The Department of Health and Human Services (HHS) has released rules for risk adjustment in Exchanges created by the Affordable Care Act (ACA) and a recommended premium age structure, but is delaying the implementation of some other Exchange provisions. States have decided whether to run Exchanges autonomously or in partnership with the Federal government. States are also taking a wide range of policy postures on whether to expand Medicaid under the ACA, with 20 states currently declaring opposition to Medicaid expansion. State-driven policies will set a fluid ACA policy environment for years to come. In RO1-MH094290, Mental Health Coverage in Health Care Reform, our team assessed incentives for Exchange plans to supply care for mental health and other chronic conditions, finding that incentives for underservice were strongest for cancer and mental health care. In a major methodological development, MH094290 identified a simple modification of conventional risk adjustment methods, namely, imposing constraints on least-squares regressions, that can address efficiency problems associated with risk adjustment. Our work so far has used the Medical Expenditure Panel Survey (MEPS). In this competing renewal we propose to refine and extend our methods and to apply them to the very large data sets used for development of actual payment models. We plan to accomplish two aims: First, construct a simulation model of a Health Insurance Exchange using MEPS data to: a) confirm the presence of adverse incentives for mental health (and other chronic illnesses) in Exchanges based on current federal policy; and b) apply constrained regression techniques to address selection incentives within the framework of proposed risk adjustment policy. Second, improve on existing risk- adjustment methodology by: first, using a large MarketScan Exchange eligible adult population that is selected and weighted using the MEPS Exchange population so as to be representative of the spending and illness distribution of likely Exchange participants; second, accounting for payment system features (plan-set premiums and reinsurance) affecting plan risk and incentives; and third, applying the constrained-regression fix for incentives related to selection against those with mental and other chronic illnesses. In addition to academic papers, Aim 2 will produce a potentially implementable optimal risk adjustment model for adults that corrects selection-related incentives.

Public Health Relevance

As of January 1, 2014, US citizens and legal residents who are not eligible for employer-sponsored or public coverage will be able to purchase health insurance through new state-level health insurance markets, referred to as 'Exchanges.' Persons with mental illness and other chronic conditions need special protection in private health insurance markets. This project assesses the incentives to health plans in Exchanges to undersupply care to these groups, develops a solution to this problem by modifying the way plans are paid, and applies this solution to the very large data sets used by the federal government to calibrate payment models.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH094290-04
Application #
8847799
Study Section
Special Emphasis Panel (SERV)
Program Officer
Rupp, Agnes
Project Start
2011-07-09
Project End
2016-04-30
Budget Start
2015-05-01
Budget End
2016-04-30
Support Year
4
Fiscal Year
2015
Total Cost
$594,627
Indirect Cost
$202,872
Name
Harvard Medical School
Department
Administration
Type
Schools of Medicine
DUNS #
047006379
City
Boston
State
MA
Country
United States
Zip Code
02115
Rose, Sherri (2018) Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending. Health Serv Res 53:3836-3854
Geruso, Michael; Layton, Timothy J (2017) Selection in Health Insurance Markets and Its Policy Remedies. J Econ Perspect 31:23-50
Layton, Timothy J; Ellis, Randall P; McGuire, Thomas G et al. (2017) Measuring efficiency of health plan payment systems in managed competition health insurance markets. J Health Econ 56:237-255
Sinaiko, Anna D; Layton, Timothy J; Rose, Sherri et al. (2017) Implications of family risk pooling for individual health insurance markets. Health Serv Outcomes Res Methodol 17:219-236
Ellis, Randall P; Martins, Bruno; Zhu, Wenjia (2017) Health care demand elasticities by type of service. J Health Econ 55:232-243
Layton, Timothy J (2017) Imperfect risk adjustment, risk preferences, and sorting in competitive health insurance markets. J Health Econ 56:259-280
Rose, Sherri; Shi, Julie; McGuire, Thomas G et al. (2017) Matching and Imputation Methods for Risk Adjustment in the Health Insurance Marketplaces. Stat Biosci 9:525-542
van Kleef, Richard C; McGuire, Thomas G; van Vliet, René C J A et al. (2017) Improving risk equalization with constrained regression. Eur J Health Econ 18:1137-1156
Montz, Ellen; Layton, Tim; Busch, Alisa B et al. (2016) Risk-Adjustment Simulation: Plans May Have Incentives To Distort Mental Health And Substance Use Coverage. Health Aff (Millwood) 35:1022-8
McGuire, Thomas G (2016) Achieving Mental Health Care Parity Might Require Changes In Payments And Competition. Health Aff (Millwood) 35:1029-35

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