Benefit Design Should Reflect Value

In 1965, when Medicare was enacted, spending for prescription drugs was less than $4 billion—so low that no one thought to include a drug benefit as part of Medicare. By 2003, the cost and importance of drug therapy was so high that Medicare Part D was enacted.

Drug therapies have become one of the most important tools for managing chronic illness: they forestall complications, reduce attendant medical utilization, and help improve patients’ productivity. [1,2]

Unfortunately, the benefits of drug therapy are regularly undermined by the low rates of compliance—sometimes as low as 20 percent, and varying with complexity and duration of therapy. [3] The reasons for noncompliance are myriad—including aversion to side effects and general forgetfulness—and can be difficult to combat.

However, financial incentives can influence patient behaviors. We know, for example, that copayments exert a powerful influence on use of chronic medications. [4] So why not lower them for certain patients to encourage better adherence to high-value drugs that are most effective?

Increasingly, payers are embracing value-based insurance design (VBID) that reduces copayments for patients who are most likely to benefit from a drug or service, as determined using available clinical evidence. [5,6] Patients for whom the therapeutic benefit is modest—or the evidence is mixed—face higher cost sharing. For example, a plan might charge a lower or no copayment for cholesterol lowering drugs if a patient has another risk factor, like diabetes. To offset this cost, patients at low risk might face higher copayments.

Empirical studies—most focused on prescription drugs—suggest measurable benefits from a value-based approach to drug therapy. [6,7,8] For example, VBID for cholesterol-lowering therapy alone would reduce patients’ total health costs by 3–5 percent. [9] Anecdotal evidence suggests even more dramatic savings. Pitney Bowes reduced copayments for several classes of chronic medications, including diabetes, hypertension, and asthma, in combination with other health initiatives. They found improved medication compliance, with the higher pharmacy costs more than offset by lower rates of emergency department visits and avoidable hospitalizations. [10]

Clearly, VBID could be a very useful tool for restraining health care costs by discouraging use of medical interventions with marginal value and by encouraging certain services for selected patients for whom there is clinical benefit. But VBID faces operational challenges that could limit broader application.

First, if guidelines aren’t carefully drawn, they can lead to perverse incentives. For example, patients who feel relatively healthy might postpone medical care until they are sicker and/or get better coverage. Second, some anecdotal evidence suggests that offering more generous drug benefits makes a plan less competitive. [11] A health plan with a reputation for offering the most generous benefits may disproportionately attract the sickest patients. These concerns, however, can be mitigated through risk adjustment and incentives to stay healthy. [12]

The biggest challenge is that clinical data on efficacy for many services and procedures are lacking or expensive to collect, so VBID is not yet a widespread solution. However, the potential VBID has shown with medications suggests that payers may want to use it with those procedures— such as medical devices and imaging—that impact spending the most. [13]

VBID shows promise as a key strategy to help move the nation toward a health care system that rewards value. We must continue to test and establish financial incentives that steer patients toward the most appropriate levels of care for their conditions. The real promise of VBID is to mitigate tension between controlling health care costs and ensuring that patients get the care they need.

 

---

References

1. Lichtenberg. 1996. Am Econ Rev 86(2): 384-88.
2. Lichtenberg. 2001. The Effects of Medicare on Health Care Utilization and Outcomes (Columbia University Press).
3. Dunbar-Jacob, J., J. A. Erlen, E. A. Schlenk, C. M. Ryan, S. M. Sereika, and W. M. Doswell. 2000. Adherence in chronic disease. Annual Review of Nursing Research 18: 48-90.
4. Goldman, D. P., G. F. Joyce, J. J. Escarce, J. E. Pace, M. D. Solomon, M. Laouri, P. B. Landsman, and S. M. Teutsch. 2004. Pharmacy benefits and the use of drugs by the chronically ill. JAMA 291(19): 2344-50. https://doi.org/10.1001/jama.291.19.2344
5. Chernew, M. E., I. A. Juster, M. Shah, A. Wegh, S. Rosenberg, A. B. Rosen, M. C. Sokol, K. Yu-Isenberg, A. M. Fendrick. 2010. Evidence that value-based insurance can be effective. Health Affairs 29(3): 530-36. https://doi.org/10.1377/hlthaff.2009.0119.
6. Chernew, M. E., A. B. Rosen, and A. M. Fendrick. 2007. Value-based insurance design. Health Affairs (Millwood) 26(2): w195-203. https://doi.org/10.1377/hlthaff.26.2.w195
7. Rosen, A. B., M. B. Hamel, M. C. Weinstein, D. M. Cutler, M. Fendrick, and S. Vijan. 2005. Cost-Effectiveness of Full Medicare Coverage of Angiotensin-Converting Enzyme Inhibitors for Beneficiaries with Diabetes. Annals of Internal Medicine 143(2): 89-99. https://doi.org/10.7326/0003-4819-143-2-200507190-00007
8. Chernew, M. E., M. R. Shah, A. Wegh, S. N. Rosenberg, I. A. Juster, A. B. Rosen, M. C. Sokol, K. Yu-Isenberg, and A. M. Fendrick. 2008. Impact of decreasing copayments on medication adherence within a disease management environment. Health Affairs (Millwood) 27(1): 103-12. https://doi.org/10.1377/hlthaff.27.1.103
9. Goldman, D. P., G. F. Joyce, and P. Karaca-Mandic. 2006. Varying Pharmacy Benefits With Clinical Status: The Case of Cholesterol-lowering Therapy. American Journal of Managed Care 12(1): 21-28.
10. Mahoney, J. J. 2008. Value-based benefit design: using a predictive modeling approach to improve compliance. Journal of Managed Care Pharmacy 14(6 Suppl B): 3-8. https://doi.org/10.18553/jmcp.2008.14.S6-B.3
11. Hellinger, F. J. and H. S. Wong. 2000. Selection bias in HMOs: a review of the evidence. Medical Care Research and Review 57(4): 405-39. https://doi.org/10.1177/107755870005700402
12. Baicker, K. and D. Goldman. 2011. Patient Cost-Sharing and Healthcare Spending Growth. Journal of Economic Perspectives 25(2): 47-68.
13. Robinson, J. C. 2010. Applying value-based insurance design to high-cost health services. Health Affairs (Millwood) 29(11): 2009- 16. https://doi.org/10.1377/hlthaff.2010.0469

Tweets by @theNAMedicine