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Activity Number: 119 - SPEED: Government and Health Policy
Type: Contributed
Date/Time: Monday, July 30, 2018 : 8:30 AM to 10:20 AM
Sponsor: Health Policy Statistics Section
Abstract #328838 Presentation
Title: Intervening on the Data to Improve the Performance of Health Plan Payment Methods
Author(s): Savannah Bergquist* and Tim Layton and Tom McGuire and Sherri Rose
Companies: Harvard University and Harvard Medical School and Harvard Medical School and Harvard Medical School
Keywords: Risk Adjustment; Medicare; Disparities; Mental Health

The conventional method for developing health care plan payment systems uses observed data to study alternative algorithms and set incentives for the health care system. In this paper, we take a different approach and modify the input data rather than the algorithm, so that the data used reflect the desired spending levels rather than the observed spending levels. We call our proposed method "intervening on the data." We present a general economic model that incorporates the previously overlooked two-way relationship between health plan payment and insurer actions. We demonstrate our approach in two Medicare applications: underprovision of care for individuals with chronic illnesses and health care disparities by geographic income levels. Empirically comparing intervening on the data to two other common approaches shows the "side effects" of these approaches vary by context, and that intervening on the data is an effective method for addressing misallocations in individual health insurance markets.

Authors who are presenting talks have a * after their name.

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