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Hospital Network Competition and Adverse Selection: Evidence from the Massachusetts Health Insurance Exchange

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  • Mark Shepard

Abstract

Health insurers increasingly compete on their networks of medical providers. Using data from Massachusetts's insurance exchange, I find substantial adverse selection against plans covering the most prestigious and expensive "star" hospitals. I highlight a theoretically distinct selection channel: consumers loyal to star hospitals incur high spending, conditional on their medical state, because they use these hospitals' expensive care. This implies heterogeneity in consumers' incremental costs of gaining access to star hospitals, posing a challenge for standard selection policies. Along with selection on unobserved sickness, I find this creates strong incentives to exclude star hospitals, even with risk adjustment in place.

Suggested Citation

  • Mark Shepard, 2022. "Hospital Network Competition and Adverse Selection: Evidence from the Massachusetts Health Insurance Exchange," American Economic Review, American Economic Association, vol. 112(2), pages 578-615, February.
    • Handle: RePEc:aea:aecrev:v:112:y:2022:i:2:p:578-615
    DOI: 10.1257/aer.20201453
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    Citations

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    Cited by:

    1. Mark Shepard & Ethan Forsgren, 2023. "Do insurers respond to active purchasing? Evidence from the Massachusetts health insurance exchange," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(1), pages 9-31, March.
    2. Abe Dunn & Joshua D Gottlieb & Adam Hale Shapiro & Daniel J Sonnenstuhl & Pietro Tebaldi, 2024. "A Denial a Day Keeps the Doctor Away," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 139(1), pages 187-233.
    3. Pietro Tebaldi & Alexander Torgovitsky & Hanbin Yang, 2023. "Nonparametric Estimates of Demand in the California Health Insurance Exchange," Econometrica, Econometric Society, vol. 91(1), pages 107-146, January.
    4. Tuukka Holster & Shaoxiong Ji & Pekka Marttinen, 2024. "Risk adjustment for regional healthcare funding allocations with ensemble methods: an empirical study and interpretation," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 25(7), pages 1117-1131, September.
    5. Buitrago, Giancarlo & Rodríguez-Lesmes, Paul Andrés & Serna, Natalia & Vera-Hernández, Marcos, 2023. "The Role of Hospital Networks in Individual Mortality," Documentos de Trabajo 20945, Universidad del Rosario.
    6. Devesh Raval & Ted Rosenbaum & Nathan E. Wilson, 2022. "Using disaster‐induced closures to evaluate discrete choice models of hospital demand," RAND Journal of Economics, RAND Corporation, vol. 53(3), pages 561-589, September.

    More about this item

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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