The effect of predictive analytics-driven interventions on healthcare utilization
Smith-McLallen, Aaron and
Journal of Health Economics, 2019, vol. 64, issue C, 68-79
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.
Keywords: Predictive analytics; Cost containment; Population health management (search for similar items in EconPapers)
JEL-codes: I10 I12 I19 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jhecon:v:64:y:2019:i:c:p:68-79
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