from Journal of Health Economics at http://bit.ly/2tejvdk on February 11, 2019 at 11:04PM
Publication date: Available online 10 February 2019
Source: Journal of Health Economics
Author(s): Guy David, Aaron Smith-McLallen, Benjamin Ukert
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.