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Activity Number: 493
Type: Contributed
Date/Time: Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
Sponsor: Health Policy Statistics Section
Abstract #317309 View Presentation
Title: Using Causal Framework to Estimate an Impact of Changes in Demand and Pricing on the Health Care Bill
Author(s): Irina Bondarenko* and Trivellore Raghunathan and David Cutler and James Shaffer and Kaushik Ghosh
Companies: University of Michigan and University of Michigan and Harvard University, National Bureau of Economic Research and University of Pennsylvania and National Bureau of Economic Research
Keywords: causal inference ; healthcare spending ; counterfactual ; attributed cost
Abstract:

For the last several decades, health care spending in the United States has grown at a much more rapid rate than the economy as a whole. The three major factors contributing towards this trend could be changes in (1) the prevalence rate of diseases; (2) the pattern of utilization of care, and (3) general inflation in healthcare prices. We use a causal inference framework to parse contributions of these three factors on the overall health expenditure. We estimate various potential expenditures assuming that the demand or pricing of healthcare is kept at hypothetical values. Then, we compared these potential expenditures to the observed spending per person and estimated the impact of changes in demand and pricing on the observed trend. We applied the proposed method to the Medicare population of 65 years and older and analyzed the data from 1999-2009 Medicare Current Beneficiary Surveys to estimate the contribution of pricing and demand to ultimately parse the average 3.8% annual increase of healthcare expenditure in elderly population in the United States.


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