Implications of family risk pooling for individual health insurance markets

  • Anna D. Sinaiko
  • Timothy J. Layton
  • Sherri Rose
  • Thomas G. McGuire


While family purchase of health insurance may benefit insurance markets by pooling individual risk into family groups, the correlation across illness types in families could exacerbate adverse selection. We analyze the impact of family pooling on risk for health insurers to inform policy about family-level insurance plans. Using data on 8,927,918 enrollees in fee-for-service commercial health plans in the 2013 Truven MarketScan database, we compare the distribution of annual individual health spending across four pooling scenarios: (1) “Individual” where there is no pooling into families; (2) “real families” where costs are pooled within families; (3) “random groups” where costs are pooled within randomly generated small groups that mimic families in group size; and (4) “the Sims” where costs are pooled within random small groups which match families in demographics and size. These four simulations allow us to identify the separate contributions of group size, group composition, and family affinity in family risk pooling. Variation in individual spending under family pooling is very similar to that within “simulated families” and to that within random groups, and substantially lower than when there is no family pooling and individuals choose independently (standard deviation $12,526 vs. $11,919, $12,521 and $17,890 respectively). Within-family correlations in health status and utilization do not “undo” the gains from family pooling of risks. Family pooling can mitigate selection and improve the functioning of health insurance markets.


Risk pooling Health insurance Adverse selection 



We thank Randy Ellis, Joe Newhouse, Bastian Ravensteijn, and Richard van Kleef for helpful comments on an earlier draft. The views in this paper are the authors’ alone. Andrew Hicks provided excellent statistical programming assistance.


We gratefully acknowledge funding for this work from the National Institute for Mental Health (R01 MH094290), and the John and Linda Arnold Foundation.

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Anna D. Sinaiko
    • 1
  • Timothy J. Layton
    • 2
    • 3
  • Sherri Rose
    • 2
  • Thomas G. McGuire
    • 2
    • 3
  1. 1.Department of Health Policy and ManagementHarvard T.H. Chan School of Public HealthBostonUSA
  2. 2.Department of Health Care PolicyHarvard Medical SchoolBostonUSA
  3. 3.National Bureau of Economic ResearchCambridgeUSA

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