutaneous and deep tissue, which contribute to a more localized, sharp quality of pain. The category of visceral pain is conducted over a neuronal network of fibers that spreads across multiple viscera and combines before entering the spinal cord in the dorsal root. There are also connecting fibers towards the autonomous nerval system. This is why the visceral pain is not only more diffuse and not clearly localizable pain, but also it can also be accompanied by autonomic reactions such as alternating blood pressure or influencing the heart rate of the patient. The aim of different therapeutic intervention is to target these afferent structures in various ways. Antagonizing pain receptor activity, blocking the production of pro-inflammatory mediators or simply blocking the afferent nerve are only a few ways to improve postoperative pain management. w w w. e u r o p e a n h h m . c o m

Measuring the pain

Systematic overview

In general, it is verry difficult to measure pain, because there are nearly none objective measurements available. There are several individual factors that can influence the pain in patients, such as age, gender, social background, etc. In the time of migration there are sometimes a lot of problems in communicating with the patients, making it difficult for patients and the medical stuff to evaluate the pain. There are several scales available for quantizing pain, many of those require communication. Widely used therefore is the Visual Analog Scales (VAS) and the numerical rating scales (NRS).

In 2012 the American Society of Anesthesiologists (ASA) published a guideline for acute postoperative pain management, which was approved by the American Society of Regional Anesthesia and Pain Medicine. There are several pre-, inter- and postsurgical interventions and management strategies are available to reduce the postoperative pain of the patients.

Fig.1: VAS for evaluation of pain

Fig. 2: NRS for measuring the pain

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Systemic pharmacologic therapy The systemic application of opioids, NSAID (non-steroidal anti-inflammatory drugs), acetaminophen, gabapentin, ketamine or

lidocaine or many other substances is widely used in pain management. Oral application of opioids is preferable to the intravenous route. Nevertheless, there are situations, where oral medication is not the way to go. Extreme pain or non-ability to digest the medication during an Ileus or other circumstances could lead to the fact, that oral medication cannot be applied. In that case, the intravenous route has to be chosen and therefore the ASA recommends the form of patient-controlled anesthesia in those patients.

Local, Intra-articular, or topical techniques That kind of site-specific pain control is not in wide use. They could be considered individually but there is no general recommendation for these procedures.

Regional anesthetic techniques A local anesthetic with or without the addition of IV opioid medication is an option for fascial plane block, site-specific regional anesthetic injections, or in some cases epidural injections depending on the type of procedure performed. These procedures are usually performed under ultrasound guidance. The use of continuous medication IV for general pain control is preferable to singleinjection techniques in cases where the duration of postoperative pain is prolonged. Intrapleural analgesia is not recommended for pain control as there is little evidence to suggest benefit, and high systemic absorption within the pleural space increases the risk of drug toxicity.

Neuraxial anesthetic techniques The Injection of local anesthetics into the epidural space is often performed in modern surgery. The addition of IV opioid is optional. It can be applied through continuous infusion or also as patient controlled anesthesia, doselimitation is then mandatory. These techniques are widely used in thoracic surgery, extended abdominal procedures as well as Operations on hips and lower extremities. It is also performed in section caesarian, because there is verry little additional necessary and therefore the child is hardly affected. Nonpharmacologic therapies- ex, cognitive modalities, physical therapy, transcutaneous electrical nerve stimulation (TENS) In general, additional physiotherapy as well as cognitive modalities are an addition to pharmaceutical or other modalities of pain control. Some of these modalities can start before the operation and is performed in some centers.

Surgical techniques In recent past not only the anesthesiologic and pharmacological pain management improved, but also the surgical procedures improved a lot when it comes to postoperative pain. The evolution of laparoscopic and thoracoscopic surgery led to less traumatizing procedures because there are less inflammatory mediators released. Therefore, less pain is developed and the pain management is better than in w w w. e u r o p e a n h h m . c o m

open and conventional surgery. The rise of the robotic surgery in recent years also shows the benefit of less invasive procedures providing and enabling the surgent to perform even more complex resections than by other minimal invasive modalities. With the development of newer robot generations and the broader use of those equipment all over the world the experience within the sergeants will grow and more and more complex operations will be performed by this technique.

Clinical view There are several factors, that have to be considered when planning the postoperative management of a patient. Besides the factors of the planed procedure there are several individual factors, that have to be considered. These include patient age, history of chronic opioid use, and other comorbidities 62

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Especially obese patients are challenging patients regarding to the use of opioids because they easily develop respiratory deficiency or sleep apnea. Patients suffering from chronical pain syndrome often require huge amounts of analgesia exceeding their baseline dose. Interventional anesthetic techniques and non-opioid pain management is verry important in these patients. To be taken into consideration is also the possible misuse of opioids. A pre-existing history of depression or misuse of other substances as well as other risk factors have to be considered when planning on pain management. Inadequate pain management has severe impact on the patient’s health, including the ability to manage their daily life. Often there are sleeping disorders, reduction of libido, and

Conclusion Pain management is one of the big tasks to be achieved after surgery, esp. after big resections and thoracic surgery. Less pain in patients lead to a faster recovery and less chance of persisting postoperative pain in the long term. It reduces the days in the hospital and the patient will be able to start his daily routine as early as possible. It is in the best interest of the anesthesiologist, the surgeon and all other participating specialties like the nursing stuff to monitor and manage the pain of postoperative patients to reduce complications in the long run. References are available at www.europeanhhm.com

AUTHOR BIO

mood disorders. There is also a higher probability of developing a chronic pain syndrome with initially poor pain management. The risk in taking opioids show in somnolence, sedation, respiratory depression, urinary retention, nausea/vomiting, ileus, which could lead to death. There is, as already mentioned, the possibility of addiction and substant use disorder and severe withdrawal symptoms when getting of the medication. There is a bleeding risk in the use of NSAID, which has to be considered in operations, where a big blood loss is to be expected. There is also an increased risk in gastrointestinal bleeding and renal dysfunction. Peripheral nerval blocks may result in motor blockade of depended muscles, increasing the morbidity and severely reducing the mobilization of the patient. In neuraxial anesthesia, patients require close monitoring as respiratory depression, hypotension, and motor weakness from spinal cord compression may occur. These are severe complications requiring acute intervention if they occur.

ERAS-Concept Enhanced recovery after surgery (ERAS) are specially designed multimodal perioperative care pathways with the purpose of earliest possible mobilization and to get the patients back to their daily routine as soon as possible. In the ERAS-Concept, pain management is key to early mobilization of the patient as well as the preoperative preserving of organic function and reducing the stress response after surgical trauma.

Dr. Paul Swatek did his degree at the medical university of Graz, where he also specialized in thoracic surgery. After several years as a consultant, he took over the department of thoracic surgery at the Klinikum Ingolstadt/Germany. He is specialized in oncological resections and in minimal invasive thoracic surgery with uniportal approach. Today he is working at the medical university of Graz again to examine and develop new approaches on thoracic surgery.

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Transforming Healthcare with AI A Cardiac Surgical Perspective

Artificial Intelligence (AI) is poised to revolutionize healthcare like never before. It has the potential to bring about unprecedented innovations in medical care with accelerated progress. In the field of cardiac surgery, AI is being increasingly utilised to enhance surgical care through technological remodeling and cognitive augmentation. With more robust infrastructures and information technology wings, automation and machine learning are bound to metamorphose clinical care and healthcare administration by eliminating human errors, time constraints, manpower shortages, and financial hindrances. This article provides an overview of the various applications of AI in cardiac surgery and its astounding impact.

Anitha Chandrasekhar MSc, DMSc, FIECMO, FAPACVS Clinical Lead- Lung Bioengineering & Organ Procurement, Northwestern Memorial Hospital

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ith a technological revolution engulfing the world in all domains, the healthcare sector has slowly, steadily, concretely and compellingly joined the bandwagon. Cardiac surgery is a high-risk, high-octane, resource-intensive, sophisticated speciality that requires exceptional

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surgical prowess and astute cognitive skills. AI has been effectively incorporated into cardiac surgery to facilitate dynamic clinical decisions through innovative risk stratification tools. AI has significantly impacted areas such as disease prevention/well-being, early detection, diagnosis, surgical decisionmaking, surgical techniques, prognosis, research, and chronic care management, contributing to enhanced and efficient patient care. AI, as the name indicates, refers to the intellectual capacity that is artificially created for machines to learn from crowd sourced data sets that can be processed at incredibly rapid times to provide lightning-fast inferences. It is the science of making machines simulate human intelligence to enable problem-solving by recognising patterns for decision-making, thereby reducing the margin for error.

Early Detection AI in Cardial Surgery Diagnosis & Prognosis

Surgical Techniques Surgical Decision Making

Heart failure (HF) is a deadly dangerous disease with high morbidity and mortality, making it one of Europe's leading causes of death. Preventive care is essential to help patients circumvent the onset of illness, slow disease progression, and reduce the chance of developing severe complications. AI is reshaping the way heart failure is anticipated and prevented. AI-driven preventive care has the potential to extend life expectancy and improve the well-being of patients with chronic conditions like diabetes and hypertension, which are significant risk factors for heart disease. AI algorithms improve clinicians' comprehension, judgment, and decision-making for each patient. Predictive and prescriptive analytics strengthen disease prevention and support positive outcomes.

Early detection

Disease Prevention Chronic Care

Disease prevention

AI has a vital application in the early detection of heart diseases. In the terminal stages of HF, when biventricular dysfunction sets in, a patient may quickly progress to kidney, liver, and sometimes neurological dysfunction due to low cardiac output, ultimately leading to multi-organ failure. AI is increasingly being employed by clinicians to diagnose HF early, enabling the prompt initiation of treatment. Abnormal heart sounds and murmurs are classical features of heart disease. However, identifying them is highly subjective and depends on the clinician’s w w w. e u r o p e a n h h m . c o m

level of experience and expertise. A novel HF screening framework based on the Gated Recurrent Unit (GRU) has been developed by Chinese researchers. The GRU model is a deep learning model that can acquire features of heart sounds directly, process signals, and generate inferences on HF. It is a promising tool for non-invasive screening of HF and is paving the way for early detection of coronary collapse. In another advancement, physicianscientists from Northwestern Medicine, have developed an algorithm feeding in signs that can detect early HF. the algorithm runs through the hospital-registered patient database to pick up these signs from their laboratory tests or physician notes during their visit, thus identifying potential HF patients. Based on the flags from this computer model, the patient is contacted and evaluated for HF. The hospital reports that out of 2500 patients that were recognised and reached out, 500 patients have been diagnosed with HF with the use of AI and initiated treatment. This model has helped identify candidates for heart transplantation and enrol patients in advanced therapies through clinical trials, thus improving their quality of life and longevity. Due to the potential sensitivity of AI tests in detecting disease early and providing deep phenotypes, it may appear to predict future diseases by creating a class of ‘previvors’ who have not yet experienced a disease.

Diagnosis An electrocardiogram (ECG) is a standard, 66

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ubiquitous test used in clinical workflows for a long time and is widely available for the diagnosis of heart disease. However, with the emergence of AI ECG, the diagnosis of heart disease has been revolutionized. With the help of massive labelled datasets, complex neural networks have been created to uncover subtle patterns in ECGs that even expert ECG interpreters may have missed. These neural networks bring new diagnostic power and value to the ECG to identify low ejection fraction of the heart, propensity for atrial fibrillation, hypertrophic cardiomyopathy, hyperkalemia, medical comorbidity/frailty, age, sex, markers of valvular heart disease, amyloidosis, etc. FDA approval has been granted to AI-based tools for rhythm detection. The ‘EAGLE’ trial, a large cluster design pragmatic trial, is currently underway at the Mayo Clinic to evaluate the effectiveness of 12-lead ECG in identifying left ventricular dysfunction, which is asymptomatically present in 3% to 9% of the general population. The AI ECG has also been embedded into a stethoscope form with embedded electrodes, by Texas Heart Institute clinicians, to record ECGs during routine clinical examination. Additionally, it can be used to monitor patients at risk of ventricular dysfunction, such as those undergoing chemotherapy or heart transplant patients, in the comfort of their homes at a lower cost. The use of AI in Echocardiography, a crucial diagnostic tool for heart failure, has led to the

development of convolutional neural networks that can determine ejection fraction and longitudinal strain. These networks can also detect pulmonary arterial hypertension, cardiac amyloidosis, and hypertrophic cardiomyopathy.

Surgical decision making AI is incredibly helpful in surgical decisionmaking, providing explicit predictive models and risk assessment tools created by collating information from diverse sources about patient risk factors, anatomical features, natural history of the disease, patient values, and costs. AI-enhanced risk assessment models have proved to be more accurate than any surgical risk score predictor. Ex Vivo Lung Perfusion (EVLP) is a cutting-edge technology in lung transplantation that involves continuous machine perfusion of marginal donor lungs after procurement, to optimize and test functionality before implanting them into the recipient. Clinician-scientists at Toronto have used AI in developing an Extreme Gradient Boosting model (XGBoost), named InsighTX, which has been constructed from donor features along with biological, physiological, and biochemical parameters assessed during EVLP. The InsighTX model, with a machine learning approach, has proven to be accurate in predicting lungs unsuitable for transplantation after an EVLP run. This is an excellent aid in clinical decisionmaking for thoracic surgeons using the EVLP technology. Another centre has created

a convolutional neural network that pools thousands of chest radiographs from EVLP lungs. For every neural network, a standard model was adapted to detect atypical findings on the chest radiograph such as atelectasis, infiltration, consolidation, interstitial lines, nodules etc. This automates EVLP radiograph image processing with accurate analysis. Advancements in Magnetic Resonance Imaging (MRI) technology, powered by AI, are having a groundbreaking impact on surgical decision-making for complex cardiac conditions. By uploading MRI scan images into Virtual Reality (VR) software, precision VR images can be generated to help in unparalleled surgical planning. The MRI-VR technique provides surgeons with additional insight and enables a more effective game plan, including a 3-D trial surgery, before beginning a complex invasive procedure.

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Surgical techniques The impact of AI on surgical techniques has been transformative. Robotic heart surgery and robotic-assisted thoracic surgery are now commonplace. Surgeons use a computerenhanced robotic system to perform surgery through minimal access. The surgeon typically sits in a console, similar to a video game, and controls surgical instruments attached to robotic arms that mimic the human hand, wrist, and finger movement. This increases the range and precision of movements. From coronary bypass surgery, valve repair and replacement, closure of holes in the heart to cardiac mass, lung cancer, and mediastinal tumour removal are being performed robotically. In such complex surgical procedures, AI leveraging machine learning, computer vision, and robotics can significantly help surgeons perform intricate surgeries with greater success, lesser complications, and upholding patient safety.

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Interestingly, AI has also improved surgical training simulators that can assess the participant’s performance and offer customized feedback to enhance and refine surgical skills.

Prognosis Prognosticating outcomes is an important aspect of cardio-thoracic surgery, to weigh the pros and cons, the risks and benefits for better judgement and informed decision making. End-stage HF patients may often decompensate while on the wait list for a suitable donor heart and may require a form of mechanical circulatory support to sustain life till the time an organ becomes available. There are various options available but the kind of support and its outcome is often unpredictable and depends on multiple factors. Researchers in Switzerland have effectively used AI in developing an interpretable machine learning model based on a large

clinical database that can effectively predict one-year mortality in patients with temporary mechanical circulatory support as a bridge to cardiac transplantation. Another gradientboosted classification algorithm model (GBM) developed by scientists at Mayo Clinic, helps in accurately predicting graft failure and five-year mortality after orthotropic heart transplantation. Machine learning has also been proven effective in projecting one-year mortality after heart and lung transplantation.

Long term care Another pioneering application of AI is in chronic care management, which plays a crucial role in determining the outcome and quality of life of the sick subset of patients undergoing heart and lung transplantation. One of the most common complications posttransplant is rejection. Physician-scientists in Boston successfully integrated AI into a novel deep-learning model to detect Acute Cellular Rejection in heart and lung transplant biopsies. With digital pathology and AI technology, the machine learning algorithm can differentiate the vascular component of rejection in transplant biopsies from normal tissue and thus can detect, classify and grade transplant rejections. AI has also been used to predict post-heart transplant graft function, re-hospitalisation, re-transplantation, graft survival, cardiac allograft vasculopathy, and model blood levels of immunosuppressive medications. The care of heart failure patients needs a paradigm shift from reactive to predictive,

preventive and personalized care. Active participation of patients in their care processes is mandatory to reduce the burden of HF on healthcare labour and costs. PASSION-HF consortium (PAtient Self-care uSing eHealth In chrONic Heart Failure) is a collaborative initiative by physician-researchers in the Netherlands and the UK. They use AI to develop a ‘virtual doctor’ at home for self-care using digital therapeutics. This virtual doctor will follow HF guidelines, consider patient co-morbidities, and ensure safe prescribing and handling of medications. It will include an AI-powered decision support engine, an interactive physician avatar interface, serious gaming tools, a self-learning feedback system, and patient coaching.

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Research AI and machine learning also hold the promise of positively impacting research, drug discovery and development, as researched by Indian scientists. They can enable leveraging human datasets leading to a better understanding of target biology. AI can use real-world human data to generate new insights and translate them into potential therapeutics for the benefit of patients suffering from cardio-metabolic conditions.

unprecedented levels of data analysis and pattern recognition, thus minimising errors, the depth, empathy and nuanced understanding that come with human interactions are irreplaceable. AI cannot replace but complement and enhance human intelligence to an extent never conceived before. References are available at www.europeanhhm.com

A new robot named Moxi is unpretentiously traversing through the hallways of Northwestern Memorial Hospital! Moxi is designed to deliver items such as laboratory specimens and medications between the lab, pharmacy and floor. It also helps with the stocking of medication and supplies. The hospital believes that automating these tasks will help free up time for Laboratory services and Pharmacy team members to better focus on tasks that they are licensed to perform. Moxi uses an AI system to navigate its way through the hospital and also has a robotic arm to perform tasks such as pressing elevator buttons. In conclusion, AI is undeniably reshaping the healthcare landscape by refining clinical practice for better patient outcomes. And it isn’t about the future, it’s the direction the healthcare is headed right now. However, there are numerous challenges in the implementation of AI in healthcare such as accessibility, equity, cost and resource allocation, validation, regulation, and ethical dilemmas. While AI can provide 70

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AUTHOR BIO

Hospital applications

Dr. Anitha Chandrasekhar is a Cardiothoracic surgical professional with over two decades of involvement in cardiac surgeries including the entire spectrum of congenital, coronary, valvular, aortic, heart and lung transplantation and ventricular assist device implantation procedures. She has presented scientific papers extensively in national and international surgical conferences and published many articles in indexed journals. She has held multiple leadership positions in various associations and has carved a unique pathway in the cardiac surgical domain. As a passionate ‘Surgical Scientist’, she is currently serving as Clinical Lead- Lung Bioengineering and Organ Procurement at Northwestern Medicine, Chicago, IL, USA.

THE FUTURE OF QUALITY AND PATIENT SAFETY IN HEALTHCARE Sony Prabowo Acting Hospital Director Ciputra Mitra Hospital

The future of quality and patient safety in healthcare is expected to see significant advancements and innovations as healthcare systems worldwide continue to evolve. Here are some key trends and developments: Artificial Intelligence and Machine Learning Genomic Medicine Telehealth and Remote Monitoring Patient Safety Technologies Interoperability Human-Centered Design Patient Engagement Patient Safety Culture Quality Metrics and Transparency Workforce Development Global Collaboration Regulatory Changes In summary, the future of quality and patient safety in healthcare will be marked by technological advancements, increased patient engagement, regulatory enhancements, and a continued cultural shift towards prioritizing safety.

uality and patient safety have always been paramount in healthcare. As technology, research, and healthcare delivery methods evolve, the future of quality and patient safety holds great promise and presents unique challenges. This article explores the future landscape of quality and patient safety in healthcare, examining emerging trends, technologies, and strategies that will shape the way healthcare organizations deliver safe and high-quality care to their patients. w w w. e u r o p e a n h h m . c o m

I. The Evolving Concept of Quality and Patient Safety A. Definition and Significance: Quality in healthcare refers to the degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge. On the other hand, patient safety is the avoidance, prevention, and amelioration of adverse outcomes or injuries arising from healthcare processes.

B. Patient-Centered Care: Patient-centered care is a fundamental approach to healthcare that places the patient at the center of the care process. It recognizes that patients are unique individuals with their own preferences, values, and needs, and it aims to tailor healthcare services to meet those individual requirements. This approach prioritizes patients' preferences, values, and needs, involving them in decision-making processes and care planning. Key principles and components of patient-centered care include: 1. Respect for Patients' Preferences and Values: Patient-centered care starts with acknowledging and respecting the preferences, values, and goals of each patient. It involves actively listening to patients, involving them in decisionmaking, and considering their opinions when developing care plans. 2. Shared Decision-Making: Healthcare providers and patients work collaboratively 72

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to make decisions about treatment options, taking into account the patient's medical condition, values, and preferences. This shared decision-making process empowers patients to be active participants in their healthcare. 3. Holistic Approach: Patient-centered care recognizes that health and wellbeing are influenced by various factors, including physical, mental, emotional, and social aspects of a person's life. It takes a comprehensive and holistic approach to care that goes beyond just addressing physical symptoms. 4. Individualized Care Plans: Instead of using a one-size-fits-all approach, patientcentered care involves tailoring treatment plans and interventions to each patient's unique needs. This may involve considering cultural, religious, or personal factors that impact the patient's health. 5.Clear Communication: Effective communication is essential in patientcentered care. Healthcare providers must convey information in a clear, understandable manner and encourage patients to ask questions and express their concerns. 6. Emphasis on Prevention and Health Promotion: Patient-centered care places a strong focus on preventive care and health promotion. It encourages patients to take an active role in maintaining their health through lifestyle changes, screenings, and vaccinations. 7. Continuity of Care: Patients benefit

from having a consistent and coordinated healthcare team that communicates and collaborates effectively. This ensures that patients receive seamless care across different healthcare settings and providers. 8. Feedback and Evaluation: Patient feedback is valued in patient-centered care. Healthcare organizations seek input from patients to continually improve their services and make necessary adjustments. 9. Cultural Competence: Healthcare providers should be culturally competent, meaning they are sensitive to the cultural backgrounds, beliefs, and practices of diverse patient populations. Cultural competence helps ensure that care is respectful and responsive to the unique needs of each patient. 10.Measurement of Patient Experience and Outcomes: Healthcare organizations use patient-reported outcome measures and patient experience surveys to assess the quality of care and identify areas for improvement. Patient-centered care has gained widespread recognition as a cornerstone of high-quality healthcare. It has been associated with improved patient satisfaction, adherence to treatment plans, better clinical outcomes, and increased trust between patients and healthcare providers. As the healthcare landscape continues to evolve, patient-centered care remains a crucial approach for delivering care that meets the needs and expectations of patients while promoting their well-being

C. Holistic Approach: A holistic approach in healthcare is an approach that considers the whole person, including their physical, mental, emotional, and social wellbeing, rather than just focusing on specific symptoms or diseases. It recognizes that all aspects of a person's life are interconnected and can impact their overall health and wellbeing. Some key elements and principles of a holistic approach in healthcare are Mind-Body Connection, Individualized Care, Preventive Care, Patient-Centered Care, Complementary and Alternative Therapies, Nutrition and Diet, Emotional and Spiritual Well-Being, Collaborative Care, Environmental Considerations, Cultural Sensitivity, Long-Term Well-Being, Education and Empowerment.

II. Emerging Trends Shaping the Future A. Data-Driven Healthcare 1. Big Data Analytics The vast amount of healthcare data generated daily, from electronic health records (EHRs) to wearable devices and medical imaging, has the potential to revolutionize patient care, research, and healthcare management. Big data analytics in healthcare refers to the use of advanced data analysis techniques to process and derive insights from large and complex healthcare datasets. These datasets typically include a wide range of information, such as patient records, clinical notes, medical images, and genomic data. Big data analytics w w w. e u r o p e a n h h m . c o m

leverages various technologies, including machine learning, artificial intelligence, and statistical analysis, to extract valuable knowledge from this data. Benefits of Big Data Analytics in Healthcare are improved Diagnosis and Treatment, Enhanced Patient Care through Predictive Analytics and Preventative Care, Operational Efficiency, Research and Development for Drug Discovery and Clinical Trials, and Population Health Management such as Identifying Health Trends and Disease Surveillance 2. Artificial Intelligence (AI) Artificial Intelligence (AI) is revolutionizing the healthcare industry in unprecedented ways. It is rapidly transforming the diagnosis, treatment, and management of medical conditions, enhancing patient care, and improving healthcare operations. 74

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Artificial Intelligence in healthcare involves the development and application of AI technologies, including machine learning, deep learning, natural language processing, and computer vision, to healthcare-related tasks. These technologies enable machines to analyze vast amounts of healthcare data, make predictions, and assist healthcare professionals in decision-making processes. Some applications of AI in Healthcare are: a. Medical Imaging: * Radiology: AI can analyze medical images (X-rays, MRIs, CT scans) to assist radiologists in detecting abnormalities, tumors, and fractures with greater accuracy. * Pathology: AI helps pathologists in identifying cancerous cells and other abnormalities in tissue samples. b. Disease Diagnosis and Risk Prediction: * Early Diagnosis: AI algorithms can identify

early signs of diseases like cancer, diabetes, and cardiovascular conditions by analyzing patient data. * Risk Assessment: Predictive models can assess a patient's risk of developing certain diseases, enabling preventive measures. c. Drug Discovery and Development: AI accelerates drug discovery by analyzing molecular data, predicting drug interactions, and identifying potential candidates for drug development. AI helps in identifying suitable candidates for clinical trials, improving the efficiency of drug testing. d. Electronic Health Records (EHRs): AI enhances EHR management by automating data entry, coding, and documentation, reducing administrative burdens on healthcare professionals. Clinical decision support systems use AI to provide real-time insights and recommendations based on patient data. e. Remote Patient Monitoring and Telehealth: AI-powered wearable devices and sensors monitor patients' vital signs and send alerts to healthcare providers if anomalies are detected.Telehealth platforms use AI for triage, diagnosis, and follow-up care, extending healthcare access to remote areas. f. Personalized Medicine: AI analyzes genetic, clinical, and lifestyle data to tailor treatment plans and medication dosages to individual patients. Pharmacogenomics uses AI to predict a patient's response to specific drugs based on their genetic makeup. Benefits of AI in Healthcare are Improved Accuracy and Efficiency by reducing human

errors in diagnosis and treatment planning, Enhanced Diagnosis and Early Detection, Cost Reduction, Patient-Centered Care, Research Advancements. Artificial Intelligence is poised to revolutionize healthcare by improving diagnosis accuracy, treatment personalization, and operational efficiency. The continued development and responsible integration of AI technologies promise a future where healthcare is more accessible, efficient, and patient-centered.

B. Telehealth and Remote Monitoring: Telehealth and remote monitoring have revolutionized healthcare by making it more accessible, convenient, and effective. As technology continues to advance and regulatory frameworks adapt, these approaches are likely to become even more integral to the healthcare system, offering patients and providers new opportunities for improved care and better health outcomes. Telehealth refers to the use of electronic information and telecommunication technologies to provide healthcare services remotely. It encompasses a wide range of services, including medical consultations, therapy sessions, and education, delivered through videoconferencing, phone calls, or secure messaging. The Benefits of telehealth are Accessibility, Convenience, and Reduced Exposure. Remote patient monitoring involves the use of technology to track and monitor a w w w. e u r o p e a n h h m . c o m

patient’s health data and vital signs outside of a traditional healthcare setting. This can include wearable devices, sensors, and smartphone apps. The benefits such as Continuous Monitoring, Chronic Disease Management, Improved Outcomes, reduced hospital readmissions.

C. Interoperability: Interoperability in healthcare refers to the ability of different healthcare systems, software applications, and devices to seamlessly exchange and use patient information and data in a standardized and coordinated manner. Interoperability in healthcare is an ongoing effort aimed at improving the quality of care, enhancing patient outcomes, and reducing healthcare costs by enabling seamless data exchange and collaboration across the

healthcare ecosystem. As technology and standards continue to evolve, achieving greater interoperability remains a central goal in modern healthcare. Some key aspects of interoperability in healthcare are Data Standardization, Electronic Health Records (EHRs) that allow exchange patient data across different healthcare organizations and systems, Clinical Decision Support, Health Information Exchange (HIE) that facilitate the sharing of patient data among healthcare organizations, Patient Portals, Medical Devices that is connected to EHR systems and share real-time patient data, Telehealth and Remote Monitoring, Pharmacy and Medication Management, Patient Identifiers.

III. Strategies for Ensuring Quality and Patient Safety A. Continuous Quality Improvement (CQI) Continuous Quality Improvement (CQI) is a systematic and ongoing process used by organizations to identify, measure, analyze, and improve their products, services, processes, and overall performance. The primary goal of CQI is to enhance the quality of products or services and increase customer satisfaction while also optimizing organizational efficiency and effectiveness.

B. Standardization and Guidelines Standardization and guidelines play a crucial role in ensuring quality and patient safety in 76

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healthcare settings. They provide a structured framework for healthcare providers to deliver consistent, evidence-based care, reducing the risk of errors, improving patient outcomes, and enhancing overall healthcare quality. Healthcare organizations should regularly update and educate their staff on guidelines and standards to ensure they are aligned with the latest best practices in the field.

C. Patient Engagement Patient engagement is becoming increasingly important in the future. It involves actively involving patients in their care, decisionmaking processes, and the management of their health. The future of patient engagement in these areas holds several key developments and trends such as Shared Decision-Making, Digital Health Tools, Telehealth and Remote Monitoring, Health Literacy and Education, Patient-Reported Outcomes (PROs) which are measurements of patients' perceptions of their health and quality of life, Patient Safety Reporting, Cultural Competency, Quality Metrics and Transparency, Patient Advocacy, Regulatory Emphasis. Empowered and informed patients can actively contribute to their own safety and the overall quality of care. Healthcare providers and organizations are adapting to this changing landscape by integrating patient engagement strategies into their practices and systems, ultimately leading to improved patient outcomes and safer care delivery.

D. Education and Training Education and training play a pivotal role in shaping the future of healthcare by ensuring that healthcare professionals have the knowledge, skills, and tools necessary to provide safe and high-quality care. Healthcare organizations, educational institutions, and regulatory bodies must collaborate to ensure that healthcare professionals are equipped with the knowledge and skills needed to meet the evolving challenges and opportunities in healthcare delivery. Here are some key aspects of education and training: Advanced Curriculum Integration, Interdisciplinary Training that encourage interdisciplinary teamwork and communication skills to improve coordination and reduce errors, Simulation-Based Training, Continuous Learning, Quality Improvement Projects, Leadership Development, Ethical Considerations, Digital Health and Health Information Technology, Patient-Centered Care, Global Perspectives.

IV. The Role of Policy and Regulation A. Regulatory Bodies Regulatory bodies play a critical role in ensuring quality and patient safety in healthcare. These organizations establish and enforce standards, guidelines, and regulations to promote high-quality care, protect patients, and hold healthcare providers and facilities accountable. w w w. e u r o p e a n h h m . c o m

technologies, and foster a culture of continuous improvement to excel in this value-driven landscape.

Conclusion

B. Value-Based Care Value-based care is a healthcare delivery model that focuses on delivering high-quality care while controlling costs. It emphasizes achieving better patient outcomes and patient satisfaction rather than the volume of services provided. In the future, value-based care is likely to continue evolving and expanding as a dominant model in healthcare. As this transition occurs, there will be an increased focus on patient safety and quality, driven by the model's fundamental principles of achieving better outcomes while controlling costs. Healthcare organizations will need to adapt, invest in 78

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AUTHOR BIO

The future of regulatory bodies will involve adapting to technological advancements, promoting patient-centered care, addressing healthcare disparities, and ensuring that healthcare systems remain responsive to emerging challenges and opportunities. These bodies will continue to evolve to meet the changing needs of healthcare systems and the populations they serve.

The future of quality and patient safety in healthcare is a dynamic and evolving landscape shaped by emerging trends, technologies, and challenges. Achieving the highest standards of care and ensuring patient safety will require a concerted effort from healthcare organizations, policymakers, and healthcare professionals. By embracing innovation, datadriven approaches, and person-centered care, the healthcare industry can work towards a future where every patient receives safe and high-quality care, regardless of their background or circumstances.

Dr. Sony Prabowo is currently an Acting Hospital Director at Ciputra Mitra Hospital in Indonesia.He took Pediatric residency at Davao Doctors Hospital - Philippine and obtained his Master of Hospital Administration from Esa Unggul University – Indonesia. In addition to his academic career, Dr Sony is the author of several health-related books in Indonesia.

Impact on the Workforce with AI in Healthcare

Many healthcare professionals view the advent of AI with considerable concern and a fair measure of trepidation. For virtually everyone, their worries are misplaced because AI is a tool that will make their jobs easier and more personally and professionally rewarding. Here are some prime examples. James Doulgeris Chairman Population Health Advisory Board RSDSA

rtificial intelligence has been incorporating itself into healthcare for years. Equipment gets smarter and more capable. Systems become easier to use and more intuitive. Routine tasks that used to be done by people are now routinely done by EMR and other integrated systems. Only recently has the spectra of AI become worrisome as its role has accelerated enough to become w w w. e u r o p e a n h h m . c o m

noticeable. Nonetheless, AI is still a tool that will make our jobs easier and more personally and professionally rewarding. While time will tell where things go, at present, AI is here to augment, not replace, humans and these are exciting times. While the threat of our computer overlords remains stuff of science fiction, here is a fact based look at how AI is impacting the healthcare workforce in some critical ways:

Revolutionizing Primary and Specialty Care The largest immediate impact by far is at the primary care level where most chronic and rare disease is identified and treated. Early diagnosis and focused treatment is the key to improving health status and mitigating long term impact of chronic conditions. There is a long list of routine administrative tasks that are being assumed by AI at the point of care allowing primary care providers to focus their attention on their patients instead of electronic medical record systems. Chronic conditions represent over three quarters of the cost of care under the age of 65 and over 95 percent of the cost over the age of 65. Rare diseases, of which there are about 7,000, are often less rare than rarely diagnosed before it is too late to treat them effectively. The first operating entity in this area is Navina, which uses a novel AI to sift through EMR data including handwritten notes and disparate data such as specialist, laboratory

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and imaging reports to create an organized, one-page clinical summary for clinicians prior to each visit. This summary saves up to 25 percent of the time spent on EMR focus for each visit. Further, the company is exploring a partnership with a non-profit rare disease support group to identify potential patients using its platform that can save patients a lifetime of misery. Once identified, the system can direct physicians on proper diagnosis, treatment, and support of this and prospectively many other rare diseases. AI is already on its way to revolutionizing primary care by relieving it of the following administrative burdens, further freeing clinicians to focus on patient care and to practice at the top of their licenses:

1. Data Entry and Documentation: Natural Language Processing (NLP) systems can transcribe spoken words into text or extract information from medical records.

2. Appointment Scheduling: Chatbots and other automated scheduling systems can handle appointment bookings and reminders. Patients can schedule appointments online or through automated phone systems, reducing the need for staff to manage appointment logistics.

3. Medical Coding: Automatic assignment and recommendation of

diagnostic and procedural codes allows medical coders to focus on high level issues instead of low-level clerical duties while reducing human error.

4. Billing and Claims Processing Automating the billing process by generating invoices, verifying insurance information, and processing claims ensures timely and accurate billing, reducing administrative overhead, human error and enhancing cash flow.

5. Patient Communication: Communication tools can send automated follow-up messages, appointment reminders, and educational materials to patients, improving patient engagement and reducing workload.

6. Transcription Services: Voice to text transcription allows medical records to be updated and shared with the patient at the point of care. Patient privacy and security regulations must be updated to ensure these enhanced capabilities protect patient rights to confidentiality.

Data Driven Clinical Decision Support AI is on the verge of revolutionizing clinical decision support by providing healthcare professionals with data-driven recommendations and best practices insights to augment clinical decision-making in ten critical areas. Overall, these advances will allow physicians and other

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clinicians to focus their practices at the top of their licenses and to do more with less support staff. The net effect will be a more streamlined, efficient system of higher qualified and trained people:

1. Diagnosis and Risk Assessment: New AI systems integrated into EMR platforms promise to analyze patient data that includes medical history, symptoms, and test results, to assist healthcare providers in diagnosing diseases and relative risk management using population health database driven comparisons. These comparisons can identify patterns and correlations indicating early onset of disease including rare diseases. Early diagnosis is key to the most effective and successful treatment.

2. Medical Imaging Analysis: AI-powered image recognition and analysis can help radiologists and pathologists interpret medical images more accurately by detecting anomalies in X-rays, MRIs, CT scans, and pathology slides that are not visible to the human eye.

and current health status, healthcare providers can make more informed decisions about the most appropriate treatments and therapies.

4. Clinical Pathways and Guidelines: Consistency in adhering to clinical guidelines and best practices is a challenge at the practice and healthcare system level. By providing realtime guidance to clinicians. AI can suggest appropriate tests and interventions based on a patient's condition consistent with the most current evidence-based medicine.

5. Patient Monitoring: Just because we can now collect volumes of clinical data does not mean that healthcare providers can consume it. AI-driven predictive analytics can continuously monitor patients and identify subtle changes in vital signs or health parameters eliminating the need to absorb oftentimes overwhelming amounts of clinical data. This enables early intervention when deterioration is detected, improving patient outcomes.

6. Genomic Medicine: 3. Pharmacogenomics, or Precision Medicine: Using AI to compare a patient’s genetic profile to identify genetic variations that influence a patient’s ability to metabolize, absorb, and respond to a medication to tailor drug therapy to their unique genetic profile optimizes treatment outcomes and to reduces the risk of side effects. Combined with the patient’s medical history 82

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When genomic data is available AI can compare them with a large database to identify genetic markers associated with diseases to, combined with health and diagnostic status, guide personalized treatment decisions.

7. Population Health Management: Population health analytics without AI are more art than science. AI can analyze population

health data empirically, comparing it to larger datasets to identify trends and risk factors, identifying health risks and trends, allocating resources efficiently and effectively. This will create new job opportunities in a wide range of new healthcare planning and management areas.

8. New Drug Discovery: By analyzing vast datasets to identify potential new drug candidates and predict their prospective effectiveness. This can lead to the development of new treatments and therapies creating a boon in research and development jobs.

status and estimate resource requirements from staff to disease specific equipment and supplies, helping hospitals to effectively meet demand.

10. Empirical End of Life and Organ Allocation Support: Complex ethical dilemmas in healthcare such as end-of-life care or organ allocation are often subjective leading to high-stress situations and emotional distress. Fact-based, empirical direction can often ease these tensions by providing an impartial third-party empirical rationale that all parties can rely on.

9. Resource Allocation:

Bringing Best Practices, Collaborative Evidence Based Medicine to the World

Predictive models can forecast inventory needs, automatically reorder taking advantage of preferred pricing, predict patient admissions based on historical data and population health

An article in the JAMA Open Network entitled “Use of GPT-4 to Analyze Medical Records of Patients with Extensive Investigations and Delayed Diagnosis” explains in depth how

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GPT-4 can “improve the diagnostic accuracy of clinicians by supplying the most probable diagnosis or suggesting differential diagnoses in complex cases.” The thrust of the article is how Open AI’s Chat GPT-4 can do more than augment the effectiveness of healthcare workers in parts of the world where more must be done with much less. Now, with a laptop and Internet connection, the quality of medical care can be elevated to be on par with the best care practices and science.

compare it to population health risk assessed databases to indicate a range of likely diagnoses helping clinicians narrow down their risk assessment and diagnosis. This risk assessment can guide further testing and treatment decisions.

1. Reviewing Medical Literature:

5. Automatic Monitoring:

GPT-4 can quickly go through vast volumes of medical literature, research articles, and clinical guidelines to provide clinicians with up-to-date information relevant to a patient's condition anywhere an Internet connection is available. Providers always have the latest best practices and treatment options at their fingertips and added services such as medication and therapeutic equipment acquisition can be added.

Staffing in many areas is spread thin and generally multitasked. AI can fill a critical gap by continuously monitoring patient data and updating its diagnostic suggestions as new information becomes available. It can detect subtle changes in a patient's condition that might indicate an increasing or decreasing risk factor or even different diagnosis.

2. Case-Based Knowledge: By evaluating complex patient cases using available medical data and comparing it to a database of similar cases, GPT-4 can identify potential diagnoses and suggest inferred or differential diagnoses and treatment protocols and the reasoning behind the recommendations.

3. Risk Assessment: Using available medical data, GPT-4 can 84

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4. Red Flag Alerts: GPT-4 can monitor medical records and identify potentially severe or urgent conditions requiring immediate attention and recommend diagnostic and treatment protocols.

6. Patient Education: Patient-friendly diagnostic and treatment plan explanations and summaries can help patients and their families understand their medical condition and treatment options in their native language. Where literacy is an issue, text to voice options are available.

7. Multi-Location Collaboration: GPT-4 provides a common platform for sharing and discussing complex cases and potential diagnoses.

AI’s Impact on Non-Physician Healthcare Workers AI is already having a significant impact on the non-physician healthcare workforce by assuming more and more routine tasks, which are transforming roles, streamlining processes, and enhancing efficiency in all healthcare settings. The net effect is that almost every side of healthcare can do more with less people. The upside is that those that remain are better trained and better paid. This trend will continue except in some areas. Vitals will still need to be taken and bedpans changed by people. For now. Here's how AI is affecting different non-physician healthcare roles:

1. Nurse Practitioners and Physician’s Assistants: Clinical Decision Support: Advanced Practice

Registered Nurses and Physician Assistants practice using algorithms while physicians use training and experience-based medicine. AI-powered clinical decision support systems recommend diagnostic protocols and provide real-time evidence based, best practice diagnosis and treatment presently at a physician level.

AI at the point of care allows providers to focus on patients, not paperwork

staff to be proactive instead of reactive to patients’ needs. Over time, the role of licensed practical nursing staff will be reduced or replaced with less skilled medical assistants. Medication Administration: Medication error remains a problem in hospitals and is a vexing problem in long term nursing facilities. AI systems help ensure accurate medication administration by verifying dosages, checking for drug interactions, and providing medication administration records including interfacing with patient data to suggest medication changes to prescribing physicians to allow them to be more proactive with inpatients.

3. Pharmacists: Automated Dispensing Systems: Hospital and

2. Registered and Licensed Practical Nurses

retain pharmacies may be staffed by a single pharmacist overseeing an automated system.

Patient Monitoring and Communications: AI-enabled

wearable devices and remote monitoring solutions provide up to data patient data on demand via smartphone or tablet and instantly when a patient calls for assistance. It also provides alarms and updates to allow nursing

4. Medical Laboratory Technicians and Technologists: Automated Testing: Like pharmacies, laboratory

equipment is becoming more and more automated and autonomous. While the role w w w. e u r o p e a n h h m . c o m

5. Billing, Revenue Cycle Staff, Medical Coders, Collections and Health Information Technicians: Automated Coding: AI is increasingly assuming

the role of assigning diagnostic and procedural codes to patient records, reducing, or eliminating the clerical workload for coders and improving coding and billing accuracy. Data Abstraction: AI can extract relevant information from unstructured clinical notes and documents including handwritten documents and data from disparate sources, aiding in accurate coding and data abstraction for research and billing purposes. As AI systems come online and improve through machine learning, lower skilled clerical positions will be reduced or eliminated. 6. Radiologic Technologists: These positions will be largely unaffected because obtaining images for X-Ray through PET Scans requires trained human intervention.

7. Administrative and Support Staff: From front desk staff in physician’s offices to back-office staff in health systems, overall staffing will be cut by as much as three quarters over the next ten years while other, 86

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more skilled positions will open. Training for existing employees for more skilled positions is an obvious win-win for both parties and a very likely outcome.

8. Healthcare Assistants and Home Health Aides: Roles in these areas are unlikely to change except for added training in the installation and maintenance of remote monitoring equipment. Overall, virtually every position, professional and support, in healthcare will change as AI is implemented and incorporated into the system. How those changes manifest will be a matter of the type of AI used, the type of healthcare system and the payment, political and institutional focus. Resistance, as the famous science fiction saying goes, is futile.

AUTHOR BIO

of phlebotomists is likely to be merged with laboratory technicians or eliminated outright, someone will still have to collect the samples and load the machines. Similarly, higher skilled technologists will still have to make more complex decisions and run maintenance and quality control programs on the equipment.

James Doulgeris is a retired healthcare executive with over 35 years’ experience in CEO roles in hospitals, accountable care and medical device companies. He is an active business, science and medical writer on healthcare and advisor and consultant to both healthcare provider and support businesses.

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Combating the Global Healthcare Cost Crisis with Artificial Intelligence

Healthcare costs are rising faster than GDP in most countries and this is completely unsustainable. Urgent action is needed to mitigate this trend. The AI & IoT revolution promises to reduce costs throughout the entire healthcare pipeline. From automating simple customer care to improved diagnostics, high-throughput image-based diagnosis all the way to personalized medicine and drug discovery. The coming decade will see enormous progress in the reduction of healthcare sector costs using these emerging technologies. Simon Waslander Chief Operating Officer of Teleios Health

ver the course of the past two decade’s healthcare spending as a percentage of GDP has increased from 8% to nearly 10% in OECD22 countries. Healthcare spending is an essential component for society but if these costs increase faster than economic growth, simple logic deduces that large systemic problems will arise. This can

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take many forms such as a reduction in the quality of care, a reduction in accessibility by less privileged parts of society, increased waiting times, or some combination of these. This is obviously very undesirable for society, patients, and the medical sector. (Figure 1) To make matters even more stressful, Western countries are facing a tsunami of aging population demographics. In 2022, nearly 10% of the population was aged 65+, by the year 2050, this is projected to increase to over 16% of the global population. As aging is the number 1, independent risk factor linked to non-communicable diseases, we can expect the increase in the elderly population to come with a host of chronic illnesses on the population level. (Figure 2) To compound these already worrisome trends, The World Health Organization projects that there will be a shortage of over 18 million healthcare workers globally by 2030.

Figure 1: OECD22 Healthcare Spending to GDP. Source: OECD

Overall this paints a rather bleak picture. However, the revolution in digital diagnostic tools, novel biomarkers, and Artificial Intelligence makes this author feel confident that we will not only overcome these challenges in the Western healthcare sector but improve care for patients across the board.

The Artificial Intelligence Revolution. According to a Nature Digital Medicine review by Mesko et al. 2020, Artificial Intelligence is expected to profoundly alter the practice of medicine. Furthermore, this new field of medicine is growing in an exponential fashion if we analyze PubMed citations. (Figure 3) According to this author, AI can be defined as follows: “A.I. is an interdisciplinary field spanning computer science, psychology, linguistics, and philosophy, among others. According to its simplest definition,

Figure 2: Global Aging Population

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Figure 3: Citations of Artificial Intelligence in Pubmed by Mesko et al. 2020.

Figure 4: FDA-Approved AI Tools in 2020 by Benjamens et al. 2020 90

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artificial intelligence (A.I.) is intelligence demonstrated by machines. It is sometimes also described as “machines that mimic cognitive functions that humans associate with the human mind, such as learning and problem solving” According to a review by Benjamens et al. 2020, there were over 29 FDA-approved AI algorithms, spanning radiology, cardiology, ophthalmology, endocrinology, internal medicine, emergency medicine, and oncology. (Figure4) Since this publication, the total list of tools has exploded. A complete list can

be found via the Medical Futurist at the following URL: https://medicalfuturist.com/ fda-approved-ai-based-algorithms/ With a special focus on radiology and pathology that are being revolutionized. In these fields alone there are over 392 registered AI-based tools. The long-term potential of AI doesn’t stop with ultra-specialized products. Just a few months ago, DeepMind a subsidiary of Alphabeth announced the creation of Med-PalM M. This system is described in detail in an article by emerging technology specialist Peter Xing.

Figure 5: xooxi oioxi oixoxi oxioxi oxo ixoixo ix

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Digital Twins

Figure 6: Digital Twin Graphic by Björnsson et al. 2020 (5)

This novel Multimodal Generative AI model simultaneously understands clinical language, imaging, and genomics. In total this system can perform 14 diverse biomedical tasks,

AI and IoT offer hope to combat the unsustainable rise in healthcare spending and address challenges from an aging population and workforce shortage.

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outperforming human counterparts in many of these tasks as well. (Figure 6) Driven by sensors, data gathering advanced laboratory diagnostics, and Artificial Intelligence. The concept of designing personalized Digital Twins of patients is a near-term possibility. With the potential set to profoundly affect all facets of the entire healthcare sector, be it in the realm of individual human suffering, workflow of medical doctors who are currently in growing scarcity, and even all the way to drug discovery, potentially leading to billions in savings for society. In the simplest terms, using real-time highly accurate health measurement tools both from

sensors and from wet-lab tests, clinicians are able to create a highly accurate digital surrogate of any patient. These concepts have been extensively reviewed by several authors. This technology is already reaching clinical relevance with various case studies already having been conducted. The potential of this technology is immense, from highly personalized medicine, to truly preventive analytics to next-generation drug discovery. Reviewed by this author in Longevity Report.

Concluding Remarks The Western healthcare system faces systemic challenges frightening its very core and social access. But on the horizon the dual Revolutions in Artificial Intelligence and Digital Twin based health surrogates are set to revolutionize every aspect of medical practice, creating not only a beacon of hope for current issues plaguing the sector but a bright tower of light. These new technologies will usher in an unprecedented period for medicine, leading to improved disease management, patient care, and quality of life for millions of healthcare participants. References are available at www.europeanhhm.com

AUTHOR BIO

Simon F. Waslander is the Strategic Engagement Partner of Swire Consulting and Capital. A boutique strategic management and capital matchmaking firm based in the United Kingdom. He is also the Chief Operating Officer of Teleios Health, a start-up seeking to revolutionize healthcare with the creation and use of Digital Twins technologies. Simon’s multifaceted expertise drives him to explore intersections between scientific advancement and business opportunities, shaping the future of both deep science and consulting landscapes. Based in Aruba, he is currently working to leverage the Island’s unique geographical position to attract global investment and innovation. Simon holds a BSc. in medicine from the University of Groningen and a MSc. in healthcare management, policy and innovation from Maastricht University.

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Digital Health Healthcare Digitization, Innovations & the Roadmap Digital health enriches healthcare education, helping train future professionals while empowering patients to engage in their care. Bridging traditional and digital healthcare presents challenges in interoperability and resistance, yet holds opportunities for enhancing efficiency and outcomes. Digital health can mitigate healthcare disparities through inclusive, personalized care. Future trends include AI-driven healthcare and telemedicine expansion.

Dipu Patel Vice Chair for Innovation Department of Physician Assistant Studies University of Pittsburgh

1. How has your background in healthcare and education uniquely prepared you to navigate the intersection of technology and healthcare in the digital health sector? My background in healthcare and education has uniquely prepared me to navigate the intersection of technology and healthcare in the digital health sector. As a healthcare provider, I understand the clinical aspects and the needs of patients. Additionally, my experience in education has given me insights into how to effectively communicate and train future healthcare professionals in the 94

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use of digital health technologies. This blend of clinical and educational experience allows me to bridge the gap between the technical and clinical aspects of digital health.

2. Digital health often involves collecting and managing vast amounts of patient data. How do you approach data privacy and security concerns in your work, especially in light of regulatory requirements like HIPAA? Data privacy and security are paramount in the digital health sector, especially considering regulatory requirements like HIPAA. As many aspects of the digital health ecosystem are in the early development phase, I would recommend that companies and entities aiming to implement digital health solutions should keep security protocols and encryption mechanisms at the forefront of their product design. Furthermore, ensuring that all members of the healthcare and support teams are well-versed in data privacy regulations and conduct regular training to maintain compliance. It's essential to stay updated on evolving regulations and adopt the latest security practices to safeguard patient data.

One promising digital health technology I find exciting is remote patient monitoring (RPM). RPM allows patients to be monitored outside traditional healthcare settings, providing real-time data to healthcare providers. This technology has the potential to improve patient care by enabling early intervention and personalized treatment plans, ultimately reducing hospital readmissions and enhancing patient outcomes. While current RPM technology is physically worn (smart watches, smart rings, etc.), the future will bring the increased use of digital tattoos and implantable devices which will truly revolutionize how care is delivered; rather that a single visit and single data point, we will make decisions on real time data and trends.

3. Given your commitment to innovation in healthcare, could you share an example of a digital health technology or solution that you find particularly promising in improving patient care or healthcare operations?

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4. With your experience in clinical, academic, and leadership roles, how do you see digital health impacting the training and development of future healthcare professionals, including PAs? Digital health is transforming healthcare education by providing students with hands-on experience through simulation, telemedicine, and virtual learning tools. This prepares future healthcare professionals, including PAs, to adapt to the evolving healthcare landscape and fosters a better understanding of technology's role in patient care, diagnosis, and treatment. The early education and training of healthcare providers in technology is crucial for their future patients.

5. You achieved certification in Artificial Intelligence for Medicine. How do you envision AI and machine learning influencing the future of healthcare, and how are you actively contributing to the integration of AI in the healthcare field? I am very excited to have achieved this certification and I look forward to the next certification. AI and machine learning are poised to revolutionize healthcare by aiding in diagnosis, treatment recommendations, and predictive analytics. I actively contribute to the integration of AI in healthcare by staying updated on the latest AI developments, collaborating with tech experts, and educating the next generation of healthcare providers in 96

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Digital health links education and patient engagement, enhancing efficiency and inclusive care, as AI and telemedicine redefine the future.

this budding field in healthcare.

6. Can you provide examples of how digital health technologies have enhanced patient engagement and self-care management in your experience? Digital health technologies have improved patient engagement and self-care management by offering personalized health apps, wearables, remote patient monitoring, and telemedicine services. Since the pandemic, we have seen a greater adoption of these tools which I think is for the better in the long run. While we are actively working the policies that govern these tools, they are empowering patients to monitor their health, access information, and communicate with their healthcare providers more conveniently and efficiently.

7. As someone deeply involved in both healthcare and technology, what are the key challenges and opportunities you see in bridging

the gap between traditional healthcare systems and the adoption of digital health solutions? The key challenges in bridging traditional healthcare systems and digital health solutions include data interoperability, resistance to change, and regulatory hurdles. The opportunities lie in improving efficiency, patient outcomes, and access to care through telehealth, remote monitoring, and AI-driven solutions while simultaneously continuing to research the best approach to implementation and outcomes.

8. Digital health can improve access to healthcare, but it also raises questions about healthcare disparities. How do you think digital health can be used to address and reduce disparities in healthcare access and outcomes? Digital health can help address healthcare disparities by enhancing and democratizing access to care, particularly for underserved populations through telemedicine and mobile health solutions. It can also provide culturally tailored information and education, making healthcare more equitable and inclusive through personalized health literacy plans and delivery methods.

9. In your role as Vice Chair for Innovation, how do you integrate digital health and technology into the curriculum for PA students

to prepare them for the evolving healthcare landscape? As Vice Chair for Innovation, there are several ways I integrate digital health and technology into the curriculum for PA students by creating interactive learning modules and incorporating digital health and AI tools into their training. The curriculum delivers this at both the Master’s and Doctoral levels. This ensures that current students and practicing PAs both receive the training needed. This ensures that they are not only well-prepared to engage with the technology but harnessing it for improved patient outcomes.

10. With your leadership in digital health and innovation, can you share insights into the future trends and advancements you anticipate in the digital healthcare field, especially in terms of improving patient care and clinical practice? Future trends in digital healthcare may include AI-driven diagnosis and treatment recommendations, expanded telemedicine capabilities, and the continued widespread use of wearables and health apps to monitor and manage health. These advancements will improve patient care and clinical practice by making healthcare more personalized, efficient, and accessible. Furthermore, we will see use of AI-driven solutions in hospitals and clinics for documentation, streamlining of processes and workflows, and patient triaging. w w w. e u r o p e a n h h m . c o m

healthcare and digital health?

11. You mentioned your commitment to the human touch in healthcare. How do you ensure that the adoption of digital health technologies does not compromise the essential human connection between healthcare professionals and patients? To ensure the adoption of digital health technologies does not compromise the human connection in healthcare, it's crucial to emphasize the importance of empathy and communication skills in healthcare and healthcare education; in fact, technology only heightens this need. Technology should be used to complement, not replace, the human touch.

12. Is there any key message or piece of advice you'd like to leave with our audience, whether it's healthcare professionals, educators, or those interested in the digital health field, based on your journey and experiences in

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AUTHOR BIO

The adoption of digital health technologies does not compromise the human connection in healthcare

My key message to healthcare professionals, educators, and those interested in digital health is to be curious and remain open to innovation and embrace new technologies while never forgetting the human aspect of healthcare. Technology is a tool to enhance the patientprovider relationship, improve care, and reduce healthcare disparities. It's an exciting time to be in the digital health field, and by working together, we can shape the future of healthcare for the better.

With over 23 years of experience, Dipu Patel, is deeply committed to medical education. Her leadership extends from academia to healthcare tech startups, where she led provider-driven, patientcentered clinical pathways. As Vice Chair for Innovation and Professor at the University of Pittsburgh's DPAS program, she focuses on quality improvement, innovation, and digital health. Her passion lies in merging clinical expertise with technology to enhance patient care and education while maintaining the importance of a human touch.

The Role of ML/ AI in Healthcare The field of AI is growing rapidly, and healthcare is poised for a transformative change. AI has the potential to greatly benefit the healthcare industry, but it must be embraced with cautious optimism. AI technology needs to be tailored to the unique challenges of healthcare in order to be successful.

Abhinav Chandra Executive Medical Director of Specialty Care, Yuma regional medical center

1. Can you provide an overview of how Machine Learning and Artificial Intelligence are currently being used in the healthcare industry? Machine learning (ML) is already being used in a variety of ways in the healthcare industry, including: Patient-directed technology: Wearable devices, AI chatbots, mental health and personal health apps, and genetic testing

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Physician-directed technology: Medical imaging and pathology analysis, electronic health records (EHRs), and data analytics Hospital-specific technology: Platforms like H2O.ai, Epic’s Deterioration Index Clinical research: Genetic analysis, clinical trial design, and drug discovery Telehealth: Telemedicine, disease management, and lifestyle management

2. What are some key challenges that ML/AI can address in healthcare, and how have these technologies been applied to solve them? ML/AI based technologies can help in monotonous, time consuming and laborious tasks. InnerEye is an AI system that can help doctors plan radiation therapy for head and neck and prostate cancer. It can do this much faster than traditional methods (up to 90% faster), which can save time and money for hospitals and patients and enables patients to receive cancer directed therapy sooner. Expanding care/ services to underserved communities using ML/ AI have been documented. Data-driven artificial intelligence model for remote triage in the prehospital environment was successfully launched in South Korea. The model was trained on a dataset of over 100,000 patient records from the National Trauma Data Bank (NTDB). The model was able to predict the need for immediate hospitalization with an accuracy of over 90%. The authors also evaluated the model in a real-world setting using data from over 1,000 trauma patients. The model was able to accurately predict the need for 100

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immediate hospitalization in over 80% of cases. AI is utilized in India in screening for cancer, osteoporosis prediction models and rehabilitation. BAGMO (blood bag monitoring) device addresses lack of blood availability in rural India.

3. Can you share specific examples of successful ML/AI applications in healthcare, highlighting the impact on patient outcomes or cost savings? The Nuance Dragon Ambient eXperience (DAX) is an AI‑powered, ambient clinical intelligence (ACI) solution that utilizes machine learning, natural language processing (NLP) to help in documentation. The physicians from healthcare systems who utilize this technology have reported 50% reduction in documentation time, 70% reduction in the feeling of burnout and majority of them feel that their quality of documentation has improved. The Centers for Medicare & Medicaid Services (CMS) has approved Medicare reimbursement for the use of the Food and Drug Administration (FDA)-approved AI algorithm IDx-DR. IDx-DR is a system that can detect more-than-mild diabetic retinopathy with 87% sensitivity and 90% specificity. A Novant Health facility used a predictive model called the Epic Deterioration Index (DI) to identify patients who were at risk of getting worse more quickly. This helped the hospital staff to provide better care to these patients, which reduced the number of deaths by 22% and saved an estimated 153 lives over 11 months.

4. Healthcare data is sensitive and subject to privacy regulations (e.g., HIPAA in the United States). How do you ensure data privacy and security when developing ML/AI solutions for healthcare? This has been a complex issue especially when dealing with healthcare and sensitive patient data. Risks can be mitigated by using de-identified data, when possible, data encryption and regularly auditing. Data safety can be maintained by partnering with secure cloud computing provider and having only authorized personnel access to the data.

5. What strategies or technologies do you employ to handle and process large volumes of healthcare data, including structured and unstructured data sources? The process of clinical trial matching is complex. A lot of information needs to be processed – inclusion and exclusion criteria, performance status, biological markers, next-generation sequencing (NGS) results, etc. Yuma Regional Medical Center has partnered with Tempus Labs, to open precision oncology clinical trials in real time. Data ingested was from electronic medical records through EMR integration or clinic, pathology reports, and NGS results were obtained. For the successful implementation of the program both methodologies were usedlarge amounts of data from the NGS labs were used to train a standard NLP model using annotated data. Also, domain experts validated the unstructured records from each

AI's potential in healthcare demands careful integration to effectively tackle unique industry challenges.

patient which were obtained through the EMR. There was a large amount of relevant data available from these sources. From the high-level patient matches, another domain expert manually evaluated the data to confirm that the match was appropriate. Subsequently, the information was sent to the site about a potential clinical trial for the patient. This led to the successful enrollment of patients in relevant oncology clinical trials at our institution. Results were published as an abstract at the American Society of Clinical Oncology conference in 2021.

6. How can ML/AI be used for disease diagnosis and early detection? Could you provide insights into the algorithms or models commonly used for this purpose? The Swedish group has shown that AI-supported mammography screening when compared with standard double reading has similar cancer detection rate. AI has shown good accuracy and sensitivity in identifying imaging abnormalities. There remains the need to balance enhanced detection

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Vs overdiagnosis which AI tools can help with. These technologies will be an ally to the radiologists and not eliminate the role of radiologists. They have the potential to enhance the workflow by identifying normal digital breast tomosynthesis screening examinations and decreasing the number of examinations that require radiologist interpretation. The company Freenome is using AI to detect weak signals in blood to diagnose cancer in early stages. The company analyzes fragments of DNA, RNA, and proteins in blood plasma. Its multiomics platform identifies key biological signals. The company deploys ML to understand additive signatures for detecting cancer early.

7. What role do predictive analytics and machine learning play in personalized medicine? Can you share any examples of personalized treatment recommendations based on patient data? Personalized treatment recommendations based on patient data can improve patient outcomes, be able to provide timely care and reduce healthcare costs. A new AI system developed at Johns Hopkins can detect sepsis earlier. Traditional methods of detecting sepsis can be slow and inaccurate, but the new AI system is able to identify patients at risk much earlier. This means that doctors can start treatment sooner, which can improve a patient's chances of survival. It has the potential of reducing the risk of death by 20%. The model sifts through electronic medical records and clinical notes to identify patients who are at high risk of developing serious complications. 102

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Google DeepMind has developed a new AI system that can predict acute kidney injury (AKI), a serious kidney condition, up to two days before it happens. This means that doctors can start treating AKI sooner, which could save lives. H2O.ai's AI system can look at all the data from a hospital or healthcare system to predict which patients are most likely to need to be transferred to the ICU or to get an infection while they are in the hospital.

8. In drug discovery, how can ML/ AI assist in identifying potential drug candidates or optimizing clinical trial designs? A new drug designed by artificial intelligence is now being tested in people. The drug is called INS018_055, designed by Insilico Medicine and it is being tested as a treatment for idiopathic pulmonary fibrosis (IPF), a chronic lung disease. The drug has completed phase 1 human safety studies and entered multi-regional Phase II clinical trials. The study is being conducted in the US and China and it will involve 60 people with IPF. The study will last 12 weeks and it will assess the safety, tolerability, and effectiveness of the drug. If the drug is successful in this study, it could be the first AI-designed drug to be approved for use in patients. This would be a major milestone in the development of AI-powered drug discovery, and it could lead to more effective and personalized treatments for a wide range of diseases.

9. What challenges do you see in adopting AI for drug discovery, and how can they be addressed? The challenges that need to be addressed are regulations, access to data and ensuring that the data is truly representative of the population, thereby reducing biases. Other barriers include high costs, ethical concerns and interpretability. Risk mitigation strategies should involve use of algorithms that are fairer and more transparent. There needs to be better under-

AI in drug discovery requires strategies to address regulation, data biases, and interpretability, emphasizing fair algorithms and transparent decision-making.

standing among researchers around the guidelines. Regulatory agencies are struggling to keep pace with the rapid evolution of AI. As technology advances, the cost of developing and deploying AI models will continue to go down. Also, legislature and government funding can help with AI based research. AI systems need to be more interpretable, i.e., we should have better data visualization of the AI predictions and the models should be able to explain their decisions. AI systems need to be transparent and explainable. One needs to understand how

the system makes these decisions and be able to identify any potential biases. Black box AI systems often involve complex algorithms such as deep neural networks. They can be effective in solving problems but difficult to understand. There is a potential to have biases built in in those systems especially if the system is trained on biased data.

10. What ethical considerations should be taken into account when deploying ML/AI in healthcare, especially regarding bias and fairness in algorithms? The ethical concerns regarding deploying ML/AI in healthcare revolve around trust, consistency and explainability. Work needs to be done to minimize bias and promote fairness in algorithms. We want to ensure that the data on which ML/AI algorithms are trained are free of bias as it can lead to adverse or unfair outcomes for the minority population. ML/AI algorithms need to be transparent about how these algorithms work and be able to provide information about how data is being used. There also needs to be accountability by possibly having human review. These processes will help in improving patient outcomes and building trust with the public.

11. How do you address the issue of interpretability and explainability of ML/AI models, especially when making critical healthcare decisions? Interpretability and explainability of AI ML/ AI models are crucial for healthcare decisions and for building trust. ML/ AI algow w w. e u r o p e a n h h m . c o m

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rithms need to be interpretable, consistent and trustworthy. The AI techniques used need to be transparent and explainable. As mentioned earlier, having human review of the decisions made by ML/AI algorithms can ensure fairness and help build trust. Also sharing data with patients about how these algorithms work can ensure buy-in from all stakeholders.

12. How do you ensure that ML/AI solutions in healthcare comply with industry regulations and standards, such as FDA approvals for medical devices or GDPR for data protection? The black box problem is the lack of understanding by which a ML/AI algorithm arrived at a particular conclusion is a matter of concern by healthcare organizations, public and regulatory personnel. For FDA approvals for medical devices, it is important to demonstrate that the device is effective, safe and has demonstrated success by enrolling sufficient patients in clinical trials. Other key factors include data privacy, security and ongoing compliance to ensure that the solution continues to comply with the latest regulations and standards.

13. Can you provide insights into the challenges and opportunities related to regulatory compliance in the healthcare AI space?

Dr. Abhinav Chandra is the Executive Medical Director of Specialty Care at Yuma regional medical center, AZ, USA. He completed his MBA from UCLA Anderson School of management. He completed the course ‘Artificial Intelligence in Health Care’ from the MIT Sloan School of Management in May 2022.

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One of the biggest challenges in the use of ML/AI in healthcare is that regulations are not keeping up with the rapid pace of innovation. Additionally, healthcare systems are complex organizations with multiple stakeholders and increasing regulations around data privacy and security. Despite these challenges, ML/AI has the potential to revolutionize healthcare by improving patient outcomes, reducing costs, and providing more timely access to care, especially for underserved communities.

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November 3, 2023

Health Intelligence and Automation 2023

Athens, Greece

November 29 - 30, 2023

https://www.iirst.com/event/index.php?id=2014084

London, United Kingdom

About Event: International Congress on Surgery serves as a forum for researchers, scientists, academicians, policymakers, and industry experts from all backgrounds to convene and share their expertise and insights. Attendees will have the opportunity to engage in stimulating discussions, exchange ideas, and establish valuable connections.

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International Congress on Surgery

Listed Under: Surgical Speciality

16th International Conference on Neurosurgery and Neuroscience November 13-14, 2023 Barcelona, Spain https://neuro-surgery.insightconferences.com/

About Event: The Health Intelligence and Automation 2023 (HIA 2023) conference is the premier event for healthcare professionals looking to stay at the cutting edge of technology. This two-day event features keynote speakers from top technology companies, hospitals & healthcare providers, pharmaceutical companies, investors, government agencies, and tech start-ups and the event will provide attendees with an immersive experience that explores how artificial intelligence, automation, machine learning and data analytics can be used to revolutionize healthcare delivery and patient care. Listed Under: Information Technology

About Event: Neurosurgery 2023 is an annual meeting which gathers Neurosurgeons as well as Neurology researchers to explore the future of the Neurosurgery and Neurological disorders which offers you to pay attention to distinct factors of new ideas and developments in Neurology and Neurosurgery to enhance public health and wellbeing. Listed Under: Medical Sciences

International Metabolic Diseases and Liver Cancer Conference

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December 4 - 5, 2023

Copenhagen, Denmark

London, England

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About Event: International Metabolic Diseases and Liver Cancer Conference will bring leading scientists, academicians, industry professionals, speakers, and experts of to one platform. The informative discussions will highlight solutions, achievements, trending issues, and future strategies.

About Event: The GIANT Health Event bring together innovators, investors, global corporates, established SME, doctors, hospital managers, government health officials, to engage directly with the UK healthcare procurement ecosystem; to spark productive business collaboration and accelerate better health outcomes.

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International Conference on Medical and Health Sciences

Warsaw Medical Expo

December 5- 6, 2023

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About Event: Warsaw Medical Expo will showcase medical equipment, rehabilitation devices, and hospital, clinic, and laboratory furnishings. It is the only opportunity to get acquainted with the offerings of various manufacturers and distributors and obtain reliable information about the products.

About Event: International Conference on Medical and Health Sciences will bring together leading researchers, engineers and scientists in the domain of interest from around the world. We warmly welcome previous and prospected authors submit your new research papers to ICMHS, and share the valuable experiences with the scientist and scholars around the world. Listed Under: Medical Sciences

December 6-8, 2023

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The 4th International Conference on Medical Imaging and Computer-Aided Diagnosis December 9-10, 2023 Cambridge, United Kingdom https://www.micad.org/ About Event: MICAD aims to provide a platform for researchers, academics, and industry professionals to come together and discuss the latest advancements in medical imaging and computer-aided diagnosis. Listed Under: Diagnostics

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8th International Conference on Cardiovascular Medicine and Cardiac Surgery

International Conference on Neuro Oncology (ICNO - 23)

December 06-07, 2023

December 15, 2023

Rome, Italy

Aarhus, Denmark

https://cardiovascular.cardiologymeeting.com/

https://sairap.org/conf/index.php?id=1872483

About Event: Cardiovascular Conference strives to bring renowned Cardiologists, Cardiovascular online visitors ranging from Researchers, Academicians and Business professionals, who are working in this field, students and Business delegates under a single roof providing an opportunity to share the knowledge and scientific progress in the field of Cardiovascular Medicine and Cardiac Surgery shaping the future research.

About Event: The theme and objective of the conference is centered around addressing the key challenges faced by various industries, including engineering, medicine, social science, applied science, management, and others. The aim is to bring together organizations and professionals from these fields to identify bottlenecks and collaborate on finding solutions.

Listed Under: Medical Sciences

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Freudenberg Opens New Manufacturing Facility in Ireland

Freudenberg Medical, a leading global design and manufacturing partner for minimally invasive medical devices, has announced the creation of 100 new jobs, as it marks the official opening of its newly expanded facility in Galway, Ireland. The freshly unveiled facility amplifies Freudenberg Medical's pre-existing manufacturing capacity in Galway by 50%. Simultaneously, the recently declared employment opportunities will lead to a 25% augmentation in the workforce, ultimately bringing the total headcount in Galway to 400 over the next 18 months. These new positions encompass roles in engineering, research and development, manufacturing operations, quality assurance, and support services. This expansion represents a calculated maneuver to accommodate the surging global demand for the company's vital metal components employed in catheters for minimally invasive surgeries. Furthermore, it strategically situates Freudenberg Medical to pioneer increasingly intricate products to cater to its international clientele. In Ireland, Freudenberg Medical currently employs over 1,000 individuals, operating across a combined 200,000 square feet of manufacturing space at facilities in Galway and Co. Leitrim. Collectively, these Irish establishments fabricate more than 16 million sophisticated catheters annually, catering to customers worldwide. Beyond Ireland, Freudenberg Medical operates in pivotal industry hubs spanning the United States, Europe, Asia, and Costa Rica. Its Irish facilities were originally initiated as joint venture partnerships with the former Cambus Medical and VistaMed operations, which have since integrated into Freudenberg Medical. Recruitment for the newly publicized positions at Freudenberg Medical is already in progress.

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Marizyme Launches Flagship Product for Cardiac Care

Marizyme, Inc., a global company dedicated to innovating medical technology to meet critical medical needs, has proudly announced the receipt of a de novo clearance from the U.S. Food and Drug Administration (FDA) for its pioneering product, DuraGraft™. DuraGraft is specifically designed as a vascular conduit solution for adult patients undergoing Coronary Artery Bypass Grafting (CABG) surgeries, intended for the flushing and preservation of saphenous vein grafts utilized in CABG procedures. The key action of DuraGraft lies in minimizing oxidative damage, thereby preserving the structural and functional integrity of vascular conduits. Extensive clinical studies, including imaging evaluations, have demonstrated that saphenous vein grafts treated with DuraGraft exhibit reduced graft wall thickening compared to conventional saline-treated grafts, particularly at the 12-month mark post-CABG surgery. Furthermore, the use of DuraGraft has been correlated with a decrease in long-term mortality up to three years post-CABG surgery. Following the de novo clearance, DuraGraft now stands as the exclusive FDA-cleared medical solution for use as an intra-operative vascular conduit storage and flushing application during CABG surgeries, serving as the sole approved product for this purpose in Europe and other global markets. DuraGraft is unique as the sole patented product tailored for this precise application in CABG and other vascular surgeries. Its patent portfolio is continually growing, with approved patents and pending applications spanning across 30 countries globally, including the United States, Europe, Australia, India, Argentina, South Africa, Mexico, and several Asian countries. READ THE COMPLETE POST

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Masimo's Hemodynamic Monitoring LiDCO® Module Receives EU MDR CE Mark Masimo declared that the LiDCO® board-in-cable (BIC) module has received the CE mark, aligning with the European Union Medical Device Regulation. The LiDCO BIC module is specifically designed for integration with multi-patient monitoring systems such as the Masimo Root® Patient Monitoring and Connectivity Hub, enabling advanced hemodynamic monitoring capabilities. This incorporation facilitates the easy integration of LiDCO hemodynamic monitoring, complete with its adaptable PulseCO® algorithm, into existing Root patient monitoring hubs. The pressure transducer agnostic nature of the LiDCO module ensures heightened flexibility for clinicians and hospitals.

This groundbreaking solution enables seamless hemodynamic monitoring alongside other supported parameters, eliminating the need for a dedicated hemodynamic monitoring unit. The LiDCO module supports a range of functions, including comprehensive guided protocols for assessing fluid responsiveness, comprehensive trending data, and alerts for beat-by-beat pressure analysis, all displayed in optimal configurations for individual patients on the Root monitor. The convergence of Masimo rainbow® Pulse CO-Oximetry and LiDCO hemodynamic monitoring promises to deliver substantial insights into patient conditions. The LiDCO module is designed for user-friendly setup and operation, utilizing a patient's existing arterial line and blood pressure transducer to monitor various advanced hemodynamic parameters via the robust beat-by-beat PulseCO algorithm. The instantaneous analysis facilitates prompt feedback on fluid and hemodynamic status, bypassing the delays associated with other hemodynamic monitors that rely on assumptions or specific notations. Its streamlined board-in-cable design seamlessly integrates with the Root monitor and other multiparameter platforms, reducing the need for an additional hemodynamic monitor in already spaceconstrained operating rooms and intensive care units. READ THE COMPLETE POST

Masimo LiDCO® (Photo Business Wire)

Barrow Neurological Acquires Two Harmony SHR™ Exoskeletons from Harmonic Bionics Harmonic Bionics has sold two Harmony SHR™ exoskeletons to Barrow Neurological Institute in Phoenix, AZ, for use in both their inpatient and outpatient programs.

motion for patients recuperating from neurological or musculoskeletal impairments. Its design supports evidence-based rehabilitation practices, including robotic-assisted mirror therapy, known to enhance outcomes for chronic stroke patients.

The first unit was delivered last month, marking Harmonic Bionics' inaugural clinical installation post its FDA registration in April. The second exoskeleton is set for delivery in November and will primarily serve Barrow's outpatient facility. Harmony SHR is an upper extremity exoskeleton with a specially engineered shoulder design, enabling a more natural and expansive range of

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Body Vision Medical Unveils AI Tomography Update for LungVision™ Platform Body Vision Medical has recently announced a significant software update for its groundbreaking LungVision™ navigation and real-time imaging platform.

CorWave Opens New Manufacturing Facility in France CorWave, a French company specializing in innovative cardiac assist devices, inaugurated its new facility adjacent to the Seine in Clichy, near Paris.

The latest update introduces advanced AI Tomography imaging algorithms, optimizing navigational accuracy and diagnostic success during lung nodule biopsy procedures.

With over 2,400m² of space housing production, laboratory, and office areas, the site consolidates CorWave's headquarters, R&D center, and its initial manufacturing facility spanning nearly 1,000m². This state-of-the-art factory is dedicated to the production and assembly of heart pump systems, facilitating the clinical trial phase and commercial expansion. This software release also enhances the LungVision™ workflow in collaboration with robotic bronchoscopy platforms, eliminating the necessity for C-arm spins during registration. Consequently, the streamlined workflow not only reduces the time required for the procedure but also minimizes radiation exposure for both medical staff and patients. The utilization of AI seamlessly transforms X-ray images into real-time intraoperative CT scans, empowering bronchoscopists to visualize pulmonary lesions during diagnostic bronchoscopy. This breakthrough technology holds the potential to enhance the precision of lung nodule biopsies, leading to early-stage cancer detection and improved lung cancer survival rates. The software update will be progressively rolled out to existing customers in the following weeks. READ THE COMPLETE POST

The new facility in Clichy houses an advanced production and assembly space spanning close to 1,000m², divided into two distinct areas. The first area is equipped with precision CNC machining centers, facilitating the intricate production of components vital to heart pump development. The second area comprises an ISO 7 cleanroom for controlled assembly, a specialized inspection zone for stringent quality control, and high-density warehousing for components and finished products. With a focus on its undulating membrane pump technology, CorWave aims to establish itself as a global medtech leader, producing up to 1,000 pumps annually, equivalent to potential sales of approximately 100 million euros. The facility's expansion prospects could amplify the production capacity to 10,000 pumps per year, representing a potential sales volume of around one billion euros, further solidifying its position in the industry. READ THE COMPLETE POST

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FEops Partners with ConcertAI's TeraRecon for US Market Expansion FEops, a pioneering figure in personalized predictive planning for structural heart interventions, has announced its collaboration with ConcertAI's TeraRecon for the advancement of FEops HEARTguide™ for Left Atrial Appendage (LAA) occlusion workflow in the US market. Leveraging digital twin technology, FEops HEARTguide™ offers a unique cloudbased procedure planning solution, allowing physicians to virtually simulate different implant positions and sizes of FDA-cleared LAA devices, resulting in enhanced procedural efficiency and outcomes. The partnership underscores the role of AI in reshaping the landscape of personalized and data-driven cardiac care.

X nix Medical Receives FDA Clearance for neoWave™ Implants X nix Medical, a surgical implant company specializing in solutions for spinal fusion surgery, has received U.S. FDA clearance for the nanotechnology classification of its neoWave™ line of interbody fusion implants, featuring the proprietary NANOACTIV™ surface technology. This designation bolsters claims for the neoWave cervical and lumbar interbody devices, with over 7,000 implants already in use across the United States. The NANOACTIV surface, with micro and nano-roughened features engineered at the nanometer level, is designed to enhance bone fixation and stimulate an endogenous cellular response, as demonstrated by in vitro studies. The advanced neoWave technology integrates a patented 3D-printed lattice design, providing strength while reducing device stiffness, ultimately improving endplate contact and resisting subsidence. This breakthrough combination of nanotechnology surface and lattice design represents a significant advancement in interbody fusion treatment, highlighting the potential of nanotechnology in enhancing patient outcomes and care.

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Naitive® Technologies' OsteoSight™ Gets FDA Breakthrough Designation Naitive® Technologies has earned FDA's Breakthrough Device Designation for OsteoSight™, its groundbreaking technology estimating bone mineral density (BMD) from standard X-rays. OsteoSight targets early osteoporosis diagnosis, addressing the challenge of detecting decreasing bone density before the onset of fragility fractures. By automatically integrating bone density estimates and WHO-based osteoporosis classifications into radiology reports, OsteoSight assists physicians in prompt intervention, potentially preventing debilitating fractures. This FDA program aims to expedite OsteoSight's regulatory clearance, ensuring timely access to advanced diagnostic tools for critical health conditions. READ THE COMPLETE POST

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Sleepiz One+ Device Gains FDA Clearance for Contactless Patient Monitoring

measurements compared to gold standard methods, Sleepiz is revolutionizing healthcare, elevating patient care, and empowering healthcare professionals.

Sleepiz, based in Zurich, has received FDA Class II 510(k) clearance for its Sleepiz One+ device. This small bedside table device employs contact-free measurement of macro and micro-motion to extract vital signs, aiding in the early detection of deterioration in patients with chronic conditions.

The Sleepiz One+ device can now be prescribed by physicians, ushering in a new era of personalized care. With both short- and long-term respiration and heart rate monitoring capabilities, it offers comprehensive insights into patients' physiological statuses, enabling timely interventions and patient-centric care.

The clearance facilitates the seamless integration of Sleepiz One+ into Remote Patient Monitoring (RPM) and clinical study platforms. With comprehensive respiration and heart rate monitoring capabilities, healthcare professionals gain valuable medical data for informed decision-making and actionable insights. Ensuring compliance in the realm of remote patient monitoring, Sleepiz One+ allows for 16 out of 30 days of measurements for Current Procedural Terminology (CPT) billing. This advancement opens avenues for RPM utilization and long-term monitoring, benefiting over 34 million individuals suffering from chronic respiratory diseases in the U.S. Boasting an impressive accuracy rate of 99 percent in breathing rate and 96 percent in heart rate

Designed for easy installation and use, the contactless Sleepiz One+ device enables patients to monitor vital signs from the comfort of their homes, providing continuous, accurate health status checks at their bedside. Sleepiz One+ is poised to make a significant impact in various sectors within the healthcare ecosystem, including Hospital at Home programs, pharmaceutical research and clinical trials, skilled nursing facilities, assisted living communities, and health and wellness initiatives. READ THE COMPLETE POST

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National Healthcare CMO Summit – A Marcus Evans Event 22 February - 23 February 2024 I The Las Colinas Resort I Dallas, TX I USA The National Healthcare CMO Summit is an invitation-only, premium Summit bringing Chief Medical Officer’s and innovative suppliers, and solution providers together. The Summit’s content is aligned with key clinical healthcare challenges and interests, relevant market developments, and practical and progressive ideas and strategies adopted by successful pioneers. The National Healthcare CMO Summit provides a platform that helps America's Chief Medical Officers evaluate and partner with relevant suppliers and solution providers, while we connect innovative healthcare companies with these Chief Medical strategists.

KEY TOPICS FOR 2024 The role of hospital leadership Strategizing with the healthcare triad to create resilient, high-functioning hospital teams

Healthcare access and equity Addressing healthcare disparities for quality care delivery and access to healthcare

The workforce crisis Developing strategies to drive retention, engagement and wellbeing of the hospital workforce

Healthcare technology integration From integrating AI in hospital workflows to digital health and telemedicine challenges

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Driving quality care delivery Returning to value-based care in the postpandemic era

Healthcare policy updates Evaluating the impacts of current and pending regulatory updates for physician leaders

Our distinguished speakers include: • Mark Olszyk, CMO – Carroll Hospital • Jason Globin, System CMO – Catholic Health • Jeetu Nanda, CMIO – Cone Health • Salim Saiyad, VP and CMIO – UPMC Central PA • Theodore Glasser, Chief Medical Officer – Baptist Medical Center – Jacksonville • And many more

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National Healthcare CNO Summit – A Marcus Evans Event 22 February - 23 February 2024 I the Las Colinas Resort I Dallas, TX I USA The National Healthcare CNO Summit is an invitation-only, premium Summit bringing leading Nursing Officers and innovative suppliers, and solution providers together. The Summit’s content is aligned with key clinical trial challenges and interests, relevant market developments, and practical and progressive ideas and strategies adopted by successful pioneers. The National Healthcare CNO Summit provides a platform that helps America’s leading Chief Nursing Executives evaluate and partner with relevant suppliers and solution providers, while we connect innovative healthcare facilities with these senior nursing strategists..

KEY TOPICS FOR 2024

Navigating financial headwinds Examining strategies for achieving and maintaining financial stabilitys

Our distinguished speakers include: • Theresa A Dillman, MSN, MHA, RN, NE-BC, Chief Nursing Officer – Glen Cove Hospital • Devin Carr, DNP, RN, RRT, ACNS-BC, NEABC, CPPS, Regional Chief Nursing Officer – MainHealth • Julie Mirkin, Senior Vice President/Chief Nursing Officer – Geisinger • Wendi Goodson-Celerin, DNP, APRN, NE-BC, CNO – Alameda Health System • Anne Marie Watkins, SVP/Chief Nursing Executive – UCI Health • And many more!

Nursing workforce development Fostering a skilled, diverse, and resilient nursing workforce

Redesigning nursing care Rethinking nursing practices and models

Digital innovation in nursing Harnessing digital innovation to enhance nursing practice

Optimizing the patient experience Exploring innovative approaches and best practices for improving patients’ perception of care

The multigenerational nursing workforce Promoting intergenerational integration and collaboration

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