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CONTENTS
APRIL/MAY 2013 | Volume 6, Number 2
16
FEATURES 16
Radiology’s Next Move: Bigger Data By George Wiley Reeling from seven years of reimbursement cuts, radiology has embraced business analytics and is plotting its approach to big data.
26
Radiology’s ACO Play: Get in the Game—Now By Julie Ritzer Ross Practices must honestly assess their abilities to add value and must waste no further time in opening discussions with potential ACO partners.
32
From Quality to Outcomes: Deploying Clinical Analytics By Joseph Dobrian The movement to use analytics tools to drive improvements in the quality, utility, and reliability of medical imaging is gaining momentum.
26
4 RADIOLOGY BUSINESS JOURNAL | April/May 2013 | www.imagingbiz.com
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CONTENTS
APRIL/MAY 2013 | Volume 6, Number 2
PUBLISHER CURTIS KAUFFMAN-PICKELLE · ckp@imagingbiz.com EDITOR CHERYL PROVAL · cproval@imagingbiz.com
DEPARTMENTS 8
ART DIRECTOR PATRICK R. WALLING · pwalling@imagingbiz.com TECHNICAL EDITOR KRIS KYES
AdView A Big Idea—and Bigger Challenges
ASSOCIATE EDITOR CAT VASKO · cvasko@imagingbiz.com
By Cheryl Proval
10
ONLINE EDITOR LENA KAUFFMAN · lkauffman@imagingbiz.com
The Bottom Line Is the Small Practice Dead?
CONTRIBUTING WRITERS JOSEPH DOBRIAN; ANIL NARANG, DO; JULIE RITZER ROSS; GEORGE WILEY
By Anil Narang, DO
12
36 38
Priors 12 Informatics | Big Data: Different From Small Data 14 Policy | Radiologist As Gatekeeper, Part I
ASSOCIATE PUBLISHER SHARON FITZGERALD · sfitzgerald@imagingbiz.com PRODUCTION COORDINATOR JEAN LAVICH · jlavich@imagingbiz.com
Advertiser Index
WEBMASTER ROBERT ELMQUIST · relmquist@imagingbiz.com
Final Read From the imagingBiz Web Journals
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Radiology Business Journal is published bimonthly by imagingBiz, 210 W. Main St., Suite 101, Tustin, CA 92780. US Postage Paid at Lebanon Junction, KY 40150. April/May 2013, Vol 6, No 2 © 2013 imagingBiz. All rights reserved. No part of this publication may be reproduced in any form without written permission from the publisher. POSTMASTER: Send address changes to imagingBiz, 210 W. Main St., Suite 101, Tustin, CA 92780. While the publishers have made every effort to ensure the accuracy of the materials presented in Radiology Business Journal, they are not responsible for the correctness of the information and/or opinions expressed.
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AdView
A Big Idea—and Bigger Challenges The notion of big data in radiology is tantalizing, but the challenges are great
E
very once in a while, a big idea floats, like a sweet vapor, across the popular consciousness, invading every corner of US life, from science to commerce to entertainment. Currently, our society (and business, in particular) is smitten with big data, and to be accurate, its reach is global, even unto health care. The lure is easy to understand. Take the case of biologist Pek Lum, PhD, working on a cure for cancer at a pharmaceutical company with a dataset that was a dozen years old. Lum found a correlation that she and fellow researchers had never seen before using a topology software that compresses relationships found in complex datasets into shapes more accessible to researchers than an ocean of numbers in columns would be.1 She discovered that groups of patients thought to have molecularly similar cancer were not as alike as she thought and that others were not as dissimilar—and she went to work for the software developer. We spend a good deal of acreage in this issue exploring how using big data is different from using data in traditional ways, how radiology is using data to run departments and practices, and how data can be used to improve clinical practice. To date, however, the application of data analytics in radiology would be characterized as smaller than big and the challenges before it as bigger than small.
DATA LIBERATION
The first challenge is one shared by all would-be users of big data in health care: A primary source of the data you deal with— personally identifiable health information— is highly regulated by the federal government and, therefore, fiercely guarded by each provider organization that collects the data. Consequently, these data are not freely shared. This is an access problem with implications for how data can be used. A second challenge is one that plagues any health-care data project: the ability to pull data from many disparate information systems that don’t speak the same language. In the language of health IT, this is interoperability. In the world of big data, however—for which
a defining characteristic is the sheer variety of sources from which information is pooled— the answer is data governance. On March 4, 2013, at the annual Healthcare Information and Management Systems Society meeting in New Orleans, Louisiana, Kathryn A. Whitmore, MS, president of STS Consulting Group, spoke on this topic. She explains, “Data governance is not a committee; it is not a back-office function: We are talking about a coordinated set of processes that includes people, procedures, and processing—a top-down, cascading model that allows us to transform data thought to be owned by one individual into a corporate asset that is shared.” A properly instituted data-governance plan is not intended to lock up data, but to cleanse them and ensure that the people who can use the data have access to the data that they need to accelerate change. Yet another challenge is this: All leaders—but especially physicians steeped in the scientific method—will struggle to overcome their causation bias and embrace the ideas of correlation and relationship visualized in big-data projects. In their new book on big data, MayerSchonberger and Cukier write, “Society will need to shed some of its obsession for causality in exchange for simple correlations: not knowing why but only what. This overturns centuries of established practices and challenges our most basic understanding of how to make decisions and comprehend reality.”2 An adjacent issue for organization leaders in all industries is the cultural shift inherent in replacing what wags call HiPPO, the highest-paid person’s opinion, with the willingness to defer to what the data indicate.
AN EVOLUTIONARY PATH
To deal with the access challenge, radiology departments and practices will need data ambassadors: highly skilled communicators who are able to articulate the need for data sharing across departmental and organizational borders—and to instill trust in partners. To address the datagovernance challenge, health-care systems, departments, and practices will need a policy that is at once inclusive and disciplined. They will need data czars with absolute power.
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For physician leaders, in particular, it might be easier to adapt to correlation and pattern recognition if they are viewed as a coping mechanism—an evolutionary step in dealing with petabytes (rather than megabytes) of data. Take a moment to look beyond local information systems and imagine the variety of data sources, characteristic of big data, that radiology will draw on in the future. Bradley J. Erickson, MD, PhD, director of radiology informatics at the Mayo Clinic (Rochester, Minnesota), believes that genetic and epigenetic information will be a part of the brew. What riches will the patient portals that radiology practices are building yield? Will data from biometric sensors supplement imaging data? How will the explosion in data resulting from the ICD-10 conversion be used? What effect will increased support of data projects at the National Institutes of Health (through the federal Big Data Research and Development Initiative3) have? Mark Kleinschmidt, CEO of Radiology Associates of North Texas in Fort Worth (the nation’s largest private practice), believes that radiologists—already experts in pattern recognition and informatics—have a leg up on other medical specialists and might even lead the big-data movement in health care. Are you ready for the cultural shift required to become a data-driven organization? Cheryl Proval cproval@imagingbiz.com References 1. Gage D. The new shape of big data. Wall Street Journal. http://online.wsj.com/ article/SB10001424127887323452204578 288264046780392.html. Published March 11, 2013. Accessed April 24, 2013. 2. Mayer-Schonberger V, Cukier K. Big Data: A Revolution That Will Transform How We Live, Work, and Think. Boston, MA: Houghton Mifflin Harcourt; 2013. 3. Office of Science and Technology Policy. Obama administration unveils “big data” initiative: announces $200 million in new R&D investments. http://www.whitehouse. gov/sites/default/files/microsites/ostp/ big_data_press_release_final_2.pdf. Published March 29, 2013. Accessed April 24, 2013.
THE BOTTOM LINE
Is the Small Practice Dead? Bucking the consolidation trend, one small practice retools itself to remain competitive
W
ith the rapid changes in health care, radiology (like other specialties) has had to adapt to survive. Smaller practices have been acquired or consolidated with larger practices. This allows greater emphasis on efficiency, shared risk, and economies of scale. There is also a perceived sense of security that comes with the size of the organization. Larger organizations, in addition, have greater negotiating power with both providers and insurers. These practices have the ability to attract toplevel management and administrative talent as well. Lost are the participatory governance and sense of ownership inherent in belonging to a smaller practice. There is great fear, in smaller practices, regarding their viability in a changing healthcare environment. Consolidation is not always desirable or practical for small radiology practices. The reasons can include geographic limitations, cultural differences, and individual preferences, as well as regulatory, legal, and contractual obligations. Small radiology practices are not necessarily doomed, however, and these practices can thrive in the current environment if the group can navigate change effectively. Is the 10-person radiology group dead? To the contrary: It is alive and well, in our experience. Our practice of 10 radiologists provided staffing to a community hospital, in addition to three outpatient imaging centers, which we owned and managed. The sudden departure of four partners to a large, national multispecialty provider network was a wake-up call to our practice to restructure and attempt to survive in a rapidly changing environment, where job security and competitive income were rapidly evaporating for the remaining partners. The outpatient centers were suffering from high overhead costs and were
servicing a sea of debt. The group was ineffective in responding to the changing dynamics because of internal turmoil. The result was a group that was being perceived as dysfunctional, unable to meet the needs of its primary hospital contract, and burdened by poor financial management— because noncompetitive outpatient ventures were draining both time and money from the practice. There was a strong desire, among the remaining partners, to retain and restructure the practice for future success. To make our practice thrive, we needed a national partner to acquire our technical assets, freeing the group from the debt burden and the great deal of time needed to manage the outpatient enterprise (and enabling us to refocus on the professional component of our practice). This refocusing required strong leaders and a competent management team, working with willing and flexible participatory partners. The partners were presented with a business plan clearly outlining the steps needed to ensure future success. The 10-point plan was devised to address the main concerns facing the group. These included enhanced income generation and the strengthening of hospital relations to align our practice with the strategic objectives of the hospital. Strong nonphysician management was necessary for accomplishing this task; we sought a radiology-specific management company able to support us with strong billing, contracting, and governance support.
DEMOCRACY AT WORK Effective change requires involvement of all members of the group in decision making and committees (including finance/ compensation, staffing, scheduling, quality assurance, outreach, and more). This allows greater acceptance and ownership of decision making—unique to smaller practices and harder to achieve in larger ones. This ability to make decisions rapidly, facilitated by a participatory governance model, allowed us quickly to adopt and
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BY ANIL NARANG, DO implement the proposed plan that has transformed our group. This change included an incentive plan with financial rewards for productivity, enhanced customer service, and decreased report-turnaround time. Adopting a 24/7, 365-day coverage model (allowing us to provide inhouse night-coverage service with final interpretations) resulted in significant cost savings to the practice and enhanced revenues. As a result, our daytime staffing needs decreased. These changes, along with the hiring of a neurointerventionalist and an interventional physician assistant, were perceived positively by the hospital administration, thus stregthening our relationship. In addition, it became imperative for the subspecialists to develop a comfort level in providing interpretations outside their specialties. Also adopted was a strong disciplinary policy for conflict resolution (necessary in small practices, where daily familiarity might limit the ability to resolve workplace issues effectively and honestly). A major component of this plan is fairly addressing the issue of both interventional and general radiology call and weekendcoverage needs. With greater cross-coverage among the different subspecialists, the group also needed to adopt a strong peerreview and quality-assurance program to ensure continued high quality. Even though the group’s size decreased by three radiologists, we are able to provide enhanced service, to generate greater revenues, and to have better relationships with our contractual clients, all the while obtaining a satisfied and cohesive group. After some soul searching and evolution, this 10-person radiology group is not dead: It is alive and well. Anil Narang, DO, is president of Clinical Radiologists Medical Imaging and Diagnostic Medical Imaging (Silver Spring, Maryland).
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{PRIORS} I N F O R M AT I C S
Big Data: Different From Small Data
T
hree factors distinguish big data from the analytics that many executive leaders are familiar with: volume, velocity, and variety. In a recent article that appeared in Harvard Business Review, McAfee and Brynjolfsson1 make the distinction and open a window on how two companies are harnessing big data to make more accurate predictions, better decisions, and more precise interventions—on an accelerated timetable. To describe the sheer volume of data available today, the authors explain that today, more data cross the Internet each second than were stored anywhere on the Internet in 1992. The retailer WalMart Stores, Inc, for instance, collects more than 2.5 petabytes of customer data every day from its checkout registers. How much information does a petabyte represent? It is equivalent to 20 million filing cabinets of text, the authors explain; multiply that by 1,000 for an exabyte. The authors estimate that 2.5 exabytes of data are created each day. Speed, the second key differentiator, is more important than volume, in many applications. The authors report that a colleague at the Massachusetts Institute of Technology Media Lab used location data from mobile phones to estimate Black Friday sales at Macy’s by inferring how many people were in Macy’s parking lot that day. “Rapid insights like that can provide an obvious competitive advantage to Wall Street analysts and Main Street managers,” the authors write. Variety is the third characteristic that distinguishes big data from traditional analytic activities, including many sources that didn’t exist 10 years ago, such as the messages, updates, and images posted to social networks; readings from sensors; and GPS data from cell phones. Purely through the tools and activities that we engage with today—cell phones, social
early, pilots and passengers sit on the tarmac, waiting for the ground crew; if it’s late, the ground crew stands idle, waiting for the passengers. PASSUR Aerospace, a provider of decision-support technologies to the aviation industry, is helping airlines eliminate this disconnect by providing more precise estimated arrival times. It collects data from public sources such as weather and flight schedules, as well as proprietary data that include feeds from a network of 155 radar stations that it installed near airports. The company believes that enabling an airline to know exactly when its planes will land results in several million dollars of savings at each airport. networks, GPS, and online shopping— each of us is now a walking data generator, the authors point out; because the data are unstructured, traditional structured databases that store much corporate— and health-care—information are unsuited to analyzing big data. DATA IN ACTION For skeptics of the notion that having data improves results in business, the authors interviewed executives at 330 public North American companies to determine their organizational and management practices, compared those results with performance data, and found that the most data-driven companies were, on average, 5% more productive and 6% more profitable. Specifically, how are managers using big data to improve performance? In time-sensitive industries such as aviation (and health care, for that matter), improving productivity often turns on finding and eliminating wasted minutes. Historically, the airlines rely on pilots—distracted by the responsibilities of landing an airplane—to provide estimated arrival times. If the plane lands
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BIG-DATA TIPS Having more or better data is not the key to succeeding in the big-data era, McAfee and Brynjolfsson1 write. Leaders who can set clear goals, define what success looks like, and ask the right questions will determine which companies succeed. Data scientists with skills in cleaning and organizing large, unstructured datasets (and with expertise in designing experiments) are both necessary and hard to find. The tools needed to handle volume, velocity, and variety are available and not prohibitively expensive, according to the authors. IT departments will have to acquire the skills required to integrate data from all relevant internal and external sources. Leaders will be challenged to create the organizational flexibility required to ensure that the people who understand the problem (and have the data) are connected with the people who possess the problemsolving skills. A fundamental cultural shift that a data-driven organization must make is the transition from what is thought to what is known.
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PRIORS
Combination brick-and-mortar and online retailer Sears Holdings Corp began an initiative to generate greater value from data collected from sales of Sears, Craftsman, and Lands’ End brands several years ago, and it ran into an obstacle familiar to health care: Data required to make decisions were highly fragmented, housed in many databases and data warehouses maintained by various brands. “Sears required about eight weeks to generate personalized promotions, at which point many of them were no longer optimal for the company,” the writers explain. For Sears, the answer was to borrow techniques from big data: It set up an Apache Hadoop cluster, a group of inexpensive, off-the-shelf servers commanded by an emerging software framework (Hadoop), and it started feeding data from each of its brands—
including data from existing data warehouses—into the cluster. The time needed to plan a promotion dropped from eight weeks to one, and the promotions themselves are of higher quality because they are more granular and timely. An added benefit is that data are processed at a fraction of what it would cost using a comparable standard data warehouse. CULTURAL CHANGES The managerial challenges of using big data are greater than the technical challenges, the authors believe. One of the most critical is silencing the highest-paid people’s opinions, or HiPPOs. When data were expensive and hard to get, relying on the intuition of upper-level managers made sense, but times have changed. To reinforce a data-driven decisionmaking culture, managers must begin by asking what the data say, then drilling
down to question the source, the types of analyses made, and the confidence in the data. They can also allow themselves to be overruled by the data. “Few things are more powerful for changing a decision-making culture than seeing a senior executive concede when data have disproved a hunch,” the authors write. The role of the domain experts will shift as big-data use advances; the experts’ value lies in their questions, not their answers. In conclusion, the authors have this advice: “In sector after sector, companies that figure out how to combine domain expertise with data science will pull away from their rivals.” —Cheryl Proval Reference 1. McAfee A, Brynjolfsson E. Big data: the management revolution. Harv Bus Rev. 2012;90(10):61-68.
POLICY
Radiologist As Gatekeeper, Part I
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or at least a dozen years, radiology has played a cat-and-mouse game with the notion of assuming a more active role in determining which patients get imaging. Due to concerns about referring physicians, the mouse, to date, remains elusive. The ascent of value creation in health care, however, has radiology not just thinking about a gatekeeping role, but preparing to assume one. Three speakers shared their thoughts in “The Radiologist As Gatekeeper: Should We Take a More Active Role?” on November 28, 2012, at the annual RSNA meeting in Chicago, Illinois. The session was moderated by Ruth Carlos, MD; Bibb Allen, MD, described the ACR® Imaging 3.0 initiative to provide practices with the requisite tools to assume that role (see article, page 30, for a brief summary of Imaging 3.0); Alan Kaye, MD, considered the practical aspects of that role; and A. Mark Fendrick, MD, shared insights into what is driving policy. Kaye, who is president of Advanced Radiology Consultants (Trumbull, Connecticut), portrayed the future of the practice as a blank canvas, with
many more details unknown than known. “One thing that is consistent along all of the programs that are incentivized by the federal government Alan Kaye, MD and by CMS (and recommended in the literature) are calls for safer, more effective, and more efficient care,” he says. Yet to be determined are the roles of capitation and fee-for-service payment, the prevalence of bundling, and how those bundled episodes will be characterized and reimbursed. With gain sharing and closer alignment among different providers likely to be components of the future practice, IT will be a key facilitator, Kaye believes. “The kinds of interactions and interrelationships that are going to be fostered by these new developments can only be done with a lot of IT input,” he notes. Whether those IT mechanisms put in place will be bridges to provider interaction or moats that promote silos and exclusive alignments remains to be seen.
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GUARDING/INVITING Typically, one thinks of a gatekeeper as someone who keeps things out—in the case of radiology, those would be unnecessary exams. “Radiologists are going to be key in that,” Kaye suggests. “We are going to establish guidelines, we are going to use the ACR appropriateness criteria, and we’re going to develop vehicles to implement those.” Letting people in is a less-discussed role of the gatekeeper, and that begins with doing the right exam on the right patient, correctly, the first time. Due to their role in screening exams, the entry point into the system for many patients, radiologists are in the first position. “Then, once we assert ourselves, we can be the referring physicians and move ourselves up the food chain,” Kaye says. “If you buy into the fact that a well-documented and wellvalidated screening exam leads to early diagnosis, it will improve outcomes— and it saves money, down the road.” Radiologists have three important screening tools: mammography, lungcancer screening with CT, and coronaryartery calcium scoring. “We need a validated way to stratify risk and screen
patients at moderate risk for their chances for disease,” Kaye says. Radiologists deal in information, and as such, are in an IT business, Kaye says. With the success of many new contemplated delivery models dependent on information exchange, radiology has significant health IT domain knowledge that it can share with hospital and accountable-care–organization partners. Another perspective on the radiologist as gatekeeper, Kaye says, is that the specialty can help demonstrate stage 2 meaningful use, which requires patients to access their information electronically. “One thing that is a major component of meaningful use—and a requirement of meaningful use—is the establishment of a patient portal,” he says, noting that many practices are collecting information that they never before collected. If that information goes into the patient portal and becomes portable, it can stay with patients as they move through the system. “Patients really value the ability to visualize that information and have access to it,” Kaye says. “We’ve done that in our
practice, and it’s had a lot of significant benefits for us. It lets the patients know who we are; they now know who their radiologists are. We have used it to create a bond with our patients. Patients are accessing their reports, and we’ve had zero complaints from our referring physicians.” RADIOLOGIST AS PORTAL Patient sign-ups to the practice’s portal (since it was established, at the start of 2012) have shown steady growth. Kaye says, “Right now, they are accessing their reports at a rate of over 100 per day.” Kaye’s practice also mined its information system and used the patient portal to send patient reminders (rather than letters) in a recent pilot project. About 1,000 female patients, 40 to 75 years old, were divided into three groups, for the purpose of communicating more specifically tailored messages: women who were due for a mammogram; women who had been screened, but hadn’t come back in the allotted time; and women who had had other exams at the practice,
but not mammograms. The communication resulted in 235 new mammograms being scheduled—a fact that has significant implications for the radiologist as gatekeeper. “We brought patients into the system,” Kaye says. “We brought patients not only to the referring physicians in our hospitals, but into the kind of care they should be getting.” Because patient compliance with mammography is a key measurement in so many established quality programs, he adds, “We contributed to safer, more effective, and more efficient care.” Being a gatekeeper is not such a bad idea, Kaye notes, particularly as the specialty grapples with concerns about commoditization. “This program changes us from a commodity to a member of the medical team—and an identifiable person to the patient,” he concludes. —Cheryl Proval Note: “Radiologist As Gatekeeper, Part II,” will appear in the June/July issue of Radiology Business Journal.
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COVER | Radiology and Business Analytics
Radiology’s Next Move:
Bigger Data
Reeling from seven years of reimbursement cuts, radiology has embraced business analytics and is By George Wiley plotting its approach to big data
I “
n the 1990s, it was easy to be a success. You had to work hard not to be a success. That’s not true any more,” according to Michael P. Recht, MD, Louis Marx professor of radiology at New York University School of Medicine and chair of the radiology department at NYU Langone Medical Center (New York, New York). Heightened competition, declining reimbursements, and pressure from payors to cut unnecessary imaging have forced the radiology department to watch every penny. Recht says, “We are looking at denials by site and by insurance company, asking whether there is something incorrect that we are doing. We can’t leave any money on the table.” To heighten its chances of financial success, NYU Langone Medical Center is doing what so many other radiology providers of size are doing: investing in business analytics to streamline operations and unveil opportunities perhaps otherwise missed. Analytics—a computerized way of searching for patterns—is assuming a higher profile in radiology business. The move to big data in radiology will require another leap. Characterized by the quantity and variety of data processed, as well as the speed of analysis (see article, page 12), the big-data movement seeks correlations, rather than causes, and patterns, rather than sums. It is as fundamental a management/ technological revolution as the move from film to PACS was—and equally impossible to ignore. Concepts such as data governance and pattern recognition are joining key performance indicators and balanced scorecards in the radiology management lexicon.
Preload: Preview Business intelligence—whether it involves straightforward data analytics or the more complex big data—is widely seen as a potential cure for many of the health-care sector’s ills. Efficiency and quality are the lowhanging fruit, but outcomes and
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predictive modeling are the destination as departments, hospitals, and radiology practices develop their analytics capabilities. Data governance, the ability to ask the right questions, and the means needed to cross data borders appear key to success.
Access to data has already proven its worth. When Hurricane Sandy knocked out a CT scanner at NYU Langone Medical Center (a four-hospital complex anchored by the 705-bed Tisch Hospital), real-time workflow measurements were used to reassign patients to the three remaining scanners more or less seamlessly: 95% of cases were completed in 15 minutes and 99% were done in 30 minutes. “These data have given our people autonomy and mastery,” Recht says. Analytics programs are being run from billing systems, RIS, PACS, and voice-recognition systems, and multiple vendors offer turnkey solutions for both business and clinical analytics. Some patterns and processes are similar in all business-analytics rollouts, but beneath the surface, it’s a mixed bag. With fragmentation being endemic to health care, there is a demand for solutions that stitch everything together—a necessary precursor to a big-data solution. Usable Data Thought leader James H. Thrall, MD, FACR, is an analytics pioneer. Formerly chair of the ACR® board of chancellors, Thrall stepped down as chair of the radiology department at Massachusetts General Hospital (MGH) in Boston (a job he had held for a quarter century). Thrall, who is active on the MGH medical staff and holds a professorship at Harvard Medical School, now spends more time on research, including data analytics. “There is a construct,” Thrall begins, “that goes: data to information to knowledge to wisdom. Data are individual facts, or a collection of individual facts. Information is organization of those data,
We are looking at denials by site and by insurance company, asking whether there is something incorrect that we are doing. We can’t leave any money on the table. —Michael P. Recht, MD
How do you do hand-cleansing protocols or timeout protocols? There are no commercial systems available that encompass all these elements so vital to managing a department. —James H. Thrall, MD, FACR
at some level. Knowledge is a higher-level organization of information. Wisdom is the ability to assimilate knowledge and also to draw inferences based on assimilated knowledge and experience.” Thrall says that business analytics for radiology has reached the information stage—and sometimes, the knowledge stage—but never the wisdom stage. “The big shortcoming I see in information systems—RIS and PACS—is that they provide no analytic capability,” Thrall says. “For example, we practice in nine different locations and we have CT scanners in seven different locations. I’d like to know how many of what kind of CT scans we did in each place. It sounds simple, but the RIS can’t give us that.” Thrall says that to get the data, MGH
has to export the numbers from the RIS daily and feed them into a separate server that has the software to provide the information needed to run the radiology department. “How do you do handcleansing protocols or timeout protocols? There are no commercial systems available that encompass all these elements so vital to managing a department,” Thrall adds. MGH calls its dashboard The Same Page, and it gave Thrall the ability to see how many exams of what type were done at each location. “I could then trend that for a month, a year, or two years,” Thrall says. “That is very basic, tangible analytic feedback you use as the department leader. It took me 15 years to have that on my desktop every day because of how clumsy these systems are.”
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COVER | Radiology and Business Analytics
We’re a big user of blood, with many operating rooms. There are cost and patient-safety aspects for any transfusion. We were able to reduce the use of blood by using electronic business intelligence and by partnering with our clinical teams. —Christopher J. Donovan, MBA Cleveland Clinic
This is not to say that MGH has gained minimal value from its business-analytics program in radiology; Thrall is quick to note that it has been indispensable. Tools have been developed to track changes in referral patterns, radiologists’ productivity, modality turnaround times, and much more. Dashboard-accessible heat maps display changing patterns; MGH has even developed readingroom dials to keep modality workflows proceeding optimally. The workflow dials are an example of what can be done with later-generation digital devices. Thrall says, “You mine data in real time and send that back to fine-tune the work process.” Vendors, he says, need to do more to improve data analytics by making all data sources compatible and creating accessible data exchanges to link information from different hospitals. For now, each hospital works largely with its own data. “There are so many vendors that harmonizing the data formats and installing a management or analytics system between one department and another would be a big challenge,” Thrall observes. Trusting the Numbers Hospital systems, radiology departments, and radiology practices are working to meet the challenge of structuring isolated data by organizing enterprise-wide business-intelligence units that adopt a top-down approach to disseminating information to those who need it. Administrators and executive committees determine the questions that they need to have answered and then assign individuals or teams to make
sure that needed data are gathered in a trustworthy way. Gathering reliable data for an enterprise data warehouse is a function of data governance, which assigns responsibility for the collection of specific datasets to specified individuals. The individuals are accountable for the data and their trustworthiness. Thrall compares this to any businessintelligence effort undertaken by a corporation. He says, “The strategy is to use key indicators in limited numbers and assign responsibility into the ranks.” A key indicator might be turnaround time; another might be hand hygiene. Thrall and his team identified about 150 key performance indicators and selected 30 when they built the Same Page system. “We have a person who is responsible for each key indicator and the time frame for reporting—daily, weekly, or monthly,” Thrall explains. “Each key performance indicator is fully defined and has a clear chain of responsibility. It could be the outpatient manager; it could be the quality manager or someone more senior.” The Data Governor Christopher J. Donovan, MBA, is executive director of fiscal services for the Cleveland Clinic in Ohio and is the architect of its enterprise businessintelligence strategy (which includes its facilities in Florida, Canada, and the Middle East). Donovan acknowledges that radiology operations are just one focal point in the business-intelligence effort. “We collect data from all across the enterprise,” he says. “We probably have close to 100 data projects. They come
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in as requests and are evaluated. Some are activated, and some are waiting for resources.” Anyone can request a data project, he says. A strategic multidisciplinary council reviews, scores, and ranks the requests as they are received and then prioritizes them. Once the data projects are activated, measurements for each project are developed and the results are displayed on dashboards. “We did a big project on blood use,” Donovan says. “We’re a big user of blood, with many operating rooms. There are cost and patient-safety aspects for any transfusion. We were able to reduce the use of blood by using electronic business intelligence and by partnering with our clinical teams.” The business-intelligence department was careful not to limit physicians in the ways they used transfusions. Instead, physicians were given computer displays with information on cost, safety, and trends in transfusion use. “That led to a lot of thinking, and it changed the way they used the resources,” Donovan says. “Blood use went down from 305 units to 206 units per 1,000 patient days.” Donovan says that one radiology project involves matching sites where imaging is done with sites where patients are served to see whether some imaging sites can be eliminated, based on patient convenience. “With value-based clinical care, there is a cost savings by decreasing sites,” he says. “That project uses our warehouse data. That’s ongoing right now.” A Cultural Transformation Kathryn A. Whitmore, MS, is founder and managing principal at STS Consulting Group. Whitmore consults on management analytics and overall enterprise intelligence, and she consulted with Cleveland Clinic on its businessintelligence strategy. Distribution of data across the whole enterprise is central to a business-intelligence initiative. By taking exclusive management of the data out of the IT department, you empower others to use it, she says. In this scenario, users in each relevant area (an access layer, or datamart) would have their own dashboards displaying
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COVER | Radiology and Business Analytics
Data governance is the ability to have a high-value corporate asset that everyone can share. It’s as much a cultural transformation as anything else. —Kathryn A. Whitmore, MS STS Consulting Group
the information that they need to make departmental decisions. Radiology would be one such datamart, accessing data through the enterprise data warehouse, with a strict data-governance policy limiting and granting access. The advantage of the enterprise approach is that it allows collaboration between departments (and from top executives down to department leaders). Whitmore says that the technology of data management is less important than the questions that are asked. “Data governance is the ability to have a highvalue corporate asset that everyone can share,” she says. “It’s as much a cultural transformation as anything else.” It isn’t about data and technology, Whitmore says, but about deciding what will give you the highest value. “The concept of a datamart is knowing that you have a business case to answer,” she adds. “With that business question in mind, you want just enough data components to answer that statement.” Nearly every vendor has a dashboard product as part of its software offerings, Whitmore adds. There are applications that can link data sources and drill down from the enterprise level to answer questions. She says, “You can install the analytics product on your own server or use most over the Internet, as software as a service.” Already underway is an evolution to mathematics modeling and natural language processing that will expand the types of data at our disposal and what can be accomplished with them, Whitmore says.
future? Can analytics open a door to solvency that not only is new, but that gives radiology a special place in the health-care hierarchy? At NYU Langone Medical Center, Recht is studying scheduling—not just of patients, but of how the department’s dozen or so schedulers are rotated to meet the ebbs and flows of scheduling demand. If Fridays are traditionally slow, Wednesdays might call for longer hours for the schedulers, Recht suggests. Another project is computing turnaround time: Recht says it’s not
Analytics in Action Data governance and enterprise business intelligence sound good, but what can business analytics actually accomplish? What might it do in the 20 RADIOLOGY BUSINESS JOURNAL | April/May 2013 | www.imagingbiz.com
just the time it takes for a report to be completed, but how time is spent on that exam by everyone in the department. Are patients handled efficiently? How long are billers on the phone? Kirk Lawson, MBA, is NYU Langone Medical Center’s administrative director of diagnostic radiology. Lawson says that the department always keeps an eye on its balanced scorecard—a ranking of financial incentives alongside clinical objectives, customer expectations, and internal hospital needs. To meet CMS assumptions for equipment-utilization rates, modalities must be in use a large percentage of the time, but patients don’t want to be rushed. “It’s striking that balance,” Lawson says. NYU Langone Medical Center is running analytics to see if it might overbook modalities (in the way that airlines overbook flights) to balance no-show and add-on patients, Lawson adds. “Our dashboard is presenting, in a very aggregated manner, tons of data,”
he says. “We have 25 or 30 things we look at every day. It’s how we survive in a competitive marketplace, where we want to get paid quickly because we’re getting paid less.” NYU Langone Medical Center uses a highly customized vendor solution that sits on top of the RIS and PACS to create reports and dashboards. The easiest questions to answer are the strictly numerical questions. What’s hard is developing algorithms that enable the department to change its patterns, Recht says. He uses the example of intervening when decreases are noticed in a physician’s radiology referrals. It might be that the physician is on vacation; the medical center doesn’t want to dispatch marketers if factors on the referring physician’s side are causing the decrease—but if the reason is something that the medical center is doing, it does want to know. “We have to act quickly, before we lose the referrer, but when should we intervene?” Recht asks. “We haven’t come up with that trigger yet, but we’re analyzing the question.” Socioeconomic Measurements Russell Cain, DBA, CRA, CIIP, CRT, is director of imaging services for Atlanta Medical Center in Georgia. The data that Cain looks at flow from the RIS and PACS, the hospital’s electronic medical record (EMR), the modalities, billing, and corporate headquarters. He can monitor productivity, workflow, staffing, and all of the things that hospitals use data analytics to assess. He also gets daily reports from financial analysts at the hospital’s parent company, Tenet Healthcare Corp, that show reimbursements and the payor mix. He can spot surge patterns in the emergency department and can staff accordingly; he says, “I should be able to respond to imaging requests in 15 minutes.” Things also happen by surprise, and this shows up in the data, too. The hospital lost a contract for mammography that accounted for 20% of the mammography workload. “In terms of staffing and revenue, that was a tremendous impact,” Cain says. Cain can see decreases in referrals as a referring physician gets ready to retire,
Our dashboard is presenting, in a very aggregated manner, tons of data. We have 25 or 30 things we look at every day. It’s how we survive in a competitive marketplace, where we want to get paid quickly because we’re getting paid less. —Kirk Lawson, MBA NYU Langone Medical Center
You can’t just look at imaging; what about outpatient surgery? The trends are out there. Of baby boomers, a lot are still working, but they’re looking at preventive health, and they’re getting imaged more regularly. —Russell Cain, DBA, CRA, CIIP, CRT Atlanta Medical Center
and to make sure that this is what is happening, he can respond by sending a marketer to the practice. “I don’t use one data point,” Cain says. “I look for trends.” Watching socioeconomic trends is important, he adds, because they will affect demand for imaging. “You can’t just look at imaging; what about outpatient surgery? The trends are out there,” he says. “Of baby boomers, a lot are still working, but they’re looking at preventive health, and they’re getting imaged more regularly. We’ve got a lot of young people in our downtown. They’re athletic, and they’re interested in preventive measures. Do we have a sports-medicine practice? How do I support that? That affects what we look at when hiring; we’ll want radiologists with musculoskeletal skills.” Analytics for the Practice The potential and uses of business analytics in the radiology practice are as vital as in any other provider setting. A private practice is likely to be hooked into several enterprise systems through the hospitals that it serves, and might be a participant in a huge data network. It is
this characteristic that sets some privatepractice radiology directors dreaming. Is there some way to use data analytics to create a new profit center out of the information that a radiology group can provide? At Central Illinois Radiological Associates (CIRA), Peoria, Illinois, the decision was made to partner with a billing-services vendor that was able to provide the radiology group with roundthe-clock data access and analytical software—to build meaning from the practice’s CPT® coding. Gregory Q. Hill, JD, CIRA’s CEO and an adjunct associate professor of radiology at the University of Illinois College of Medicine, says that CIRA has 77 radiologists who interpret for 16 hospitals in four separate hospital systems. CIRA also owns three interventional clinics, but not the equipment in them, Hill says. In addition, the group reads for 21 ambulatory centers operated by physicians with their own imaging equipment. CIRA interprets more than 1.3 million procedures annually. “With the data analytics we have
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Business Intelligence Series #8
Smart Growth in a Tough Market: Leveraging Business Intelligence at Texas Radiology Associates Radiology’s business environment has changed considerably since the heyday of the late ‘90s and early 2000s, when, says Paul Staveteig, MD, the equation for success was comparatively simple. “Now the environment is different,” he says. “The only way to survive in this marketplace is to be able to look at things very critically and make decisions very quickly.”
“The only way to survive in this marketplace is to be able to look at things very critically and make decisions very quickly.” — Paul Staveteig, MD Staveteig is a physician partner with Plano-based Texas Radiology Associates (texasradiology.com), also known as TRA. The 70-radiologist practice has contracts with nearly 20 hospital clients in the north Dallas area, including three large hospital chains and some physicianowned hospitals; the practice also reads for a handful of private, specialty physician groups. Three years ago, TRA began outsourcing its billing to Zotec Partners, the Indianapolis-based provider of billing and business intelligence services for radiology. Prior to contracting with Zotec, TRA worked with another third-party billing service, but the system was paper-based and unwieldy, Staveteig says: “Accountability for claims, reprocessing claims—it was really a challenge. So we went with Zotec for electronic billing.”
The Next Step The short-term result was a significant improvement in billing efficiency, Staveteig says. But Zotec’s electronic billing system had more to offer the practice than more efficient claims processes. With the com-
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pany’s business intelligence services, which provide data on everything from the practice’s payor mix at its different client facilities to the range of modalities from which the practice’s radiologists are reading studies, TRA is better able to evaluate potential new contracts—a critical consideration for a practice trying to grow in a competitive market. “With all of these hospitals, we can very quickly get a good idea of where there are new opportunities,” says Staveteig. “Looking at the payor mix and mix of modalities, we can come up with a reliable predictor of gross revenue for a particular project, and that helps us evaluate how best to grow our practice. We have found the predictions based on Zotec’s data to be within 5%.” The evaluation process also helps the practice anticipate a new client’s needs in terms of staffing, ensuring that TRA will provide optimal service from the start: “We recently started with a hospital in Sherman, Texas, and we were able to make staffing decisions to make that relationship work for the patients, administration and physicians there.”
Empowered Decision-making The ability to make these decisions pro-actively is critical to TRA’s success in its market. “We’re in an environment that’s had a fair amount of vertical integration within the medical community,” Staveteig notes. “We are able to partner with the administrators in the hospital chains as well as our local physicians to give people what they want: timely service, accurate service, and continuous, 24/7 service. We’ve been able to grow despite some of those changes that have happened in the marketplace here.” As its billing partner, Zotec has been responsive in
Sample Zotec graphics.
developing tools to address TRA’s specific needs, Staveteig says. “It’s been great partnering with them, and a lot of the tools they’ve developed were in response to issues that cropped up as we were working together,” he notes. “Each year we have something new.”
“These tools from Zotec are quite powerful. In our group meetings, we can make good decisions that people feel very comfortable with.” — Paul Staveteig, MD Most importantly, Staveteig says, business intelligence enables TRA’s physician partners to achieve consensus on difficult decisions more efficiently and with greater confidence. Empowered by clear, real-time information and analytics, the practice’s conversations around tough decisions stay on track. “Our discussions are based on data, and that keeps us on task,” Staveteig
says. “Everyone has something to add, and we take the best from everyone and then move forward.” He concludes, “These tools from Zotec are quite powerful. In our group meetings, we can make good decisions that people feel very comfortable with.”
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COVER | Radiology and Business Analytics
The ability to aggregate data has been a game changer because we are able to make decisions based on data from all 16 hospitals. The economies of scale and efficiencies are significant. —Gregory Q. Hill, JD Central Illinois Radiological Associates
today, the decision-making process is more credible,” Hill says. “The ability to aggregate data has been a game changer because we are able to make decisions based on data from all 16 hospitals. The economies of scale and efficiencies are significant.” CIRA uses analytics to track key performance indicators such as charges, imaging volumes, work RVUs, and receipts. The group also can track denials. “If I have a significant denial issue, then I can approach the hospital or the payor,” he says. “Think how powerful those data are. Prior to this I, would have had to obtain the information from multiple sources and aggregate the data myself. Now, they all come from one source.” Some analytics problems are easy, but others are more complicated; Hill says, “I can have productivity information for a site in five minutes. If we receive a request for proposal to provide services at a new hospital, however, obtaining the data not owned by CIRA requires additional time and effort.”
a focus on quality. The practice took radiology quality measures from CMS, the National Quality Forum, the ACR, and other sources and used them to develop its initial analytics program. Today, Greensboro Radiology is running its analytics effort using a system (developed in-house) that makes use of a single vendor’s voice-recognition transcription system and natural language processing software to pull data from radiology reports.
Canopy Partners Greensboro Radiology in North Carolina is taking its analytics program in two directions. It is using analytics within its own practice of 55 radiologists, but it has spun off Canopy Partners, a managedservices organization that provides analytics, billing, and other services to hospitals, radiology groups, and physician practices of all kinds. Worth Saunders is CEO of Greensboro Radiology and Canopy Partners; Stephen Willis is CIO of Canopy Partners; and John A. Stahl, MD, is chair of the best-practices oversight committee at Greensboro Radiology and a shareholder in Canopy Partners. According to Stahl, Greensboro Radiology began its analytics effort with 24 RADIOLOGY BUSINESS JOURNAL | April/May 2013 | www.imagingbiz.com
Other measurements come from the PACS and the billing system, but the heart of the data gathering is the voicerecognition system, deployed across all client sites. A single PACS is also used to view and distribute all images. “A single voice-recognition system leads to results from a single source,” Willis says. “Text and messaging coming out of the voice-recognition system contain the exam code, RVUs, the radiologist’s name, several different time stamps, and when the exam was started and completed.” Stahl says, “With natural language processing, the system has the potential to provide a radiologist with real-time alerts: Did you include this information in your report for this diagnosis, did you put all the information in for correct coding and billing, and did you notify the referrer and document that in the report?” While this ability isn’t in hand yet, it’s on the
way, Stahl says, and it will reduce delays in reimbursement. Saunders notes that Greensboro Radiology recently merged with an eight-physician practice that had a different arrangement for night coverage. Greensboro Radiology was able to use data stored in its analytics warehouse to integrate night coverage for both groups. “Whether it’s business quality or clinical quality, the difficulty is to assemble the measures that you think are useful in a fashion where the data can be obtained consistently, over time,” Stahl says. Save a Dollar and Earn a Dime Radiology Associates (RA) of North Texas in Fort Worth, the largest private radiology practice in the country, owns 13 ambulatory centers and interprets for hospitals at 26 sites. The practice’s 122 radiologists read about 2 million exams annually. Mark Kleinschmidt, RA’s CEO, says the group is now in the infant stages of building its analytics capability, still identifying key measurements and constructing a data warehouse. It is the big-data vision that Kleinschmidt offers—radiology as information broker—that is compelling. “Radiology is, and always has been, an information business, so radiology analytics is a natural step,” Kleinschmidt says. “Radiology has always been about using pattern analysis.” Currently, RA is collecting data from its own systems, the EMRs of the hospitals that it serves, and even publichealth sources, Kleinschmidt says. These data will be standardized and put in a single data warehouse to create a meaningful data pool that can be used to assist hospitals in studying radiology use, outcomes, and other topics. “At what point in a patient’s episode of care is an imaging study best performed?” Kleinschmidt asks. “Is it best on the front end, or is it better to wait and watch for six weeks?” There are instances in which RA radiologists have spotted orders from one hospital for an exam that the same patient just had at another hospital. “We want to try to use data to support whether those health-care costs are necessary,” Kleinschmidt says.
With natural language processing, the system has the potential to provide a radiologist with real-time alerts: Did you include this information in your report for this diagnosis, did you put all the information in for correct coding and billing, and did you notify the referrer and document that in the report? —John A. Stahl, MD Greensboro Radiology
Health care has been held back by competition, privacy, and security issues. Retailers are collecting data right and left. We think radiology can lead the way in health care. —Mark Kleinschmidt Radiology Associates of North Texas
RA is well positioned as an information broker, Kleinschmidt says, but the challenge is getting the competing hospitals that it serves to see the advantages of combining data. Kleinschmidt says, “There is a move away from fee-for-service reimbursement to paying for population health. We think we can provide an overall analysis based on the entire population of Fort Worth. We’re just at the stage of communicating and getting people to buy into that.” Kleinschmidt acknowledges it won’t be easy. “Health care has been held back by competition, privacy, and security issues,” Kleinschmidt says. “Retailers are collecting data right and left. We think radiology can lead the way in health care.” After all, he says, radiology is the only specialty that deals routinely with almost every other specialty. The information gatherable through radiology is potentially huge. Recently, Kleinschmidt asked his IT department to give him the number of patients at any site who’d had
more than one CT exam of the head in the past 30 days. “We found 38 patients from one hospital system who’d had more than one such exam—and one patient who’d had 14,” Kleinschmidt says. “What we found was that one hospital had a significant stroke program. It has a protocol that all stroke patients get a head CT every morning to see whether there have been changes. The question is this: What is magic about one day? We have raised the issue. We don’t tell the hospital how to do this, but as people on the radiology business side, we think that’s useful information to have.” He adds, “It’s worth looking for patterns. In someone with a bad back, what’s the likelihood of knee trouble? In the long run, if we can save money for the system, we’ll get paid for it. If we save them a dollar, they’ll pay us ten cents.” That’s an argument in favor of radiology business analytics all by itself. George Wiley is a contributing writer for Radiology Business Journal.
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RADIOLOGY | The ACO Play
Radiology’s ACO Play: Get in the Game—Now
Practices must honestly assess their abilities to add value and must waste no further time in opening discussions with potential ACO partners By Julie Ritzer Ross
T
he ACO, a relatively new concept that met with great skepticism when it appeared in the Patient Protection and Affordable Care Act, now ranks at the top of the conversation-starter list in the radiology community. Imaging providers have debated whether it is necessary for them to engage with these entities, and, if they do, what roles they would play. The current consensus not only is that radiology cannot afford to ignore the ACO model, but also that a strategic approach must be followed if providers are to assume their positions successfully under the ACO umbrella. Some (if not many) radiologists have made no immediate attempt to procure a seat at the ACO table, instead adopting a wait-and-see attitude or ignoring the issue entirely. Such procrastination is shortsighted at best, according to W. Kenneth Davis Jr, JD, partner with Katten Muchin Rosenman LLP. He says that providers who envision themselves joining Medicare ACOs must bear in mind that unless they take action now, they might find themselves with little decision-making power later. His rationale: Medicare ACOs are required to sign a three-year contract with Medicare; during this initial period, they can terminate participants, but cannot bring aboard any additional ones, be they operators, founders, or owners. It’s just as significant that while ACOs in this category can add providers and suppliers on a contract basis (within the first 36 months in which an agreement is in force), contract players cannot be assigned governance roles within the organization. “This, in itself, should be impetus to move today—not tomorrow,” he says.
Preload: Preview Radiology practices interested in being governing members of accountable-care organizations (ACOs) have already missed the boat, for existing arrangements, due to the nature of the three-year contracts.
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Utilization management, imaging appropriateness, and management of imaging programs are key activities that affect the quality and cost of overall care. It is unlikely that a radiology practice will ever lead an ACO, but opportunities to contribute and participate exist.
I told the prospective client,
“Any APS billing discrepancy for covered client services will be reimbursed at the allowable provider rate.” This partner in a 17-person radiology group was surprisingly candid with me about why he had not already outsourced his billing to us. “There are two main reasons,” he said. “First, I’m concerned that the billing-department head will be out of a job.” That wasn’t news to me. In fact, I’d heard it so many times that it had become a predictable objection to outsourcing.
W. Scott Cubellis CEO
The second objection expressed concerns about accuracy and service. “There’s this feeling that if we don’t directly control the billing and collections, we’re not going to get what is coming to us,” he said. “There is something I want you to understand,” I replied. ”APS is directly involved in the second most important aspect of these businesses. After providing professional services, you have to get paid. If you don’t get every penny that is coming to you, I’m going to hear about it—and fast—because we hold ourselves accountable to you. We would not have been in business for over 30 years if we made those types of mistakes. “I understand your concerns, though, so I can safely say that after the customary ramp-up period, you will be pleased with the collections results we’ll achieve.” I made that statement because I was confident that our experience, our expertise, and our dedication to his success were going to make this one of the best business decisions he’d ever made. I was right: Collections increased, expenses were reduced, and the entire operation ran smoother. Oh, and remember that department head who’d been there for years? She is now the liaison between the company and us. Essentially, outsourcing your billing comes down to the fact that in the current health-care environment, it is no longer feasible to conduct business as usual. Today, I can make that same guarantee to you: We are so confident in our systems and service levels that any billing discrepancy generated by APS for covered services will be immediately reimbursed to you at the allowable provider rate. To find out how to get started, call me directly at (866) 914-8719.
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RADIOLOGY | The ACO Play
ACOs are all about sharing and reducing costs without compromising the quality of care. Radiologists are in a perfect position to go beyond interpretations and act as utilizationmanagement resources. —Chip Hardesty Radiology Ltd
There is a tremendous need for such [IT] skill in the ACO model. —James T. Whitfill, MD
Despite the widely acknowledged fact that ACOs—Medicare and otherwise— are in the formative stages of development and have not hit their stride, radiologists’ chance to forge appropriate ACO alliances with the highest potential for long-term success is greater today than it will be in the not-too-distant future. Bibb Allen Jr, MD, FACR, serves as a diagnostic radiologist in the Birmingham Radiological Group in Alabama and as vice chair of the ACR® Commission on Economics. He is also the lead author of an ACR white paper1 on the subject. In the white paper, Allen et al point out that ACOs might cultivate partnerships with multiple radiology groups, entertain proposals from radiology groups based at different hospitals, and/or consider using the services of outside teleradiology companies to satisfy their imagingservices needs. As a guarantee of future ACO affiliation, “complacency and reliance on existing provider contracts at participating hospitals are not options,” Allen says. The longer the delay in attempting to sit down at that ACO table, he adds, the smaller the number of remaining tables from which to choose. Making the Transition For radiology, gaining entry into the ACO arena and becoming a key player in the delivery of care through an ACO model
are heavily predicated on a willingness and ability to offer significant added value in the management of population health. Assuming a utilization-management role that involves the assessment of imaging appropriateness and advocacy for the safest, most accurate diagnostic tests—no matter the payment methodology—is key. Chip Hardesty serves as COO of Radiology Ltd (Tucson, Arizona), which—in addition to outpatient services—provides imaging for Tucson Medical Center. The facility, along with two other independent physician groups, was one of five Brookings–Dartmouth ACO pilot sites. Hardesty notes, “ACOs are all about sharing and reducing costs without compromising the quality of care. Radiologists—who know better than other physicians which tests are best suited to which cases and when it is prudent to opt for (or against) a certain test—are in a perfect position to go beyond interpretations and act as utilization-management resources. What’s more, while it may be fairly easy for ACOs to outsource image interpretation, utilization management is much tougher to outsource, making it a very valuable way to add value.” In assessing imaging appropriateness, overseeing utilization, and administering imaging programs, Hardesty says, it
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behooves radiologists to use such IT tools as computerized provider order entry (CPOE) with decision support. In weighing in on imaging appropriateness and executing other tasks related to utilization management, however, radiologists must present feedback that is not limited to findings derived from CPOE with decision support and similar technologies, but also is based on their expertise. “If utilization management appears to ACOs as the sole product of software tools, utilization management could become commoditized—just as imaging interpretation has been, in many communities,” Hardesty says. Reclaiming the Consultative Role The added value to be afforded to ACOs by radiology also comes in consultative form. James T. Whitfill, MD, is CMIO at Southwest Diagnostic Imaging Ltd (Phoenix, Arizona) and is founder and president of Lumetis, LLC, a company that delivers IT solutions, guidance, and operational services intended to facilitate the transitions of hospitals and health plans to high-performing accountabledelivery systems. Until about 15 years ago, Whitfill says, radiologists routinely harnessed their extensive knowledge of disease and clinical states in serving as true consultants to specialists in other fields. Such catalysts as the advent of PACS, however, spurred them to cede those roles, which must now be reclaimed if ACOs are to regard radiology as something other than a commodity. Whitfill notes that on the consultative side, the true value of radiology transcends the production of text-based reports at the fastest speed and the lowest cost. It expands to encompass partnerships wherein radiologists and specialists coordinate patient care and services on multiple levels and strive to vet each others’ approaches. When the consultative piece is part of the value pie, ACOs could regard radiology in an entirely new and more positive light, Whitfill observes. In a similar way, the ACR holds that radiologists can proffer value via collaboration with primary-care providers. In the white paper, Allen et al report that
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RADIOLOGY | The ACO Play
The federal CMS ACOs are all about primary care, by law. Commercial payors are a bit more flexible, but not that much; they won’t go for radiologists driving primary care. —Michael Silver, PhD Sg2
input from radiology is effective in solving a large percentage of clinical problems seen in an ACO setting—without the need for referral to a specialist. They cite the example of a patient who sees his primarycare physician for recent-onset chest pain. The physician suspects coronary-artery disease, but is also concerned about other conditions (including pulmonary embolism, aortic dissection, pericarditis, and penetrating atherosclerotic ulcer of the aorta).
Instead of being referred to a cardiologist for a lengthy, expensive workup, the individual is sent to a radiologist, who performs one study (in this instance, triple–rule-out CT angiography). In a majority of cases, this either establishes a diagnosis or confirms the absence of a significant problem. Only if significant cardiac disease is revealed is the patient referred to an appropriate specialist for treatment. Assistance with IT constitutes another element of added value. Radiology’s
Imaging 3.0: The ACR’s Cultural Revolution
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he ACR® holds that successful participation in accountablecare organizations will be heavily predicated on combining timely, high-quality image interpretation with a new set of services designed to deliver value and cost effectiveness. Replacing the emphasis on RVU productivity with the ability to provide cost-effective care will entail a cultural change, as will having outcomes replace the emphasis on defining productivity as the number of exams interpreted. To help practices navigate the cultural transition— as well as the migration to new payment models—the ACR has launched Imaging 3.0. Described as a network of tools and services designed to optimize imaging at the point of care, Imaging 3.0 comprises four key elements. Topping the list is a self-directed work plan that radiologists can employ, both as individuals and in their practices; the plan guides physicians through the five pillars of appropriateness, quality, safety, efficiency, and satisfaction— and the myriad opportunities to embody them in patient care. A second component consists of a series of such resources as case studies, white
papers, articles, and sample documents; it includes plans that lay out how other constituents have led the way in making similar revolutionary cultural changes in their organizations and practices. Other components encompass expert advice from leading radiology, technology, and business consultants, as well as a network of Imaging 3.0 providers for collaboration and day-today support. According to the ACR, using Imaging 3.0 will enable radiologists to serve as advocates for their patients by assisting providers in the selection of the most appropriate exams and by promoting consultation with other physicians within a framework of shared decision making. It also will make it possible to empower patients to understand their many imaging options and to participate in selecting the best exams, in keeping with their particular clinical circumstances. It will ensure transparency, too, by imparting to patients a clear understanding of imaging results and by encouraging radiologists’ active participation in patient care as engaged members of a given health-care team. —J. Ross
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“long history of doing innovative things with technology,” Whitfill says, “long before other specialties got started”—as exemplified by its advances in digitizing images and reports—places imaging providers in the perfect position to proffer added value on the IT front. “There is tremendous need for such skill in the ACO model,” Whitfill states. The IT piece must be an integral component of value that includes not only input into the technologies that should be implemented by the ACO in question, but also the administration of CPOE as its decision-support hub, the active management of the ACO’s IT infrastructure, and (perhaps even more important) support for the exchange of information across a wide variety of integrated platforms and sites. Debunking Myths There also are myths to be debunked, the most prevalent being that radiology is more of a cost center than a revenue producer. Presenting ACO organizers with a comparison of costs incurred and benefits achieved, using industry benchmarks, is critical. Although some have argued that there exists no place for outpatient imaging centers within the ACO model, quite the opposite is true. As Davis and Allen point out, such facilities (arguably) cost less to operate than do their hospital-based counterparts; by affording easy access to imaging services at conveniently situated locations, they also enhance the overall health-care experience for ACO patients. When outpatient imaging centers are a component of an ACO, member hospitals shoulder a lighter imaging-services burden and can devote the bulk of their efforts to handling, in a timely manner, the imaging needs of inpatients and those seen in the emergency department. Imaging centers, however, cannot assume that these benefits are sufficient to win over ACOs. Rather, it is incumbent upon them to sharpen their persuasive edge by demonstrating additional value through participation in accreditation, utilization-management, and radiation-safety programs, as well as by becoming multimodality centers and by documenting the absence of
any financial conflict of interest for an ACO affiliation. Don’t assume that a given potential alliance with one ACO will prove as viable as a given potential alliance with another ACO, in either the shorter or the longer term. Conversely, Davis says, no matter how attractive the value proposition offered by a radiology entity is—at least, from the perspective of its own management—it might not be the right fit for every ACO prospect. The proposition of value for the ACO itself, for the patient population, and for the payors does not always mesh with the objectives and needs of a particular ACO; a lack of alignment will only lead to headaches down the road. For this reason, Davis entreats practice leaders to conduct a comparison of their groups’ value propositions with the goals and objectives of prospective partners, prior to moving forward with any ACO agreement. Michael A. Silver, PhD, vice president of Sg2, a health-care–intelligence company, concurs, adding that it is important for radiology providers to ask themselves many questions, instead of blindly attempting to shoehorn themselves into an alliance that might not be an appropriate one. “For example, does the group have sufficient physician resources and management expertise?” Silver asks. “Do the other physicians seem to have a passion for weighing cost and quality issues over time? Are electronic medical record and performance data reviewed and acted upon, and does there appear to be a willingness to adhere to patientcare and -safety guidelines? Just because a particular ACO is forming and available doesn’t mean you want to join it.” Silver adds that radiologists should also disabuse themselves of the notion that they can, or should, attempt to circumvent compatibility and other issues by forming their own ACOs. “It’s not going to happen,” he says. “The federal CMS ACOs are all about primary care, by law. Commercial payors are a bit more flexible, but not that much; they won’t go for radiologists driving primary care.” Preparing for the Challenges While the importance of adding value to the equation should not be underestimated,
The prevailing sentiment should be that risk sharing is acceptable; we’d be happy to take the risk—but if you put us at risk, you have to give us the authority to manage it and compensate us accordingly. —W. Kenneth Davis Jr, JD Katten Muchin Rosenman LLP
Radiologists need to forge arrangements with ACOs under which they receive a share of revenues to compensate them for managerial and administrative functions. It’s best to do this with shared risk or shared savings, depending on whether set targets are met. —Bibb Allen Jr, MD, FACR
the degree to which radiologists understand and plan for the risks inherent in the ACO model also has a bearing on their success. Radiologists working in an ACO setting will undoubtedly see reduced revenues from interpretations, based on the shift away from volume-based compensation and toward reimbursement that values quality and appropriateness. To compensate, they will need to garner reimbursement for nonclinical activities such as utilization management, enterprise administration, quality control, technologist supervision, equipment selection/optimization, and the education of colleagues outside the radiology realm. “The prevailing sentiment should be that risk sharing is acceptable; we’d be happy to take the risk—but if you put us at risk, you have to give us the authority to manage it and compensate us accordingly,” Davis states. Allen adds, “Radiologists need to forge arrangements with ACOs under which they receive a share of revenues to compensate them for managerial and administrative functions. It’s best to do this with shared risk or shared savings, depending on whether set targets are met.” In certain instances, he adds, ACOs might attempt to compel radiologists to
participate in capitation arrangements. To avoid difficulties, he advises, providers should ensure that the capitated payments that they receive are based on past fee schedules and have built-in risk corridors. Moreover, smaller imaging groups might find that ACOs do not generate the bulk of their business—and that they do not have as much negotiating power with ACOs as their larger counterparts have. Consolidation or integration with larger groups appears to be a panacea for ills of this type. “Among the most important things to remember is that ACOs are still in the training-wheels stage,” Silver concludes. “Like others, this model is evolving, and radiology will need to evolve with it.” Julie Ritzer Ross is a contributing writer for Radiology Business Journal. Reference 1. Allen B Jr, Levin DC, Brant-Zawadzki M, Lexa FJ, Duszak R Jr. ACR white paper: strategies for radiologists in the era of health care reform and accountable care organizations: a report from the ACR Future Trends Committee. J Am Coll Radiol. 2011;8(5):309-317.
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CLINICAL ANALYTICS | Quality to Outcomes
From Quality to Outcomes:
Deploying Clinical Analytics The movement to use analytics tools to drive improvements in the quality, utility, and reliability of medical imaging is gaining momentum By Joseph Dobrian
A
lthough radiology has employed clinical analytics for more than a decade, the field is in its infancy. Nonetheless, the possibilities are tantalizing—if technological, economic, political, and interoperability hurdles can be cleared. David Ecanow, MD, is the radiology department’s vice chair for quality at NorthShore University HealthSystem (Highland Park, Illinois). He reports that analytics methods are used across the spectrum of his responsibilities: to measure and improve access, utilization, exam quality, safety, interpretive accuracy, outcomes, communication, basic patient care, and regulatory compliance. “By measuring and analyzing the reasons for exams, we attempt to ensure that the correct test is ordered and performed,” he explains. “For example, we tracked the reasons for CT exams ordered with and without contrast, and we were able to decrease unnecessary exams.” To ensure exam quality and safety, Ecanow says, his team has been tracking CT-exam radiation dose by protocol and has used that information to reduce dose across multiple types of exams— particularly in pediatrics, obstetrics, and urology. By tracking peer review of exam interpretations, as well as clinical and pathology outcomes, Ecanow’s team is better able to pinpoint difficult diagnoses and generate inservice education to sharpen accuracy. “We audit specific critical-exam or critical-result communications to help ensure timely and appropriate
communication of results,” he adds. “We audit our mammography services extensively for both exam quality and clinical outcomes.” Improving the Product Woojin Kim, MD, is interim chief of the division of musculoskeletal imaging at the Hospital of the University of Pennsylvania in Philadelphia. He says that clinical analytics helped him increase his section’s study RVUs by 16%, and he
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also has used analytics to drive quality improvement for reports. “It’s important to remember that reports are a radiologist’s main product,” he emphasizes. “For example, by using analytics tools that can leverage the power of natural language processing, I’ve been able to monitor the laterality errors in radiology reports.” Kim says that his team—after discovering the presence of errors that were being overlooked by coders—has implemented a process for continuous
CLINICAL ANALYTICS | Quality to Outcomes
The tool keeps reminding us, if a given report with an error does not get revised. It also keeps track of the time it takes for each report to be corrected. These functions contribute to enforcing and improving compliance. —Woojin Kim, MD
monitoring that allows rapid error correction (using a tool that was developed for the department and subsequently commercialized). “The tool keeps reminding us, if a given report with an error does not get revised,” he explains. “It also keeps track of the time it takes for each report to be corrected. These functions contribute to enforcing and improving compliance.” Within a month of implementing that monitoring process, Kim notes, the error rate dropped by 48% at one of the sites within the system—purely, he insists, because people knew that the process was in place. Analytics can help an organization go beyond the typical measurements to make a meaningful impact on patient care, Kim adds. “The more advanced analytics tools, combined with natural language processing, can mine the radiology reports to detect various quality elements like laterality errors, degree of uncertainty, gender errors, coding errors, and follow-up recommendations,” he says, increasing the referrer’s confidence in the radiologist’s report. “Because many referrers and patients don’t know their radiologists, small errors in reports can have a significant impact on their confidence in their radiologists,” he notes.
Wassilchalk notes, “Our radiologists will evaluate exams on a peer-review basis and will measure concordance or discordance between interpretations. From a patient-safety perspective, dictations contain key clinical findings that are critical in nature—that need to be reported to the ordering physician in a very timely manner to effectuate clinical intervention. Images, as well as clinical findings, are captured and stored as part of the patient’s electronic record.” Down the line, Wassilchalk says, his department’s goal is to determine whether certain exams for particular diagnoses are useful in the sense of having an
The Data Path Dan Wassilchalk, executive administrator of the department of radiology at the University of Pittsburgh Medical Center in Pennsylvania, views clinical analytics within the broad sweep of the entire radiology workflow and how it connects with each patient’s data path— from registration to exam acquisition, interactions with other departments, results delivery, and follow-up care. 34 RADIOLOGY BUSINESS JOURNAL | April/May 2013 | www.imagingbiz.com
impact on treatment. Going forward, he adds, clinical analytics could be used to improve treatment across the board. “We hope to reduce the number of repetitive exams and reduce or eliminate exams that are not useful,” he says. “We want to pool radiology data with clinicaloutcomes data to improve the health-care system further. Pay for performance will be dependent on reducing admission rates and improving the quality of care.” Wassilchalk adds that one of the biggest challenges is breaking down data silos to promote interoperability among information systems. “We’re working hard to pull it together to give the analytics more power,” he notes. A colleague of Wassilchalk, Christopher Deible, MD, remarks that these data could be fed back to radiologists to show them how they are doing. The best example of this sort of information use, Deible says, is time stamping. “By doing that, we improve patient satisfaction and throughput, from exam completion to finalization of the report,” he says. “Timing is everything, and
the sooner we can provide an effective diagnosis, the faster the patient can move through the process to discharge. We want to avoid duplication of effort. We also want to use analytics to improve the quality of documentation and reporting of critical results—to make sure that if I make a critical finding, I communicate it.”
Only recently have the EMR, RIS, and national databases begun to coalesce into a useful matrix of data. The tools to mine those data robustly are only on the cusp of utility. —David Ecanow, MD
Supporting Decisions Clinical analytics can be used in the interpretation process to support radiologists’ decisions. Bradley J. Erickson, MD, PhD, director of radiology informatics at the Mayo Clinic (Rochester, Minnesota), reports that his team uses common mammography and breast MRI computer-aided detection tools, as well as more novel internally developed tools (such as an algorithm for detecting aneurysms from MR angiography data). He says, “Computer-aided detection is a subset of decision support, usually focusing on detecting lesions. Examples we use today include breast-lesion detection and polyp detection on CT colonography, and there are several 3D laboratory applications (such as liver- and kidney-volume measurements) that are important for surgical decision making.” He adds, “We’ve developed additional analytics tools that are helpful for detecting significant—but subtle— changes in brain tumors, intracranial aneurysms, and interstitial lung disease. Those hits are then sent to the 3D system and are rendered much as potential polyps are highlighted in the advanced visualization product,” he explains. Erickson’s department also developed and uses a brain-tumor change detector that highlights very subtle changes that are not easily perceived by humans, as well as an tool that characterizes and measures the amount of interstitial lung disease seen on CT exams. “All of these are visual tools that highlight things that we want to make sure the radiologist pays close attention to; however, in the end, the radiologist decides whether there’s a disease, and what to do about it,” Erickson says. “The tools are based on imaging data—from CT or MRI—and at present, we don’t include other information. We’re working on improving brain-tumor decision
support that will include nonimage data such as the tumor type and the nature of the therapy that a patient has had.” The field still has plenty of room for improvement, Erickson says. The number and quality of images being produced continue to increase, and better tools are needed to analyze them. The Compliance Juggernaut Richard Grzybowski, MD, a radiologist with Diversified Radiology of Colorado (DRC) in Lakewood, is chair of the practice’s quality committee. Using data to improve clinical performance probably began with the introduction of the ACR BI-RADS® system, Grzybowski believes. With widespread adoption of enterprise PACs and RIS, radiology departments and practices became the custodians of enormous caches of clinical data. Ecanow agrees that the BI-RADS system represents radiology’s earliest foray into clinical analytics, but he says that the system could be improved through integration with enterprise-level information systems. “Computerized tracking of multiple quality elements has been in place for at least 15 years,” he notes. “It’s progressed to a state of maturity where it’s a routine method for benchmarking our clinical quality, managing resources, and providing a high volume of the best quality of subspecialized care. The future lies in more automated data entry, with some of the elements that are now manually entered being more reliably shared from the overall electronic medical record (EMR).” “Clinical analytics is still in its early phases of utility,” Ecanow remarks. “Only recently have the EMR, RIS, and national databases begun to coalesce into a useful matrix of data. The tools to mine those data robustly are only on the cusp of utility. As these tools become more widespread and routine, we hope
that they will allow analytics to have an impact on health-care providers closer to the point of contact with patients.” Acting on Information The ways in which the information gathered is acted upon, Erickson says, are legion. One example is volume measurement for surgical planning. In cases of liver tumors that must be resected, or if using a living donor for liver tissue is being contemplated, it’s critical to know whether the amount of tissue that will be left will suffice to keep the patient (and donor, if applicable) alive. “One is further restricted by having to resect along segmental boundaries,” he adds. For liver donors, Erickson says, stateof-the-art clinical analytics can take lifethreatening guesswork out of the equation. “Another example is that some computable properties of a brain tumor correlate with molecular markers that are important for predicting responsiveness to certain classes of therapies and for predicting overall expected survival,” he says. Erickson predicts that the next big steps in clinical analytics will be integration and prediction of molecular properties. “Molecular imaging is a hot area of interest, and while some forms allow direct visualization of some molecular marker, many require additional processing or integration of other information to be useful,” he says. Ecanow points to CT radiation-dose auditing as the clearest example of how data mining can produce actionable clinical results. “A calculated dose from each CT exam is entered into the RIS,” he explains. “We then routinely audit multiple data points—patient age, exam type, dose, and so forth—letting us pinpoint exam protocols that can be improved (or practice sites or staff that need more focused improvement). By
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CLINICAL ANALYTICS | Quality to Outcomes
Analytics will improve by getting a richer set of information to work on: more information about the patient and about the health-care environment. In the future, we’ll want genetic and epigenetic information, and in turn, we’ll start providing some of that type of information. —Bradley J. Erickson, MD, PhD
addressing those exam protocols, we’ve reduced radiation dose, particularly in pediatric and urology patients, while retaining excellent diagnostic quality.” New Frontiers and Tools Most of the data currently used in radiology to perform clinical analytics are sourced at the department level, but richer meaning and benefits will be derived through access to information beyond the department—or practice— walls. Barriers to access are technological, political, and economic in nature. “By leveraging other systems (such as in pathology), one can perform tasks like pathology–radiology correlation analytics,” Kim says. “In fact, one’s ability to obtain truly meaningful analytics can be vastly improved by tapping into data from other specialties in medicine, such as pathology and cardiology.” Erickson says, “Analytics will improve by getting a richer set of information to work on: more information about the patient and about the health-care environment. Information about the patient that we need today includes the results of simple laboratory tests, such as those for creatinine level or pregnancy. In the future, we’ll want genetic and epigenetic information, and in turn, we’ll start providing some of that type of information.” Ecanow acknowledges that the origin of most of the information that he is analyzing is the RIS. “As we gain more experience in working with the overall EMR and hospital quality infrastructure, that pool of information will widen,” he says. Interoperability among information systems remains an obstacle to data
sharing. “More robust data-mining tools are slowly becoming available, but haven’t yet hit their stride,” Ecanow says, adding that simpler, more effective tools for communicating data (and then auditing that communication) are needed. The Golden Ring Despite the challenges of integrating clinical analytics with existing technologies, Grzybowski believes that the benefits to be derived outweigh the time and development efforts required to overcome the barriers. “Access to clinical data isn’t the limitation anymore,” he says. “The industry will see more transparency in quality analysis and decision support, with the growing access to clinical data. The use of clinical analytics is incredibly beneficial to patient care. Health care hasn’t pursued the benefits of data integration because it’s largely uncompensated time and expense, given current payment models. This is changing, though, as systems become more uniform and data sharing becomes more standardized.” Another factor fueling the need for clinical analytics is health-care reform: Health care is transitioning from fee-forservice to value-based payment models, for which using clinical analytics is likely to be an imperative. “As people focus more on population-health management,” Kim notes, “data mining and analytics will take us to new frontiers, allowing us to mine data we could not before and to discover things we could not before—at a much faster pace.” Joseph Dobrian is a contributing writer for Radiology Business Journal.
36 RADIOLOGY BUSINESS JOURNAL | April/May 2013 | www.imagingbiz.com
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One Day Physician Leadership Track
Physicians Uniting Around Quality, Appropriateness and Efficiency Sunday, July 28 at the AHRA Annual Meeting & Exposition Minneapolis Convention Center, Minneapolis, MN 8:30 a.m. to 4:00 p.m. Program Faculty: Jeff Patton, M.D. • Rich Duszak, M.D. • Tim Myers, M.D. Woojin Kim, M.D. • Chad Calendine M.D. • Carl Black, M.D. and Jim Jensen Zeke Silva, M.D. • Pat Basu, M.D.
Learn more at: www.ahraonline.org/physiciantrack
Designated sessions of this program will be eligible for RLI credits based on competencies outlined in the Radiology Leadership Institute Common Body of Knowledge™ (CBK).
For Leaders in Medical Imaging Services
PACS Continuity in the Eye of Hurricane Sandy: Bellevue Hospital Center By Cat Vasko
A Conversation With Mark Alfonso, MD:
What Is Patientcentered Radiology?
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f the triple aim—improved access to better-quality health care at a lower cost—is the goal of health-care reform, then patient-centered care is its soul. Throughout the Patient Protection and Affordable Care Act, the authors took precautions to protect patients from the abuses of 1990s-era managed care, when profits appeared to trump patient care. What, then, is patient-centered radiology? For the RSNA, which made patientcentered radiology the theme of its 2012 annual meeting in Chicago, Illinois, it meant inviting patients to give keynote talks at the opening session, even though
Bring on the BYOD: Providing Mobile Access to Patient Data By Cheryl Proval
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hen it comes to mobile access to patient data, CIOs have two choices: Provide a secure access method, or continue to plug the hole in the dike with their fingers—and pray. With smartphone use among physicians at 98%, according to a 2012 report from Spyglass Consulting, attending and referring physicians who find themselves locked out of mobile access to patient data are likely to be looking for workarounds to circumvent hospital policy.
By Cheryl Proval
some of what they said was hard to hear. Radinformatics.com puts that question (and more) to Mark Alfonso, MD, president of one of the nation’s most successful, respected, and tech-savvy practices, Riverside Radiology and Interventional Associates (Columbus, Ohio), and an early adopter of FUJIFILM Synapse® PACS. Alfonso details a vision and pathway in which imaging informatics is central. RADINFORMATICS: What is patientcentered radiology, and how is it different from what we are doing now?
Continued at www.imagingbiz.com/radinformatics
Health-care Data in the Public Domain: Empowering Patients By Cat Vasko
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hen Hurricane Sandy and its aftermath devastated New York, New York, in October 2012, perhaps no one was more vulnerable than the patients needing care in area hospitals. Eli Tarlow, CIO of the city’s Bellevue Hospital Center (BHC), recalls, “It was the best of times and worst of times—a natural event that no one could have prevented. You really see the best of your staff in moments of crisis, and that held true during Hurricane Sandy. Staff members at all levels volunteered to do anything necessary, from bringing needed supplies up and down many flights of stairs to helping with preparing or delivering food for patients.”
Continued at www.imagingbiz.com/imagingbiz_ ejournal
Doubling Down on Data: Meta-analyses of Productivity and Quality By Cat Vasko
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Continued at www.imagingbiz.com/health_it
Continued at www.imagingbiz.com/radanalytics
here are two sides to the aggregation and use of data in health care, according to Lynn Gibson, vice president and CTO of Christus Health, Irving, Texas. The first, and most in focus, is the provider’s; the second, less emphasized (but equally important) is the patient’s. “Health care is on a rapidly changing path,” Gibson says, “and data-driven analysis is necessary for both the caregiver and the patient. We have to be able to collect the pertinent information to support both sides and make it available to both the patient and the physician.”
nfluenced by emerging technology and regulatory changes, the role of the radiology-group CIO has undergone a dramatic shift in recent years: Wayne Davidson, CIO of Quantum Imaging & Therapeutic Associates, Inc (Lewisberry, Pennsylvania), a 40-radiologist practice, says, “In recent years, the focus has really become efficiency because of background factors like declining reimbursement. That drives the business to try to do more with less, and that goal is laid on the shoulders of the IT department.”
Continued at www.healthcxo.com
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