NBER Publications by Anirban Basu

The United States aspires to use information from comparative effectiveness research (CER) to reduce waste and contain costs without instituting a formal rationing mechanism or compromising patient or physician autonomy with regard to treatment choices. With such ambitious goals, traditional combinations of research designs and analytical methods used in CER may lead to disappointing results. In this paper, I study how alternate regimes of comparative effectiveness information help shape the marginal benefits (demand) curve in the population and how such perceived demand curves impact decision-making at the individual patient level and welfare at the societal level. I highlight the need to individualize comparative effectiveness research in order to generate the true (normative) demand cu...

Public technology assessments in general and Comparative Effectiveness Research (CER) in particular have been justified by offsetting benefits of improving patient health and reducing health care spending. However, little conceptual and empirical understanding exists concerning the quantitative impact of public technology assessments such as CER. This is needed to assess whether CER has benefits that outweighs its investment costs. This paper provides a systematic framework to analyze the impact of CER on health outcomes and medical care spending. We interpret CER to infuse evidence on product quality into the market place declaring product winners and losers. This shifts demand by patients and doctors as well as coverage by third party payers towards the winners of CER studies and away ...

Features of Part D gave rise to broad concern that the drug benefit would negatively impact prescription utilization among the six million dual eligible beneficiaries, either during the transition from state Medicaid to Part D coverage, or in the long-run. At the same time, Part D contained other features, such as its auto-enrollment and premium subsidization policies, which were designed to safeguard utilization for this vulnerable group. Using national retail pharmacy claims, we examine the experience of dual eligibles during the first 18 months of Part D. We find no evidence that Part D adversely affected pharmaceutical utilization or out-of-pocket expenditures in the transition period, or in the 18 months subsequent to Part D implementation.

Under the assumption of no unmeasured confounders, a large literature exists on methods that can be used to estimating average treatment effects (ATE) from observational data and that spans regression models, propensity score adjustments using stratification, weighting or regression and even the combination of both as in doubly-robust estimators. However, comparison of these alternative methods is sparse in the context of data generated via non-linear models where treatment effects are heterogeneous, such as is in the case of healthcare cost data. In this paper, we compare the performance of alternative regression and propensity score-based estimators in estimating average treatment effects on outcomes that are generated via non-linear models. Using simulations, we find that in moderate si...