Public Policy Decision Making

Anyone who has read this blog knows that, in discussing public policy issues, I have always tried to consider both the intended and unintended consequences of government decisions. For example, I have contended that, before governments mandate that “Do Not Mail” registries be created in each state, they should consider the economic and environmental consequences of such registries by both elected and appointed officials. If the goal of reducing unsolicited mail is to improve the environment, that goal may actually be undermined by a change in consumer behavior to engage in more face-to-face retail transactions begun by a drive in a motor vehicle to the retail store.

Using a similar analysis, the regulation jointly issued by the U.S. Departments of Labor, Health and Human Services, and Treasury limiting wellness incentives to 20% of the premiums paid by an employer-based health care plan participant is one which appears to have been decided without reference to whether it will maximize health improvement or lower health care costs for those not receiving the incentives.

The logic of those supporting this kind of wellness incentive limit appears to be that if one plan participant gets a 20% wellness incentive, someone not receiving the incentive is paying more than he or she would otherwise have paid. Hence, I surmise, the government agencies jointly participating in issuing this regulation decided that a 20% limit on incentives struck an appropriate balance between encouraging wellness programs and not having excessive penalties for those not receiving the incentives.

The flaw with this kind of thinking is that it assumes that the incentives do not bring down the overall cost of the program. If the goal is to drive down health care costs for everyone, there is the potential of a benefit for even those not receiving wellness incentives. This would happen if the incentives reduced significantly the total cost of the pool of health care plan participants, thereby benefiting everybody, including those not receiving the incentives. This recentWorld Health Care blog post further questions the reasoning behind the regulation.

I am not sure whether 20% is the right limit, or whether there are some individuals who need only a 5% incentive to do the right thing, and others who need a 50% incentive package. What I do know is that the 20% limit appears to have been created without a rigorous process of testing whether any limit makes sense, and, if so, what that optimal limit might be. What would have made this regulation defensible is if it had been issued after tests of multiple levels of incentives over an extended period of time in several different employer-based health plans I am sure that was not done here.

Government regulations like this have an opportunity to be subject to controlled tests that allow decision makers to determine whether they work to achieve the goals decision makers have in mind. Unfortunately, it does not appear that decision makers are using tools that could make their regulations a great deal more defensible.

This story in the Illinois Business Law Journal, provides a thorough analysis of the new regulation and the relevance of the American with Disabilities Act (ADA).

The book “Super Crunchers” by Ian Ayres, a Yale School of Management professor, has a superb analysis of great public policy decisions, both here in the U.S. and in other countries, that were tested and then broadly implemented after getting good feedback from the testing. For example, the Progresa program tested and implemented broadly in Mexico provided for cash transfers to mothers conditioned upon behaviors such as keeping children in school, getting prenatal care when pregnant, and doing nutrition monitoring. The program had great results, largely because it was well-conceived and implemented, but more importantly, because it was tested narrowly before being broadly rolled out. Mr. Ayres is also featured on the New York Times “Freakonomics” blog.

Citizens expect government leaders to do high-quality decision-making, not solely to do the popular thing or the superficially correct thing. We need better decision-making discipline on issues critical to us, particularly in areas of high emotional impact like health care.

Using data-driven decision-making ultimately saves taxpayer dollars in the long run.