The effect of predictive analytics-driven interventions on healthcare utilization

Journal of Health Economics
Guy DavidBenjamin Ukert

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.

Citations

Feb 13, 2020·Health Economics·Benjamin UkertRavi Chawla
Oct 13, 2020·Substance Abuse : Official Publication of the Association for Medical Education and Research in Substance Abuse·Elizabeth SkoyMark Strand
Nov 15, 2019·Journal of the American College of Cardiology·Muthiah VaduganathanScott D Solomon

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