Estimating the Impact of Medical Innovation : A Case Study of HIV Antiretroviral Treatments

As health care consumes a growing share of national income in the U.S., the demand for better estimates regarding both the benefits and the costs of new health care treatments is likely to increase. Estimating these effects with observational data is difficult given the endogeneity of treatment decisions. But because the random assignment clinical trials (RACTs) used in the FDA's approval process do not consider costs, there is often no good alternative. In this study we use administrative data from the Medicaid program to estimate the impact of a particular category of new treatments - HIV antiretroviral drugs - on health care spending and health outcomes. We use the detailed information on health care utilization to proxy for health status and exploit the differential take-up of ARVs following their FDA approval. Our estimate of a 70 percent reduction in mortality is in line with the results from RACTs and with studies that had more detailed clinical data. We also find that the ARVs lowered short-term health care spending by reducing expenditures on other categories of medical care. Combining these two effects we estimate the cost per life year saved at $22,000. Our results suggest that the administrative data that is readily available from programs like Medicaid, used with a properly specified econometric model that allows for heterogeneity in take-up rates and in effectiveness based on initial health conditions, can produce reliable estimates of the impact of new health care treatments on both spending and health