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Identifying Consistent High-cost Users in a Health Plan

Comparison of Alternative Prediction Models

Chang, Hsien-Yen, PhD; Boyd, Cynthia M., MD; Leff, Bruce, MD; Lemke, Klaus W., PhD; Bodycombe, David P., ScD; Weiner, Jonathan P., DrPH

doi: 10.1097/MLR.0000000000000566
Original Articles

Background: High-cost users in a period may not incur high-cost utilization in the next period. Consistent high-cost users (CHUs) may be better targets for cost-saving interventions.

Objectives: To compare the characteristics of CHUs (patients with plan-specific top 20% medical costs in all 4 half-year periods across 2008 and 2009) and point high-cost users (PHUs) (top users in 2008 alone), and to build claims-based models to identify CHUs.

Research Design: This is a retrospective cohort study. Logistic regression was used to predict being CHUs. Independent variables were derived from 2007 claims; 5 models with different sets of independent variables (prior costs, medications, diagnoses, medications and diagnoses, medications and diagnoses and prior costs) were constructed.

Subjects: Three-year continuous enrollees aged from 18 to 62 years old from a large administrative database with $100 or more yearly costs (N=1,721,992).

Measures: Correlation, overlap, and characteristics of top risk scorers derived from 5 CHUs models were presented. C-statistics, sensitivity, and positive predictive value were calculated.

Results: CHUs were characterized by having increasing total and pharmacy costs over 2007–2009, and more baseline chronic and psychosocial conditions than PHUs. Individuals’ risk scores derived from CHUs models were moderately correlated (∼0.6). The medication-only model performed better than the diagnosis-only model and the prior-cost model.

Conclusions: Five models identified different individuals as potential CHUs. The recurrent medication utilization and a high prevalence of chronic and psychosocial conditions are important in differentiating CHUs from PHUs. For cost-saving interventions with long-term impacts or focusing on medication, CHUs may be better targets.

*Department of Health Policy & Management

Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health

Department of Medicine, Division of Geriatric Medicine and Gerontology, School of Medicine, Johns Hopkins University

§Center for Population Health Information Technology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD

This study applies the ACG case-mix/risk-adjustment methodology, developed at Johns Hopkins Bloomberg School of Public Health. Although ACGs are an important aspect of the paper, the goal of this paper is not to directly assess or evaluate the methodology. The Johns Hopkins University receives royalties for nonacademic use of software based on the ACG methodology. All authors receive a portion of their salary support from this revenue.

Reprints: Hsien-Yen Chang, PhD, Department of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Room 682, 624 N. Broadway, Baltimore, MD, 21205. E-mail:

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