Bagley, Nicholas, Amitabh Chandra, and Austin Frakt. "Correcting Signals for Innovation in Health Care." Hamilton Project, October, 2015.
A combination of legal rules and institutional forces pushes health plans to cover nearly every medical innovation. The result is that many Americans are effectively forced to over-insure themselves for coverage of some therapies they do not much value. At the same time, others might be willing to spend even more on health plans that would cover therapies that are not considered medically necessary or that have not yet been developed. Technology developers thus receive distorted signals about the size of the market for new innovations, leading them to develop medical treatments that are not in line with what Americans would demand in a wellfunctioning market. Over time, the spending growth fueled by these distorted signals will become increasingly difficult to ignore. Yet the most prominent policy ideas for reining in spending growth concentrate on slowing the rate of technology diffusion. In so doing, they fail to fully grapple with the mix and pace of technology innovation. Our data, for example, show that a third of Medicare’s spending in physician or outpatient settings in 2012 reflects technology that did not exist a decade earlier. Addressing the incentives for technology development, and not just its diffusion once invented, is critical. We therefore advance a handful of policy proposals to adjust the innovation signal. In particular, we propose (1) replacing the tax exclusion for employer-provided health insurance with a tax credit, (2) strengthening Medicare’s coverage determination process, and (3) experimenting with reference pricing for certain therapies in Medicare. Although these proposals may strike some as politically unrealistic, alternative approaches to tackling the one-size-fits-all nature of insurance—in particular, allowing health plans to compete on the scope of what technologies they cover—would require regulations that are unlikely ever to be politically and culturally attractive.