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Contributed Papers in Health Economics

Paper Session

Saturday, Jan. 5, 2019 12:30 PM - 2:15 PM

Hilton Atlanta, 303
Hosted By: Health Economics Research Organization
  • Chair: Michael Fitzmaurice, JMF Associates

Rational Self-Medication

Michael Darden
,
Johns Hopkins University
Nicholas W. Papageorge
,
Johns Hopkins University

Abstract

If an individual has a consumption value for mental health, risky behaviors such as alcohol and tobacco consumption may alleviate the contemporaneous disutility associated with poor mental health. However, risky behaviors are costly in the sense that they draw from income, they potentially contribute to poor overall health, and perhaps most importantly, they potentially worsen future mental health. When technological advancements improve the quality of anti-depressant pharmaceuticals, the incentives to manage mental health with risky behaviors potentially change depending on the level of addiction to risky behaviors. In this paper, we estimate a model of risky behavior and anti-depressant consumption with 40-years of longitudinal data on 2,315 individuals from the Framingham Heart Study: Offspring Cohort. Importantly, during the timeframe of our study, Selective Serotonin Reuptake Inhibitors (SSRI), which dramatically improved the side effects associated with anti-depressant pharmaceuticals, entered the market and spread rapidly. Our goal is to estimate the substitutability between risky behaviors and anti-depressants while allowing for addiction in risky behaviors, which may inhibit substitution.
Reduced-form estimates of the effect of anti-depressants on tobacco and alcohol use, which condition on individual and time fixed effects, suggest strong substitutability between these risky behaviors and anti-depressants for both men and women. However, these estimates do not account for addiction in risky behaviors. Therefore, we estimate an empirical approximation to a dynamic structural model of alcohol, tobacco, and medication decisions which explicitly accounts for the history of consumption as state variables in an optimization problem. We allow the error structure of each equation to be flexibly correlated across equations with the discrete factor method for both time varying and time invariant unobserved heterogeneity. Our model is identified off of time-varying exogenous controls and the exogenous introduction of SSRI anti-depressants. Simulations of the estimated model

Early Life Exposures, Gene-Environment Interactions, and Cognition in Old Age

Atheendar Venkataramani
,
University of Pennsylvania
Jason Fletcher
,
University of Wisconsin-Madison

Abstract

Although there is a large literature linking early childhood exposures to childhood and adult outcomes, the causal evidence on how these exposures affect outcomes in late adulthood and the elderly years is limited. Moreover, the extent to which genetic factors modify the long-run consequences of these early exposures is not well understood. We examined the effects of early life exposure to pneumonia – a leading cause of infant death in the early 20th century – on cognitive outcomes among elderly adults. Leveraging the introduction of sulfonamide antibiotics in 1937 – which led to dramatic reductions in pneumonia morbidity and mortality – along with state-level differences in baseline disease rate – we find that infant exposure led to faster cognitive decline in adulthood. These effects were largest for individuals with higher genetic endowments (as measured by polygenetic scores (PGS) for cognition), and null for those with lower endowments. One interpretation of our finding is that, as environments are improved, those with genetic advantages are more fully able to leverage these improvements, which may increase inequality in cognitive performance over time.

The Impacts of CMS Public Reports of Hospital Charge Data

Kathleen Carey
,
Boston University
Avi Dor
,
George Washington University

Abstract

In May 2013, the Centers for Medicare and Medicaid Services (CMS) began publishing charges for the 100 most frequently billed diagnosis-related groups (DRGs) for inpatients treated in approximately 3,400 U.S. hospitals. The goal was to increase transparency and bring greater market forces to bear on the steep growth in prices for hospital services. While charges are not the same as payments, the data release has several advantages over claims data. The reports are readily available online, national in scope, and the subject of media attention. Charges generally are the starting point for hospital-insurer price negotiations. High charges also have a direct impact on uninsured individuals, who are exposed to full charges, as well as patients covered out-of-network or under workers’ compensation, who generally pay a portion of full charges. This paper examines whether the CMS price transparency initiative is performing as a policy lever in reducing the growth of hospitals prices and explores which stakeholders are the most receptive audiences. More specifically, we address supply side responsiveness by examining trends in hospital inpatient charges and demand side responsiveness by examining trends in volume and market share of inpatient services. Using quasi-experimental designs, we estimated econometric models using charge and utilization data obtained from CMS and from the Florida and New York AHRQ State Inpatient Databases for the years 2011-2015. To examine the impact of the CMS public reports on hospital charges, we estimated difference-in differences models that compared changes in charges for the 100 reported DRGs with changes in charges for the unreported DRGs, controlling for DRG weight, geographic location, and patient factors. To examine the impact of the public reports on consumer choice, we explored shifts in volume and market shares. We selected two reported DRGs
Discussant(s)
John Cawley
,
Cornell University
Jonathan Beauchamp
,
University of Toronto
Zach Brown
,
University of Michigan
JEL Classifications
  • I1 - Health
  • I0 - General