The effect of predictive analytics-driven interventions on healthcare utilization. Academic Article uri icon


  • 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.

published proceedings

  • J Health Econ

altmetric score

  • 30.2

author list (cited authors)

  • David, G., Smith-McLallen, A., & Ukert, B.

citation count

  • 12

complete list of authors

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

publication date

  • March 2019