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Cost Effectiveness Analysis and the Design of Cost-Sharing in Insurance: Solving a Puzzle, by Mark Pauly  (The National Bureau of Economic Research)

The conventional model for the use of cost effectiveness analysis for health programs involves determining whether the cost per unit of effectiveness of the program is better than some socially determined maximum acceptable cost per unit of effectiveness. If a program is better, the policy implication is that it should be implemented by full coverage of its cost by insurance; if not, no coverage should be provided and the program should not be implemented. This paper examines the unanswered question of how cost effectiveness analysis should be performed and interpreted when insurance coverage can involve non-negligible cost sharing. It explores both the question of how cost effectiveness is affected by the presence of cost sharing, and the more fundamental question of cost effectiveness when cost sharing is itself set at the cost effective level. Both a benchmark model where only “societal” preferences (embodied in a threshold value of dollars per unit of health) matter and a model where individual willingness to pay can be combined with societal values are considered. A common view that cost sharing should vary inversely with program cost effectiveness is shown to be incorrect. A key issue in correct analysis is whether there is heterogeneity either in marginal effectiveness of care or marginal values of care that cannot be perceived by the social planner but is known by the demander. The cost effectiveness of a program is shown to depend upon the level of cost sharing; it is possible that some programs that would fail the social test at both zero coverage and full coverage will be acceptable with positive cost sharing. Combining individual and social preferences affects both the choice of programs and the extent of cost sharing.

Behavioral Hazard in Health Insurance, by Katherine Baicker, Sendhil Mullainathan and Joshua Schwartzstein (The National Bureau of Economic Research)

This paper develops a model of health insurance that incorporates behavioral biases. In the traditional model, people who are insured overuse low value medical care because of moral hazard. There is ample evidence, though, of a different inefficiency: people underuse high value medical care because they make mistakes. Such “behavioral hazard” changes the fundamental tradeoff between insurance and incentives. With only moral hazard, raising copays increases the efficiency of demand by ameliorating overuse. With the addition of behavioral hazard, raising copays may reduce efficiency by exaggerating underuse. This means that estimating the demand response is no longer enough for setting optimal copays; the health response needs to be considered as well. This provides a theoretical foundation for value-based insurance design: for some high value treatments, for example, copays should be zero (or even negative). Empirically, this reinterpretation of demand proves important, since high value care is often as elastic as low value care. For example, calibration using data from a field experiment suggests that omitting behavioral hazard leads to welfare estimates that can be both wrong in sign and off by an order of magnitude. Optimally designed insurance can thus increase health care efficiency as well as provide financial protection, suggesting the potential for market failure when private insurers are not fully incentivized to counteract behavioral biases.

Why Doctors Prescribe Opioids to Known Opioid Abusers, by Anna Lembke (The New England Journal of Medicine)

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