-
- Benjamin Ukert, Guy David, and Aaron Smith-McLallen.
- Texas A&M University, 212 Adriance Lab Rd, College Station, TX 77843. Email: bukert@tamu.edu.
- Am J Manag Care. 2022 Dec 1; 28 (12): 668674668-674.
ObjectivesTo evaluate the effect of a predictive algorithm-driven disease management (DM) outreach program compared with non-predictive algorithm-driven DM program participation on health care spending and utilization.Study DesignWe used propensity score matching forMedicare Advantage members with chronic heart failure (CHF) to evaluate the impact of predictive algorithm-driven DM outreach using claims data from 2013 to 2018 from a large commercial health insurer.MethodsThe insurer ran a predictive algorithm to identify members with CHF with a high likelihood of hospitalization (LOH), and a DM outreach was initiated to those identified as being at high risk of hospitalization (high-LOH intervention group). The intervention group was matched to members with similar concurrent medical risk profiles, based on the DxCG/Verisk score, who received the same DM outreach through the insurer's standard process (low-LOH intervention group). This approach allowed an evaluation of the predictive algorithm in targeting individuals suitable for DM outreach.ResultsRegression models showed that high-LOH intervention members had a lower probability of hospitalization (0.032; P = .075) and emergency department (ED) visit (0.039; P = .043) in the year after the outreach compared with low-LOH intervention members, leading to lower total outpatient spending ($1517; P < .001). Analyses for no-intervention members showed that predictive outreach members would have been expected to have higher inpatient and ED utilization and higher medical spending compared with the traditional care members.ConclusionsA prediction-driven DM outreach program among patients with CHF was effective in reducing medical spending in the year after the outreach compared with traditional DM outreach programs.
Notes
Knowledge, pearl, summary or comment to share?