Value-Based Insurance Design




Introduction

The US healthcare system has widely acknowledged problems with cost, quality, and access. Medical spending is higher than that in any other country, at 17.6% of GDP in 2009, and rising at a rapid rate; such a cost trajectory is unsustainable. Meanwhile, quality is often lacking, and lags behind that of many other nations (Table 1).

Value-Based Insurance Design tab 1




Among the most widely used strategies in recent years to address spending has been an increase in patient cost sharing. In addition to shifting the economic burden associated with healthcare from purchasers to patients, economic theory suggests that shifting more financial responsibility onto the patient should reduce wasteful overuse and decrease spending. Unfortunately, patients have been shown to make poor clinical decisions when faced with higher cost sharing by reducing the use of both unnecessary and essential services. Information asymmetry, time-inconsistent preferences, and the impact of marketing and cultural values, all contribute to inefficiencies created by shifting more decision-making power onto the patient. Although such programs inevitably lead to lower spending in the short run, they have been associated with poor adherence and outcomes, increased disparities across socioeconomic groups, and possibly higher long-term spending for some patients.

Value-Based Insurance Design tab 1.1

Value-based insurance design (VBID) was proposed in 2001 as a means to mitigate the negative impact of increased cost sharing and improve the efficiency of our healthcare system. VBID refers to insurance packages that align copays with value, charging patients less for high-value services and more for low value services. By focusing on value, rather than cost alone, VBID aims to improve quality, lower barriers to essential care, and perhaps, if copays are increased for low value services, to save money. VBID programs recognize that different services offer differing amounts of benefit for the money spent. More sophisticated versions can also recognize that value reflects patient traits and can recognize patient heterogeneity.

Most commonly, VBID lowers copayments for high-value services, like diabetes and asthma medications. Cost sharing for low-value services may be increased to help offset program costs and discourage use of low-value services, but this is less common.

Although the concept of VBID is relatively recent, emerging data point to its feasibility and effectiveness. VBID approaches have been successfully adopted by numerous employers with mostly positive clinical results. Both observational data and more systematic controlled analyses support the idea that VBID improves medication adherence and clinical outcomes, and may even lower overall spending. Because its greatest impact is on low-income individuals, it may also help reduce the widespread health disparities seen in the chronically ill.

Rather than a cure-all for our system’s problems, VBID is a tool that should be integrated into other innovative approaches, including pay-for-performance (P4P), patientcentered medical homes (PCMH), consumer-driven health plans (CDHPs), and disease management (DM) programs. The ultimate objective of VBID is not to save money, but rather to maximize the health benefit achieved for the money invested; its goal of maximizing value-based limited resources is inherently aligned with that of our entire healthcare system. VBID is growing in popularity among employers, patients, and policymakers. It was included in the Patient Protection and Affordable Care Act (PPACA) and state legislation healthcare reform laws, and has been the subject of plans for new pilot programs within Medicare.

Theory

Consumers seek insurance in order to transfer the unpredictable risk of illness to others and gain access to otherwise unaffordable care. Health insurance helps individuals pool the financial risk of illness. As consumers are risk-averse, they would rather pay a certain fixed premium than risk the possibility of a very high expenditure. In addition, health insurance offers access to treatments that would otherwise not be obtainable. Regular premiums are generally more affordable than the large costs associated with major illness. Thus the benefits of insurance extend beyond risk avoidance to accessibility of care in case of a catastrophic event.

At the same time, insurance introduces moral hazard, which can reduce social welfare. Because the patient’s cost of medical treatment is greatly reduced under insurance coverage, patients will utilize more services than they otherwise would. The amount of insurance-induced consumption depends on the price elasticity in demand. The welfare consequences of the extra consumption depend only on the portion of insurance induced over consumption due to the distortion of relative prices. Any extra consumption due to an implicit transfer of income associated with insurance is not a concern. Nevertheless, because insurance distorts prices, it induces greater use of services, necessitates higher premiums, renders health insurance less appealing, and reduces the value of the healthcare system.

Cost sharing has traditionally been used to transfer some risk onto the individual consumer and reduce moral hazard. A price above zero but below the market level allows some risk pooling, while reducing insurance-induced overconsumption. Theory suggests that because of their greater insuranceinduced overuse, more elastic services should attract greater cost sharing, whereas inelastic services should be fully reimbursed. Under standard economic theory, because patients utilize services for which their perceived benefit outweighs the cost, higher price will reduce consumption disproportionately for low-value services, which will preserve value in the healthcare system.

Across-the-board copayment increases typically do not take into account differences in benefit of different treatments. The expected benefit of a therapy should be inversely proportional to the elasticity of demand, and thus copayment requirements prevail. An essential medical service should have an inelastic demand, and be covered fully by insurance. Most traditional benefit plans only take into account the cost, not benefit, of a service when determining the degree of cost sharing. Such plans also fail to appreciate patient heterogeneity; a single service might have a different benefit and elasticity for different patients depending on the clinical diagnosis. For example, beta-blocker therapy may play a vital role in the management of heart failure patients, or be used more electively in the treatment of anxiety. Differences in risk and outcome preferences among patients further contribute to patient heterogeneity, rendering indiscriminate changes in copayments suboptimal because too much risk is being transferred for inelastic services.

Yet, if patients do not make optimal decisions, placing more risk and decision-making power in their hands may have detrimental effects. As patients are risk-averse, such increased cost sharing reduces the value of the insurance plan. In addition, patients often misjudge the costs and benefits of medical therapies, and make poor clinical decisions. Inherent information asymmetry between patient and provider may lead to underuse of essential services and suboptimal resource allocation. The physician has limited information regarding patient preferences, values, and history. Likewise, patients often fail to fully understand medical information, or are otherwise influenced by external biases like marketing. They lack the clinical training to completely comprehend underlying principles and make objective decisions. Physicians typically have years of experience and better ability to predict disease progression. Similarly, patients’ time-inconsistent preferences may bias their clinical decision-making. Individuals tend to undervalue future benefits and prospective cost savings. These phenomena contribute to underutilization of valuable services, increased overall medical spending, and poor outcomes, particularly in chronic disease patients like diabetics or asthmatics.

Higher copayments further tend to have a greater impact on low-income patients, contributing to healthcare disparities. These populations already face significant barriers to essential care, which are only exacerbated by increased cost sharing. Patients with higher education and better understanding of their care are also more likely to make better clinical decisions. The increased responsibility and financial risk associated with increasing copayments places an unnecessary burden on less affluent populations, and tends to preferentially worsen their health outcomes

VBID addresses these problems using a ‘clinically sensitive’ approach to align financial incentives with value in the healthcare system. It recognizes that if decision-making is flawed, the amount of cost sharing should depend not only on the cost, but also on the evidence-based benefit of a therapy.

Defining value in the context of VBID programs is complex. Conceptually, value relates to the cost effectiveness of a given service for a given patient (health gained per dollar spent). The growing emphasis on cost effectiveness and comparative effectiveness research can support efforts to assess value and implement VBID. But it is unlikely that evidence will be detailed enough to be tailored to specific patients so most VBID programs will be applied on average for groups of patient remain. The crucial assumption is that fully informed consumers, given the economically efficient income transfer associated with insurance, would purchase these services even if they faced the true prices. In cases of high-value (e.g., highly cost effective) services, increased consumption does not represent moral hazard, and thus should not be financially discouraged. This principle is also in line with standard economic theory. Essential high-value care should have price inelastic demand (once implicit income transfers associated with insurance are taken into account), and thus little or no required cost sharing.

VBID ultimately employs evidence-based medicine to reinforce the financial incentives of using high-value care. It addresses the inherent information gap between patient and provider, and may even offer benefits beyond those of patient education for underused services. Lower cost sharing would increase consumption, improve health outcomes, and possibly even reduce long-term healthcare costs. Through lower copays, a value-based benefits design not only encourages optimal utilization of cost-effective services, but also offers a greater degree of risk protection to the consumer.

The overall financial profile of VBID initiatives can be favorable, particularly if cost sharing is increased for low-value services, and depends largely on the disease state being targeted. Services that have elastic demand and reliably prevent expensive complications that are highly likely to develop otherwise, tend to be best candidates for copay reductions. Increased cost sharing for such services might reduce short-term spending the form of lower utilization, but will likely accrue higher long-term costs through increased complications. Conversely, VBID may save money and improve outcomes in such cases.

Although VBID may reduce aggregate healthcare spending by avoiding expensive exacerbations and complications, the financial impact on the employer is less obvious. Employers face increased initial spending due to more generous coverage of high-value services, and greater demand for those services due to improved adherence. Employers take on increased medication costs, and might not be able to reap the savings if they have high employee turn-over rates. As an example, promoting the use of statins will likely increase short-term spending for the employer. A significant part of the savings in the form of avoided complications might go to Medicare once the patient retires. As long as health insurance is largely employer-based, there will be an inherent divide between employer healthcare spending and aggregate spending on a population level.

Nonetheless, some of these employer costs may be offset by savings on other medical spending, such as hospital or emergency department visits. Increased productivity, employee satisfaction, and decreased disability also contribute significant value to the employer. The return on investment will largely depend on the degree and accuracy of patient targeting. Programs that offer copayment reductions for very specific patient populations and specific medications will tend to have more attractive financial profiles. Although not a major part of VBID, increased cost sharing for other, preferably low-value services, may further help reduce implementation costs. Above all, it is vital for employers to appreciate the often overlooked value of improved productivity and lower disability. VBID will offer greatest financial benefits where the patient population is responsive to changes in cost sharing and expensive complications may be reliably prevented using cheap medications. This is true of many chronic diseases, such as diabetes or asthma, which have been the first targets of VBID programs. VBID principles may be extended to other high-value therapies as well. Nonetheless, it is important to recognize that increasing the use of cost-effective services will not in itself be cost-saving. The chief benefit will be improved efficiency and value of the healthcare system, with reductions in spending possibly requiring increased cost sharing for low-value services.

By lowering copayments for high-value services, VBID may support a number of other health system reforms, including pay-for-performance, patient-centered medical homes, and CDHPs. Both P4P and PCMHs are supply-side interventions that encourage evidence-based medicine and improve access to high-value care. These programs allow clinicians to claim a portion of savings from reduced medical spending and offer financial rewards for improving outcomes. Similarly, VBID offers patients a financial incentive to pursue lower-cost higher-value therapies in the form of reduced cost sharing. VBID naturally complements P4P and PCMHs by aligning patient and provider incentives. DM programs would likewise benefit from value-based benefit designs. DM utilizes a variety of strategies, including patient education and coaching, to encourage high-value care. Patients are often given easier access to doctor visits and relevant medications. Reducing copayments for these drugs naturally complements DM initiatives by reducing the financial barriers to care. Like VBID, CDHPs emphasize consumer incentives to improve value and curtail costs. However, CDHPs significantly increase patient cost sharing for all services below the deductible with likely reductions in the use of both low-value and essential care. Implemented together, these programs would promote cost-conscious decision-making while encouraging use of high-value care. For example, the use of ‘VBID waivers’ for certain services would mitigate the negative impact of higher cost sharing in CDHPs. Applying VBID principles to subsidize high-value services would increase their use and improve efficiency within the healthcare system.

Although drug benefits are a very natural application of VBID, the concept may be extended to other health services. As an example, it has been proposed that the field of oncology would be a natural candidate for VBID implementation for several reasons. Different therapies will offer varying degrees of benefit for patients; whereas some treatments add years of life, some might only extend survival by a few weeks. The benefit of one drug may also depend on the diagnosis. Although the same chemotherapy or radiation might be used for many different cancer types, some will be more responsive to the therapy than others. Finally, the expected value of a treatment often depends on the particular patient. Biomarkers may be used, as in the case of breast cancer, to identify patients likely to respond to certain therapies. Oncology would naturally benefit from evidence-based targeting to encourage use of high-value services. In parallel, gastroenterology has also been proposed as a possible target for VBID. For example, a colonoscopy will rather have different value for a high-risk or elder patient, than for a young patient seeking the same procedure. The basic principles of targeting and adjusting copayments according to value of a service may be applied in a variety of clinical situations, ranging from drug benefit design to oncology and gastroenterology.

Practitioners

Over the past decade, VBID has grown steadily in popularity, and by one estimate is currently utilized in some form by 20–30% of large employers. It has garnered significant support for its adaptability, depending on employer goals and the patient population. The basic principles of VBID may be applied for any balance between improved employee health and reduced spending. In practice, it is impossible to achieve perfect targeting and evaluate the value of each service for every patient. A balance must be struck between program effectiveness and feasibility, often limited by availability of evidence-based data, accurate assessment of patient’s clinical condition, and health information technology. To address these issues, several approaches for implementing VBID have been used that target patients based on service, condition, condition severity, participation in other health programs, or a combination of them.

One approach is to simply reduce cost sharing for certain drugs and services that are deemed to be of high value. All employees would face the same copayments, irrespective of clinical diagnosis or use of the therapy. Pitney Bowes and Marriot have adopted such a solution for diabetes, hypertension, and asthma medications. Pitney Bowes was among the most widely celebrated employers of VBID; although there was no external control, it reported $1 million in savings after introduction of the program in 2002. Most importantly, the program has received widespread attention and has demonstrated that VBID is feasible and may be effective.

Another possibility is to target a specific patient population and offer reduced copayments for high-value evidence-based treatment. Patients with a specific condition would be eligible to participate and receive free or subsidized care. Such programs typically target chronic diseases with known evidence-based therapies, including cancer, cardiovascular disease, obesity, respiratory conditions, and diabetes. The University of Michigan, MI, USA, is among the first to utilize this approach. All employees with diabetes are eligible to enroll and receive subsidized insulin, beta-blockers, diuretics, and other high-value medications. Started in 2009, the University of Michigan Focus on Diabetes Program is the first prospective controlled trial of VBID, and will likely shed light on its effects on outcomes and spending. The city of Asheville in North Carolina and United HealthCare have used a similar approach to target diabetes.

Less commonly used approaches include targeting high-risk patients either eligible for, or actively enrolled in, a DM program. These patients would likewise receive reduced or waived copays for certain medication classes. This design is offered by WellPoint, although it has not been widely adopted by its clients; Gulfstream offers subsidies for utilizing providers that meet certain evidence-based care criteria. Other major providers using VBID include Caterpillar, Service Employees International Union, Mid-America Coalition on Health Care, and Health Alliance Medical Plans (HAMP). Each company targets different combinations of chronic diseases, depending on the employee population and claims data. Employers may fine-tune their VBID implementation to reach a desired level of medical costs and employee health. Many providers had incorporated VBID into more comprehensive novel healthcare delivery systems. Hannaford Brothers, for instance, combined VBID targeting certain diseases and minimally invasive surgical procedures, with promoting healthy lifestyle habits and better information technology. All available results point to improved drug adherence and outcomes, especially for diabetes and hyperlipidemia.

Finally, there are increasing calls on the government to promote the adoption of VBID, and include it in any healthcare reform laws. The American Academy of Actuaries recognized the importance of VBID and recommended that any new legislation do not discourage its implementation. The government should also continue investing in comparative effectiveness research (CER) and health information technology (HIT) as means to improve value and clinical outcomes in the healthcare system. Unlike many other interventions, VBID has garnered bipartisan support, with 73% of healthcare leaders generally in favor of its adoption. VBID has the benefit of offering important financial incentives without limiting patient choice. By targeting primarily high-value services, patients are encouraged to pursue valuable care, but are given the freedom to access other services as well. In addition, it avoids placing physicians into the role of healthcare gatekeepers, and maintains low administrative barriers to care. VBID has gained support from patients, providers, and payers, by aligning their incentives.

Accordingly, VBID has gained much attention among policymakers. The PPACA includes language permitting the use of VBID for high-value preventive services, such as immunizations and screenings (2010). As required by the new law, the Department of Health and Human Services has devised a National Strategy for Quality Improvement in Health Care, which promotes the use of VBID models at the federal level (2011). Similarly, there has been interest in using value-based principles to improve the financial profile of Medicare. There have been proposals to introduce a VBID pilot program for Medicare to evaluate its effectiveness. More recently, the Medicare Payment Advisory Commission (MedPAC) report to Congress has underscored the importance of using VBID to steer patients toward higher-value services. President Obama has likewise included VBID in his Deficit Reduction Plan, and has called for vesting the Independent Payment Advisory Board with power to promote value-based benefit designs (2011).

Empirical

Patient cost sharing has been steadily on the rise over recent years, in an attempt to curtail growing healthcare spending. Between 2000 and 2009, the average generic, preferred, and nonpreferred prescription drug cost sharing increased by 25%, 80%, and 59%, respectively. Paradoxically, copayments have also risen both within DM programs and for services used as quality indicators. As DM programs implement innovative approaches to encourage use of essential services and improve adherence, rising copays discourage the consumption of those same therapies. Likewise, services accepted as high-value and used as quality measures for hospitals often lack demand-side financial incentives. Indicators contained within the Health Plan Effectiveness Data and Information Set (HEDIS) have suffered increases in copayments similar to that of other services. HEDIS is widely used to evaluate health plan performance and includes measures such as receipt of beta-blockers after a heart attack and treatment of asthma. Higher cost sharing for HEDIS services may lower health plan performance.

Further, there are significant data demonstrating the effects of greater cost sharing on adherence and outcomes. Many studies have shown that patients tend to indiscriminately cut use of both essential and low-value services when faced with greater copayments. Even vital medications, like those used for hyperlipidemia, rheumatoid arthritis, diabetes, and asthma, suffer the effects of increased cost sharing. Doubling of copayments for diabetes and hypertension drugs has decreased medication use by 23% and 10%, respectively. This is particularly alarming, considering that many crucial services are widely underutilized by patients. The resulting decreased adherence often leads to poorer outcomes and higher rates of complications. This has been particularly evident in the case of asthma, diabetes, and cardiovascular disease. Under some circumstances, increased cost sharing may actually raise long-term costs by increasing the incidence of expensive and preventable complications. Importantly, the effects of increased cost sharing have the greatest impact on low-income patients. These patients are more likely to delay treatment due to cost concerns; for example, higher out-of-pocket expenses are also associated with more frequent asthma exacerbations in children of low-income families. The higher incidence of chronic illnesses like diabetes and asthma, combined with the effects of increased copayments, contributes to worse outcomes in these populations with resulting greater health disparities.

There is less evidence regarding the effects of lowering copayments, which is the principle instrument of VBID. The impact of lower cost sharing might be different than that of higher cost sharing because of psychological phenomena, but in practice, it is generally similar in magnitude. Some indirect data had come from the introduction of Medicare Part D, which lowered out-of-pocket drug spending for seniors. There was a 3–13% increase in medication use, with the opposite effect seen in the coverage gap. This corresponded to improved outcomes and a 4.1% reduction in hospitalizations relating to diabetes and several cardiovascular and pulmonary conditions. The effects of Medicare Part D were largest for patients with previously high copays or no coverage. In this subgroup, savings on medical expenditures generally offset increases in drug costs. In other settings, it has been observed that lower cost sharing for diabetes patients is associated with better adherence and better glycemic control, as measured by the degree of hemoglobin glycation. Fixed-effects modeling further suggests that lower medication copayments may lead to higher pharmacy benefit costs, but significant overall savings in congestive heart failure, hypertension, diabetes, and dyslipidemia patients.

Direct evidence on the impact of VBID programs is relatively recent; the concept of VBID is fairly new, and it takes years to see long-term outcome and spending effects. The data are also more heterogeneous because the programs’ impact largely depends on the particular implementation. Results that are not peer-reviewed and lack a control group suggest that the experience has been generally positive. Pitney Bowes had boasted of one of the first widely celebrated programs. Caterpillar, Hannaford Brothers Company, United Healthcare, and others, reported similarly improved outcomes with no change in, or reduced, spending. Controlled studies and more systematic analyses are fewer, but offer important, often less positive insights into the consequences of VBID programs.

Earliest data on the effects of VBID come from several mathematical models. A very broad implementation targeting various high-value services throughout the healthcare system would confer an additional 5–9% health benefit, as measured in life-years, without increasing overall or out-of-pocket spending. Better targeting of high-value therapies, such as angiotensin-converting enzyme (ACE) inhibitors or cholesterol-lowering drugs, offers even more advantages. Simulation analysis suggests that eliminating cost sharing for ACE inhibitors for Medicare patients with diabetes would both improve outcomes and lower costs by up to US$1600 per patient. Adjusting copayments for cholesterol-lowering therapy based on the patient’s risk level would offer similar benefits. Thousands of hospitalizations and emergency department visits would be avoided, with over US$1 billion in annual aggregate savings. These simulations are particularly sensitive to estimates of the impact of lower cost sharing on adherence. Nonetheless, even with conservative assumptions, VBID is expected to confer clinical benefit with little change in spending.

More recently, there have been emerging data from employers implementing VBID principles. Analyses of two large firms with VBID options had demonstrated improved adherence and outcomes, with potentially neutral effects on aggregate spending. The financial impact on the employers was somewhat less favorable, but some of the cost could be offset by improved employee satisfaction and productivity. Both the State of Maine and the City of Springfield in Oregon had initiated pilot programs that targeted diabetes patients. In addition to waiving copayments for drugs and physician visits, the latter program also provided free individualized pharmacist consultations. Compared to randomly chosen controls, patients in the intervention group in each case had improved medication adherence and had better glycemic control. Sick leave had declined and productivity had improved for both programs. Although Maine reported significant savings, Springfield’s healthcare costs had actually increased. Nonetheless, it is possible that savings in the form of employee productivity and reduced disability have helped offset any program costs, and long-term savings are likely to accrue beyond the timeframe of the initial study. Both pilot programs were considered a success, with VBID options becoming more widely available soon thereafter. Overall, these data demonstrate the varied consequences of VBID implementation. The

financial profile will largely depend on the level of targeting, patient population, and other employer-specific parameters. Nonetheless, there is consistent evidence that VBID improves clinical outcomes and value of the healthcare system; by promoting the use of high-value services, it offers improved employee health and productivity. These indirect benefits are often overlooked in cost-effectiveness analyses.

VBID has also been applied in the context of DM programs and patient-centered medical homes, with very positive results. Although both DM programs and VBID improve medication adherence, a combination of the two strategies offers further benefits. Within a single DM program, VBID had increased medication adherence by 7–14% for statins, ACE inhibitors, beta-blockers, and diabetes medications. In a separate study, a combination of DM and VBID to target diabetes patients had proved to be cost-saving and improved drug use by almost 7%; these effects were significantly better than controls in either program alone. Similarly, several employers have combined VBID with PCMHs. Among others, the City of Battle Creek in Michigan and the State of Minnesota have reported positive results using this approach. Various performance measures have greatly increased by at least 20–35% following introduction of the programs. Patients have received more preventive care, and have avoided both expensive hospitalizations and emergency department visits. Blood pressure, glycemic control, and cholesterol levels have improved by 5.7–22%. Other examples further reinforce the benefits of integrating VBID into innovative payment reform approaches. Although effective on its own, VBID may be easily and effectively combined with other strategies.

Conclusion

As the persistently growing healthcare spending is addressed, it is important to maintain a focus on value and not cost alone. The purpose of healthcare is not to save money, but to provide the greatest health benefit given limited resources. Limiting access to essential care might save money, at least in the short term, but is not socially desirable. Further, focusing on shortsighted interventions like indiscriminate increases in copays may actually have opposite effects on spending in the long term. Curtailing spending should not be at the expense of reducing essential high-value care. VBID is an important approach that aims to improve the value of the healthcare system, as well as reduce barriers to essential care and health disparities.

Nonetheless, there are some challenges that lay ahead of a more widespread acceptance of VBID. Patients might have concerns of privacy and fairness. Different patients might be charged different fees for the same service. Some of the patients’ clinical data are also used for benefit design. Nonetheless, most of these issues may be addressed through patient education and careful program design. Another major challenge to VBID implementation is a lack of CER and HIT infrastructure. VBID relies on CER to identify high-value services; there are currently few studies that compare the effectiveness of competing therapies. Likewise, HIT is necessary to incorporate the data from CER into benefit design. Nonetheless, there are known high-value therapies for the treatment of many chronic diseases, and HIT is adequate for basic targeting. In these areas, VBID could be implemented successfully. As there iscontinuous expansion in targeting capabilities, opportunities for VBID will expand.

Employers have also been cautious in adopting VBID because of its somewhat uncertain financial impact. The return on investment profile of VBID largely depends on the particular implementation. Employers can improve the financial profile of their program by finer targeting. Reducing copays for a smaller group of high-risk patients is more likely to reduce program costs. Employers may also choose to raise copays for all other services, or preferentially target low-value services, though it may be difficult to identify low-value services based on easily identifiable patient characteristics. Few treatments are low-value for entire patient groups, requiring more sophisticated targeting and incorporation of clinical judgment. Another concern of VBID is that such plans might preferentially attract sickest patients who would receive lower copays for high-value services targeted at chronic disease.

The success of VBID will require a new mindset of simply embracing value over costs. After allocating the most efficient amount of resources to healthcare, the health benefit to patients will need to be maximized. This will also call for more comprehensive ways of assessing costs, benefits, and value than the often shortsighted methods being used today. Such a new approach to insurance design will require an integration of clinical medicine, economics, and actuarial analysis. The feasibility of VBID will grow with continued investment in CER and HIT. As new data become available on the relative value of services, it will be crucial to align financial incentives with the highest-value options. The recent growth of HIT will also make better benefit design feasible. As communication between patients, providers, and insurance benefit managers improves, better plans that align incentives between the parties will become a reality.

Although not a sole remedy for the healthcare system’s issues of cost, quality, and access, VBID is a powerful tool that aligns financial incentives for patients with evidence-based medicine. By adjusting cost sharing based on the value of a service in the context of a particular clinical situation, VBID can facilitate more efficient resource allocation and better health outcomes. Integrated with other approaches, including DM, CDHPs, and patient-centered medical homes, VBID may prove to be a powerful tool for tackling major health care reform in the coming years.

References:

  1. Braithwaite, R. S., Omokaro, C., Justice, A. C., Nucifora, K. and Roberts, M. S. (2010). Can broader diffusion of value-based insurance design increase benefits from US health care without increasing costs? Evidence from a computer simulation model. PLoS Medicine 7, e1000234.
  2. Chang, A., Liberman, J. N., Coulen, C., Berger, J. E. and Brennan, T. A. (2010). Value-based insurance design and antidiabetic medication adherence. American Journal of Pharmacy Benefits 2, 39–44.
  3. Chernew, M. E., Juster, I. A., Shah, M., et al. (2010). Evidence that value-based insurance can be effective. Health Affairs 29, 530–536.
  4. Chernew, M. E., Shah, M. R., Wegh, A., et al. (2008). Impact of decreasing copayments on medication adherence within a disease management environment. Health Affairs 27, 103–112.
  5. Choudhry, N. K., Fischer, M. A., Avorn, J., et al. (2010). At Pitney Bowes, valuebased insurance design cut copayments and increased drug adherence. Health Affairs 29, 1995–2001.
  6. Choudhry, N. K., Patrick, A. R., Antman, E. M., Avorn, J. and Shrank, W. H. (2008). Cost-effectiveness of providing full drug coverage to increase medication adherence in post-myocardial infarction Medicare Beneficiaries. Circulation 117, 1261–1268.
  7. Gibson, T. B., Mahoney, J., Ranghell, K., Cherney, B. J. and McElwee, N. (2011a). Value-based insurance plus disease management increased medication use and produced savings. Health Affairs 30, 100–108.
  8. Gibson, T. B., Wang, S., Kelly, E., et al. (2011b). A value-based insurance design program at a large company boosted medication adherence for employees with chronic illnesses. Health Affairs 30, 109–117.
  9. Goldman, D. P., Joyce, G. F. and Karaca-Mandic, P. (2006). Varying pharmacy benefits with clinical status: The case of cholesterol-lowering therapy. American Journal of Managed Care 12, 21–28.
  10. Mahoney, J. J. (2005). Reducing patient drug acquisition costs can lower diabetes health claims. American Journal of Managed Care 11, S170–S176.
  11. Mahoney, J. J. (2008). Value-based benefit design: Using a predictive modeling approach to improve compliance. Journal of Managed Care Pharmacy 14, S3–S8.
  12. Rosen, A. B., Hamel, M. B., Weinstein, M. C., et al. (2005). Cost-effectiveness of full medicare coverage of angiotensin-converting enzyme inhibitors for beneficiaries with diabetes. Annals of Internal Medicine 143, 89–99.

 

Supplemental Insurance in National Systems and the USA