Posts filed under ‘Value-Based Insurance Design’

MedSpan Research Pay-For-Performance Case Study

MedSpan Research Pay-For-Performance Case Study

Connectivity is one of the Key Underlying P4P Programs…Read more to learn why

Continue Reading July 21, 2015 at 2:00 PM Leave a comment

Here is What MedSpan Research Has Been Up To and Learning: Our Tri-Weekly Newsletter

Recently, a Modern Healthcare survey determined that a majority of healthcare CEOs supported the transition from Fee-For-Service to Value-Based Compensation. However, their time frame of transition varies. Read our blog entry for more on this subject.

Continue Reading June 8, 2015 at 10:22 AM Leave a comment

Why Market Access is Crucial for Healthcare Marketers Today

Market access has changed dramatically over the years and is becoming a high priority for healthcare marketers. Read on to learn about these changes and how to address the complexities of gaining access.

Continue Reading July 12, 2013 at 10:04 AM 1 comment

Value Based Insurance Design: Return on Investment


Fact:  Treating pre-diabetic patients costs $5,000 in total, while the average annual cost of diagnosed diabetes with complications, such as heart disease or kidney failure, can be as high as $30,000 per year.[1] 

Given the limited nature of healthcare resources, value-based insurance design (VBID) sets allocation priorities based on clinical evidence demonstrating which type of care delivers the greatest value .  That is, VBID programs motivate patients to use, and physicians to prescribe, the treatment alternatives that best enhances health status at the lowest possible net cost.  VBID programs discourage the use of services with marginal value to ensure the appropriate and cost-effective utilization of health care resources.  

One way to measure the effectiveness of VBID programs is return on investment (ROI), which demonstrates the improvement in health status as compared to the money spent in designing, developing and implementing a VBID initiative. 

 ROI Calculation for VBID

 Generally, there are two ways to go about calculating the ROI for VBID initiatives.   The first method considers the costs to the health plan related to reduced co-pays and other financial incentives plus any increased utilization of healthcare resources that may result from the incentives.  The ROI is then calculated by comparing those costs to the reduced medical costs resulting from increased treatment adherence by the newly engaged enrollees plus any increase in revenue due to new beneficiaries who join a plan due to the VBID program.[2] 

Alternatively, the more expansive ROI calculations include program costs, such as communication initiatives and disease management and other support programs, as well as productivity increases associated with reductions in absenteeism and presenteeism.[3] 

Both of the above calculations do not take into account the impact of healthcare treatment on the patient’s quality of life.  While quality of life is an important outcome of healthcare, objective measurement ranges from difficult to impossible.

 So far, several health plans have reported positive results from their VBID programs.  Here are some examples.

 (1)     Savings from Adjustment and or Waiver of Co-payment

 WellPoint tested a VBID model in the State of Maine, with 40,000 employees, targeting diabetes by either waiving or reducing copayments.  This pilot program covered four employers, including the  Preliminary results for the City of Maine pilot, the Telephonic Diabetes Education and Support program, showed an improvement in medication possession rate increasing from 77 percent to 86 percent post the implementation of the program.  One year follow-up study reported adjusted average cost for participating members being $1,300 less compared to the non-participants. 

 (2)     Long Term Savings from Increase Medication Adherence

 Health Alliance Medical Pans, Inc.’s VBID initiative made available to 86,000 fully insured members and dependents a fourth copayment tier called the Value Based Benefit tier addressing members with diabetes, hypertension and asthma.  The new benefit made specific drugs related to the three conditions available for a 10 percent copayment, a copayment less than its second tier $22 copayment.  Under the Value Based Benefit tier, the plan provider shifted lower value drugs to higher tiers by choosing not to cover over-the-counter non-sedating antihistamines that instantly saved the plan provider $2 million.  Although utilization and monthly prescription drug costs increased, medication adherence for diabetes and asthmatics increased 10.6 percent and 32.7 percent, which is likely to generate long-term medical savings. [4] 

 (3)     Savings from Comparatively Lower Rate of Increase in Healthcare Cost

 Also encouraging is the comparatively slower rate of increase in healthcare cost noted by VBID program providers.  For example, IBM reported that the company, as one of the early adopters of VBID for its employee healthcare plans, was able to maintain a health care cost trend at 3% to 4% mark while comparative average healthcare cost trend was 12% and higher.[5]

[1] Houy, M. Value-Based Benefit Design: A Purchaser Guide. National Business Coalition on Health. January 2009.

[2-5] ibid


August 24, 2010 at 9:52 AM 2 comments

Evidence-based radiology — a concept on the cusp

For some years now, payers, academics and clinical practitioners have had concerns about the justifications for clinical practice patterns.   The need for evidence-based practice ranges from formulary design to clinical care to radiology.

“Medical practice is largely based on clinical anecdotes, uncontrolled investigations and expert opinion. The demand for scientific evaluation to guide patient care is increasing because financial resources are limited and because practice based on such influences may be inappropriate. In radiology, the situation is especially problematic…. Few radiology programs address and encourage critical thinking skills.” (Source: Hillman BJ, Noninterpretive skills for radiology residents. Critical thinking: deciding whether to incorporate the recommendations of radiology publications and presentations into practice. AJR Am J Roentgenol 2000; 174 (4):943-946.)

For example,  when clinicians, such as radiologists, health plan administrators, and others try to decide between imaging and interventional options, they may find that textbooks are out of date, guidelines are not specific enough and there are conflicting or apparently unreliable reports in the literature. Expert opinions and policies vary and even the definition of ‘evidence’ is unclear.

Some experts recommend using the ‘consensus of experts’ approach.  However, the reliability and reproducibility of this type of evidence is questionable.  Others recommend the use of guidelines that are based on expert appraisal of the literature.  These are roughly equivalent to a consultation with experts but may not answer our specific question well, be based on strong evidence or take into account new developments and local circumstances.  However, when clinicians and health plan administrators go to the literature, the first problem encountered is the volume of literature being published and, perhaps, a lack of training in how to separate the good studies from the weak ones.  Another problem is determining whether specific clinical decisions and medical policies should be based on the general consensus illustrated by the evidence or following a minority opinion that better applies to a specific situation or sub-group of patients.

One of the issues facing healthcare manufacturers is how to best support clinicians and administrators as they address these challenges.  For healthcare manufacturers, the key questions are 1) What type of data will my customers find most compelling?  2) How will that data best support my marketing efforts and support appropriate adoption of my product? 3) How can I develop the data most cost effectively?  Is a retrospective study or an observational study sufficient?  Is a costly prospective study with a randomized design necessary?  4) What return will I realize from the data I develop?

The first step for healthcare manufactures is to realize the data are necessary.  As comparative effectiveness research becomes more prevalent and clinical decisions are increasingly scrutinized, data is all that clinicians and administrators will find relevant and compelling. 

The next step is to develop an evidence plan early in the product development process.  To the extent possible, the time to develop such data is when drugs are going through clinical trials or diagnostic assays and imaging equipment and applications are under development.   Developing data after FDA approval and product launch could burn the limited commercialization time available before a competitor arrives or patent protection expires.

The evidence plan should be based on the expected return on investment.  If less-costly retrospective and observational studies will drive adoption, though perhaps not optimally, they might optimize ROI.  Potential market blockbusters might warrant costly prospective, multi-center studies that support a lasting and profitable competitive advantage.

The design of specific studies within the evidence plan should be based on the intended audience.  Payers (eg, health plans and hospital administrators) are looking for value.  That is the expected improvement in quality of care, based on specific and measurable outcomes, divided by the impact on cost.  Cost includes that of the drug, device or imaging application as well as any cost offsets (eg, reduction in hospitalizations) directly due to the product.  Providers are more focused on improvements in clinical care and outcomes and, to a lesser degree, cost impact. 

As today’s discussion begins to illustrate, the development of an evidence plan is a complex undertaking that should be well thought out.  Today’s environment and its emphasis on comparative effectiveness, cost management and access to appropriate therapies and procedures makes the development of the evidence plan more critical than ever before.

July 23, 2010 at 12:49 PM Leave a comment

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