Abstract: Wait time is a key factor of health-care services, yet data is rare, often unreliable, and inconsistently measured across systems. The scarcity of data prevents systematic analyses of allocative inefficiency and inequality in access to health. We propose a measure of wait times - detection to treatment (DTT) - solely based on medical variables, which are both widely available and standardized. DTT records the time elapsed between the detection of a patient as being high-risk of receiving a surgery, and the date of the procedure. We use recurrent neural networks to represent patients’ high-dimensional medical trajectories as a risk profile over time. As expected for a measure of wait times, we find that DTT increases with supply constraints. Patients enrolled in more restrictive insurance plans experience longer DTT and an increase in the load of medical providers increases the wait time. Using provider loads as exogenous variation in wait times, we show that an increase in DTT results in higher medical expenditures, longer hospitalization, and increased use of addictive drugs.
Work in Progress
The Role of Experience in Physician Treatment Decisions: Evidence from the Introduction of Medicare Part D (with Marissa King and Tanja Saxell)
Abstract: How do physicians learn about new treatments? Using the setting of antipsychotic treatment choice, we measure the relative importance of two key pathways: observational learning, in which physicians update their knowledge from public signals, and learning-by-doing, in which the physician relies on her own private experience treating patients. To do so, we exploit two sources of exogenous shocks to physicians’ information. First, in 2007, regulators issued new guidance in the antipsychotic market, approving one drug as a secondary treatment for depression and warning that another posed a substantial risk of side effects. Second, in 2006, the introduction of Medicare Part D shocked the typical physician’s patient composition, with more patients obtaining private insurance coverage. Examining the time periods surrounding the drug advisories, we find physicians with greater patient volume and with more specialized training learn about product quality sooner. Public warnings primarily affect the decisions of the least experienced and least specialized physicians. Importantly, among physicians seeing few patients, recent graduates react more quickly and robustly to the advisories following their publication. We further show that exploiting variation in experience stemming from Medi- care’s insurance expansion is necessary to distinguish the effect of volume from unobserved factors, such as physician quality.