Paul Cohen

Traditional insurance prices health products and services according to their cost. Formularies, which are the schedules of drug benefits created by insurance plans, operate under a one size fits all model. As a result, insurance plans inadvertently discourage many health behaviors with high clinical value by charging for them at prices irrespective of their benefit to the patient. This leads to misaligned incentives and suboptimal outcomes. For example, a 2004 study demonstrated that decreasing medication co-payments for patients with coronary heart disease (the leading cause of death [pdf]) from $20 to $10 increased medication adherence from 49% to 76%. Poor medication adherence alone accounts for about 15% of total health care [pdf] spending in the United States, and a nontrivial portion of this expense could be prevented by removing cost barriers to accessing medications.

 

Value-Based Insurance Design
Value-based insurance design (VBID) aims to solve the failure of the cost-based, one size fits all approach. VBID acknowledges decades of behavioral economics research demonstrating that humans do not follow the strict axioms of rational decision making. VBID recognizes patient heterogeneity and adjusts out-of-pocket costs to match the expected clinical benefit according to evidence-based research. While traditional insurance design pairs a patient with an insurance product, the value-based insurance product is optimized for the patient, who is unable to properly assess the costs and benefits of most clinical options. VBID suggests that a patient with coronary heart disease should have lower co-payments for medications that drive the best outcomes. An insurance plan might also waive co-payments for routine physician visits for patients with chronic disease. These outpatient interactions are designed to monitor health, ensure medication adherence, and spot early indications of condition deterioration – often preventing expensive emergency inpatient care. VBID typically offers disease prevention programs promoting physical activity and proper nutrition at little to no cost. Type 2 diabetes adds an average of $85,000 in lifetime health care costs, so the expected outcome of preventive measures is often worth the up-front investment, as at least one empirical study has shown. At the same time, VBID discourages the use of high cost, low value services. Identifying these services is challenging and sometimes controversial, but there are obvious interventions that reduce systemic costs. Colonoscopies in the same city frequently vary in price by up to 300%. VBID often implements reference pricing to reduce overpaid diagnostic tests. Value-based insurance design helps alleviate the patient decision burden by incentivizing the high value services that improve health outcomes.

 

The Challenge of Economic Incentives
The Affordable Care Act follows the value-based insurance approach by permitting incentives for favorable behaviors, such as smoking cessation, weight loss, and exercise. These incentives are primarily economic – e.g., insurers may levy a 50% premium surcharge for smokers. Will it work?  The empirics tell a mixed message. While 87% of large employers offer wellness programs, participation rates are abysmally low (5% to 8%). Benefit consultant Towers Watson predicted that an incentive of $350 per employee would be required to boost health risk appraisal (HRA) participation above 50%. The story is worse for more involved wellness programs that could meaningfully impact health outcomes and costs. Fewer than 10% of employees even attempt to enroll in a weight loss program, even when offered $600 or more to participate. Economic incentives are a necessary but insufficient component of value-based insurance design.

Behavioral Sciences and Population Health
The rules of trade will be rewritten as our health care system reorients towards population health. In the coming decade of care delivery and reimbursement experimentation, the roles of payers (“payors”), providers, and employers will shift in potentially dramatic ways. Accountable care organizations (ACOs) paid under some combination of capitation and fee-for-service with shared savings arrangements will shift risk to providers, who will be incented on patient outcomes. With the shift from reactive treatment and hospitalization to proactive prevention, many revenue line items on a hospital P&L will swap places with expenses. A real challenge for payers and providers in the coming decade will be to orchestrate behavioral change at scale – using techniques that go beyond economic incentives. But who owns these capabilities?  Providers know how to treat illness. Insurers understand how to manage actuarial risk. And self-insured employers know how to write big checks. How can physicians conduct patient outreach and activation?  What tools can they use to encourage patients to join weight loss programs, change their diet, or start exercising?  And how do they monitor and coach patients through these behavioral changes?

The behavioral sciences will play an important role in this transformation, but the current capability gap is enormous. We know more about an individual as a consumer of discretionary products than as a consumer of essential health services. And we do more to convince the former to buy expensive headphones than the latter to get a flu shot. The academic community has proactively increased research at the intersection of health and decision theory. Most notably, the University of Pennsylvania’s schools of medicine, law, and business have joined together with Carnegie Mellon’s Center for Behavioral Decision Research to form the Center for Health Incentives and Behavioral Economics (CHIBE). But we can start with the existing playbook used by advertisers and begin applying these techniques more aggressively to drive health outcomes and improve lives. We can’t afford to do otherwise.