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The effect of predictive analytics-driven interventions on healthcare utilization

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  • David, Guy
  • Smith-McLallen, Aaron
  • Ukert, Benjamin

Abstract

This paper studies a commercial insurer-driven intervention to improve resource allocation. The insurer developed a claims-based algorithm to derive a member-level healthcare utilization risk score. Members with the highest scores were contacted by a care management team tasked with closing gaps in care. The number of members outreached was dictated by resource availability and not by severity, creating a set of arbitrary cutoff points, separating treated and untreated members with very similar predicted risk scores. Using a regression discontinuity approach, we find evidence that predictive analytics-driven interventions directed at high-risk individuals reduced emergency room and specialist visits, yet not hospitalizations.

Suggested Citation

  • David, Guy & Smith-McLallen, Aaron & Ukert, Benjamin, 2019. "The effect of predictive analytics-driven interventions on healthcare utilization," Journal of Health Economics, Elsevier, vol. 64(C), pages 68-79.
    • Handle: RePEc:eee:jhecon:v:64:y:2019:i:c:p:68-79
    DOI: 10.1016/j.jhealeco.2019.02.002
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    References listed on IDEAS

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    Cited by:

    1. Benjamin Ukert & Guy David & Aaron Smith‐McLallen & Ravi Chawla, 2020. "Do payor‐based outreach programs reduce medical cost and utilization?," Health Economics, John Wiley & Sons, Ltd., vol. 29(6), pages 671-682, June.
    2. Margherita Fort & Andrea Ichino & Enrico Rettore & Giulio Zanella, 2022. "Multicutoff RD designs with observations located at each cutoff: problems and solutions," FBK-IRVAPP Working Papers 2022-01, Research Institute for the Evaluation of Public Policies (IRVAPP), Bruno Kessler Foundation.
    3. Subodha Kumar & Liangfei Qiu & Arun Sen & Atish P. Sinha, 2022. "Putting analytics into action in care coordination research: Emerging issues and potential solutions," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2714-2738, June.
    4. Vanessa Ress & Eva‐Maria Wild, 2024. "The impact of integrated care on health care utilization and costs in a socially deprived urban area in Germany: A difference‐in‐differences approach within an event‐study framework," Health Economics, John Wiley & Sons, Ltd., vol. 33(2), pages 229-247, February.
    5. Luke Connelly & Gianluca Fiorentini & Marica Iommi, 2022. "Supply-side solutions targeting demand-side characteristics: causal effects of a chronic disease management program on adherence and health outcomes," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(7), pages 1203-1220, September.

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    More about this item

    Keywords

    Predictive analytics; Cost containment; Population health management;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I19 - Health, Education, and Welfare - - Health - - - Other

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