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Gathering and Using Data for Value-Based Health Care Initiatives:

by | Larry McNutt

Fifth in Six-Part Series

How Data Can and Should Define Strategies

Benefits Magazine v 49 no 6 Jun 2012 pp 30-36

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Plan sponsors (employers, board of trustees, human resources leadership) are facing their greatest challenges in decades in maintaining effective health insurance for plan participants. Because of national health reform, state-based

exchanges and local/regional health care system consoli-dation, the medical-economic landscape is in the throes of change not seen since the implementation of Medicare nearly 50 years ago.

Plan sponsors have a range of available responses. Some will choose the “do-nothing” approach in the expectation or hope that upcoming national elections will result in further changes to the rules and operating environment. Others will opt for a “throw some mud at the wall and see what sticks” approach that will include haphazard plan design changes in reaction to deteriorating plan reserves or increased drag on corporate or public treasuries.

Others, aided by insights provided in this series of articles1 and other sources,2 will select a thoughtful, evidence-based approach to developing a clear understanding of “best prac-tices” in design and administration of plans. This approach will be targeted at caring for the current population’s health needs while focusing diligently on shaping the future health status of the plan’s covered population.

In this fifth article in the series, we will pull together sev-eral key elements of a data-driven approach and offer sugges-tions for assessing the feasibility of a value-based design. The objective of this article is to provide guidance in developing a data-driven, evidence-based decision framework for imple-menting and maintaining value-based health coverage.

In the sixth and final article, in the July issue of Benefits Magazine, consultants John Riedel and Claire Brockbank will write about how plans and employers of smaller size, with ac-cess to limited resources, can pursue a value-based approach.

Keys From Earlier ArticlesIn the introductory and first articles, Paul Hackleman set

the stage by challenging us to look at data as a means to an end, not an end in and of itself. He focused our attention on using data to design purposeful, relevant initiatives and to produce results, not just to raise awareness of problems that exist in our health plans. He alerted us to the opportunities for improvement in plan design and operation by promoting best practices and using standardized measures and compar-isons to assist in identifying areas for improvement. Finally, Hackleman reminded us that focusing on a small number of expensive cases can make a significant difference in a plan’s financial performance.

In the second article in the series, Lewis E. Devendorf led us through the ways in which plan sponsors can set a base-line description of a plan’s opportunities for improvement through comparison of key data elements to appropriate peer-group plans and to a plan’s prior-period performance. He cautioned us to take care in selecting both individual metrics and plans against which we would compare our-selves, noting that differences in group demographics, eligi-bility and participant income levels may lead to inconclusive or misleading comparisons. Devendorf also provided useful advice in obtaining data from vendors who might initially resist requests for claims and demographic data.

The third article in the series discussed the diverse land-scape of providers. Noting variations in data availability and data quality among physicians, hospitals and other care settings, we cast light on the challenges presented to plan sponsors seeking to understand the quality of care deliv-ered to plan participants. We also cautioned that methods of determining the value of care being purchased by health plans are in their infancy. No “gold standard” of measure-ment or comparison is in place yet. We described the need

This is the fifth article in a series intended to help employers and multiemployer funds collect health data, understand what data might tell them about plan participants’ current and future health status, and use that information in plan design.

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to aggregate data from all sources in-cluding physician claims, pharmacy, dental and vision claims, as well as insights gained through health risk as-sessments and clinical data that may be available through electronic medi-cal records.

In the latest article, John W. Bar-ton and Susan Manning prepared us for the breadth and depth of a data- focused effort in evaluating value-based health care design and imple-mentation. Drawing from their sig-nificant experience in implementing and designing value-based benefits, they exhorted us to “measure, moti-vate and evaluate.” Thoughtful gather-ing and analysis of data about the be-havior of plan participants and health care providers, knowing how those behaviors affect a plan’s sustainability,

and the use of data to change behavior where necessary and appropriate will all help sponsors preserve the physi-cal and mental health of plan partici-pants and the financial health of the plan. Finally, the authors pointed out

that higher cost care is not indicative of higher quality care. In the future, data analysis will provide an objective means of demonstrating this to plan participants and to providers serving those participants.

learn more >>EducationTrustees and Administrators InstitutesJune 11-13, San Francisco, CaliforniaFor more information, visit www.ifebp.org/trusteesadministrators.What Your Data Tells You About Health Care Cost Driversby Ted Carlson, CEBS. 2009. International Foundation CD-ROM.For more details, visit www.ifebp.org/books.asp?PS003.

From the BookstoreZero Trends: Health as a Serious Economic Strategy by Dee W. Edington. University of Michigan. 2009. For more details, visit www.ifebp.org/books.asp?8884.

. . . specializing in multiemployer benefit plansPension Health & Welfare Other• General Consulting • General Consulting • Mergers & Spinoffs• Annual Actuarial Valuations • Annual Reports • Annuity & 401(k) Plans• PPA Compliance • Reserve Calculations • Documents, SPDs & Amendments• Real-Time Modeling • Real-Time Modeling • Research Publications• Benefit Improvement Studies • Medicare Part D Attestation • HIPAA Privacy & Security• Employer Withdrawal Liability Studies • ASC 965 (SOP 92-6) Valuations • Vendor RFPs

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www.unitedactuarial.com

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Putting It All TogetherArmed with the insights of these previous articles, it is

time to build a cohesive template to assist plan sponsors—es-pecially large plan sponsors—in developing their own data-focused, evidence-based approach to value-based benefits.

Let us remind ourselves of the definition of value-based benefits developed by the International Foundation:

“Value-based health care (VBHC) is a holistic and system-atic approach to establishing a true culture of health for orga-nizations and their employee populations across the health risk continuum. VBHC strives to remove barriers and align both financial and nonfinancial incentives and rewards for living healthy and productive lifestyles, while using high- value prevention, health enhancement and health care servic-es. VBHC extends beyond health care benefits to include the design, implementation, and continuous evaluation of high-value approaches for improving employee health and well- being while reducing the need for high-cost medical services.”

Achieving the objectives of removing barriers, aligning incentives, rewarding healthy living and using high-value services in a holistic and system-level approach will be chal-lenging. It will require a process for defining the problem, evaluating the performance of the health plan in addressing the health issues of the covered population, and understand-ing the relevant socioeconomic challenges that may other-wise thwart planned interventions.

Assessing Readiness/Ability/Willingness to Implement VBHC

Stephen R. Covey’s book, The 7 Habits of Highly Effective People, reminds us to “begin with the end in mind.” This tenet holds in considering design for a data-driven, value-based health plan. Once the “vision” is clarified, it is critical to get the buy-in of all who will have a hand in designing, communicating, implementing, evaluating and adapting this new approach to health plan design and financing.

Executive suites, boards of trustees, public entity leader-ship and other decision makers must come together in sup-port of the value-based concept. We referred earlier to a couple of approaches to the problems health plans face—the “head-in-the-sand” and the “mud-at-the-wall” approaches. There may be some among a health plan’s leadership who fit into one of these categories. Identify them and turn them. It will make the process much less complicated and much more productive.

Current Areas for Data Gathering and AnalysisIn determining data to be gathered, organized, analyzed

and communicated, it is important to remember that the state of the art in data availability and analysis is just coming into focus. Also, we must be mindful that the task of adapt-ing a value-based design to the ever-changing landscape of health care is as much art as science.

Data that are important today in understanding how to deal with diabetes, cardiovascular disease, various forms of cancer, costly pharmaceutical treatments and an aging work-force will likely change in the next few years. Almost cer-tainly, the “value” proposition in value-based benefit design will continue to evolve. To stay ahead of the curve in treating today’s participant/patients and working to keep tomorrow’s group healthy, we will need a framework that can be rapidly adapted, in which new data sources and new approaches for measurement and analysis are being continuously incubated to identify, analyze and apply new knowledge and methods.

A cautionary reminder: Plans of any size will have some statistics drawn from a small number of observations. Some providers may see only a handful of participants in a year’s time. Be careful when drawing conclusions from small sam-ples. These situations often lead to incorrect conclusions about provider characteristics that could be damaging to the plan in the long run.

Take, for example, a primary care physician who saw only three diabetic patients covered by a particular plan and failed to order an HbA1c test for blood sugars for any of them. That provider may be painted with a “substandard practice” brush. However, if these patients’ data indicate that they are other-wise well-managed, it is likely they are receiving diabetic care (including routine A1c testing) from another provider, per-haps a specialist such as an endocrinologist. Remember the

takeaways >>•  Getting all of a health plan sponsor’s decision makers to support a

value-based concept will make the process easier.

•  Plan sponsors need to be nimble and flexible, realizing that the kind of data that is important now will change, and that new approaches to measure and analyze data are constantly evolving along with the availability of data.

•  Take care in interpreting data, especially data from a small number of observations.

•  Many sources are available to help identify treatments and diag-noses that are candidates for application of value-based design.

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TABLEIdentifying Individuals for Outreach and Care NavigationIdentifying characteristic Purpose for identification How to put this information to useLarge numbers of diagnostic imaging Low-back conditions are often treatable with Plan design may include significant (MRI or CT) in cases involving back pain lifestyle changes including weight loss or participant copayments if imaging is or postdiagnosis/presurgery imaging of conditioning and are often overtreated employed where not otherwise indicated. musculoskeletal conditions with surgery following imaging, particularly The Washington State Department of in physician-owned imaging centers. Labor and Industries has developed Orthopedic conditions treated with surgical evidence-based guidelines for advanced means are often not better informed with imaging that may provide a useful imaging than with gross examination. reference in considering plan design

and treatment guidelines in this area.

Prescription drug fills for high-cost brand Participants may benefit from therapies Plan design may implement a step-therapy and specialty drugs for which other first- having a better established track record program employing predecessor treatment line therapies exist and better understood efficacy and side options as a requirement before the plan effects than new-to-market therapies. will cover newer, higher cost therapies. Plan may employ a “quality-adjusted life years”

assessment in determining whether to cover new therapies and, if so, at what level of coinsurance.

Rate of preventive care visits and Participants may benefit from redesigned Plan design may include preventive care screening present in recent historical preventive care benefits leading to prompt benefits including annual physicals and claims data diagnosis and treatment of emerging conditions diagnostic testing that are not subject to or identification of lifestyle or other patient deductibles or coinsurance. The U.S. characteristics that, if properly controlled, Preventive Services Task Force has lead to improved prevention of future disease. developed clear, evidence-based recommenda-

tions that can inform the plan.

Cost of palliative and end-of-life care Participants may benefit from improved Plan may cover “end-of-life” and “comfort in recent claims data “comfort care” benefit design while at the same care” without subjecting the patient to time curbing inappropriate continuing treatments deductibles, copays and coinsurance. that do not improve quality or length of life in patients suffering from terminal conditions.

Compliance rates within the participant Identify population-based metrics for Identify providers delivering high-quality population for evidence-based care to commonly measured quality-of-care patient treatments that are aligned with the manage chronic disease and prevent indications. evidence regarding treatment and deterioration and complications. This care prevention. Plan may customize or tier includes weight management, HbA1c and provider networks to provide high-quality- cholesterol testing, eye examinations, performing physicians and care settings at kidney disease screening and consistent a higher reimbursement level, particularly use of age-appropriate medication to in settings providing overall management control asthma, diabetes or hypertension. of care for participants assigned or selecting these care settings.

Participants who have not had a primary These participants are likely to lack a “primary Communicate to participants the value of a care visit in the past two years care home” and are at higher risk for inappropriate primary care home and maintaining a use of emergency rooms, duplicate and/or consistent health record of examination unnecessary testing and visits to specialists and and preventive care. Plan designs may undiagnosed conditions associated with later include low- or no- copay primary care emergence of chronic disease. office visits for two or three visits per year. Plan designs may also include incentives

for selecting and maintaining a relationship with a primary care provider.

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TABLEIdentifying Individuals for Outreach and Care NavigationIdentifying characteristic Purpose for identification How to put this information to useParticipants who have more than The participants may lack a consistent primary Communicating to participants the one hospital-based emergency room care relationship leading to suboptimal importance of regular preventive care. visit in a year preventive care and late diagnosis of preventable Plan designs may include low or no or controllable health conditions including copay for a limited number of primary asthma, urinary tract infections, headaches care visits. Plan design may also and other conditions generally believed to be include significant copays for repeated treatable outside of emergency room setting. use of the emergency room in a defined period of time (e.g., one year).

Participants with two or more inpatient Participants may be at risk for future Postdischarge followup calling to admissions for the same condition admissions due to poor understanding of participant and family to review within the past two years postdischarge medication or rehabilitation understanding of medications and requirements. rehabilitation requirements, home-care

requirements and followup provider appoint-ments. Plan design may include voluntary or mandatory case management until demon-strated stability.

Participants with a diagnosis of Participants may be at risk for later Plan may provide low- or no-copay “overweight” or “obese” without an developing diabetes. nutrition counseling and meal accompanying diagnosis of diabetes planning. Plan may provide low- or prediabetes or no-copay sleep studies to diagnose sleep

disorders commonly associated with “over-weight” or “obese” conditions.

Participants with a diagnosis of diabetes Participants may be at risk for numerous Plan design may include low- or no-copay and indications of suboptimal debilitating chronic diseases and preventable diabetic supplies and insulin, including management of the diabetic condition complications. commonly preferred dispensing methods.

Plan may also provide low or no copays for cholesterol testing and medication, nutritional counseling or other services related to diabetes management and associated risk of cardio-vascular disease, as well as low- or no-copay diabetic education.

Participants identified through claims or Participants may be at risk for increased Plan may provide a “no-fault” multiple health risk assessments as smokers or incidence of respiratory diseases including asthma quit attempts tobacco-cessation program smokeless tobacco users and COPD as well as a wide range of cancers supported by low- or no-copay prescription and heart disease. drug quit aids.

Participants identified with diagnosis Participants may be at risk for various Plan may provide for no- or low-copay of hypertension cardiovascular conditions including cardiac generic prescription drugs to control events, kidney failure and stroke. hypertension.

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phrase popularized by Mark Twain: “There are three kinds of lies: lies, damned lies and statistics.” Take care in interpreting the data.

Identifying Subpopulations Needing Special Benefit Design Consideration

The table provides examples of health conditions and treatment characteristics that are the focus of today’s value-based approach. It includes characteristics the data might identify among groups of participants within a plan, why those characteristics may be occurring and how a plan sponsor might use the information in value-based plan design.

There are many sources identifying treatments and diag-noses that are candidates for the application of value-based design. One example is the list of value-based services identified by the Oregon Health Services Commission. The list is available at www.oregon.gov/OHPPR/HSC/docs/VDS.pdf.

In a February 2011 report on reducing inappropriate use of emergency room facilities, the Washington State Hospital Association references a Medi-Cal-produced list of services within California’s Medicaid program that should rarely if ever be treated in an emergency department setting. That list

and a complete discussion of the issues is at www.wsha.org/files/127/ERReport2.pdf. These may be areas worth consid-ering for a value-based approach as well.

ConclusionWhen considering a data-driven, evidence-based struc-

ture for plan design and operation, it may be helpful for your team to begin by considering some of the following ques-tions:

• Do we have a clear understanding of why we are con-sidering VBHC?

• Is our population (employees, plan participants, HR department, corporate finance, trustees) open to im-plementing VBHC-based changes in order to gain greater understanding of cost and quality drivers and factors underlying our plan’s performance?

• Do our participants respond more effectively to car-rots or sticks in the face of limited plan resources?

• Do our participants understand the need to become more actively engaged in their health care and well-being, including greater accountability for both health care decisions and suboptimal lifestyle choices that ad-versely impact the plan?

• Do we have, or can we achieve in a relatively short time, access to the data necessary to implement a data-driven VBHC strategy that is specific to the health profile of our population? If not, can we explore alter-natives to existing vendor relationships?

• Do we possess or have access to well-informed analyti-cal talent to perform analysis of current data?

• Do we have the resources to monitor and adapt our program in the future to the changing landscape of value-based opportunities?

If you can answer “yes” to most of these questions, you may be further along in the development of a value-based approach than you had thought.

Endnotes 1. The articles in this series, along with a snapshot of sample data re-ports and service definitions, are available to members at www.ifebp.org/news/FeaturedTopics/valuebasedhealthcare.hcdata.htm. 2. Links to surveys and reports from the International Foundation’s multistep value-based health care initiative, as well as dozens of articles and an extensive l ist of resources, are available at www.ifebp.org/ valuebasedhealthcare.

Larry McNutt serves as salaried administrator of the Carpenters Trusts of Western Washington in Seattle, Washington, a group of four self-admin-istered trusts serving more than 10,000 active and retired union carpenter families throughout Washington, Idaho, Montana and Wyoming. A certified public accountant, McNutt has more than 35 years of experience in Taft-Hartley fringe benefit administration and is a past president of the Northwest Association of Administrators. He serves as chairman of the Health Economics Committee of the Puget Sound Health Alliance. McNutt’s experience includes administration of benefits for many industries, including construc-tion, freight and warehousing, building service, shipbuilding and food processing.

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