Addition of pharmacy cost data improves performance of the Adjusted Clinical Groups predictive model for total health care costs overall and within disease specific groups

Published: June 9, 2004
Category: Bibliography > Reports
Authors: Meyer C, Pierson P, Powers CA, Vaziri B
Countries: United States
Language: null
Types: Care Management
Settings: Hospital

Value in Health 7:371.

AdvancePCS, Hunt Valley, MD, USA

OBJECTIVE: To determine the effect of adding the pharmacy cost data option to the Adjusted Clinical Groups Predictive Model (ACG-PM) when estimating future total health care costs.

METHODS: Longitudinal analysis using medical and pharmacy claims data from a large state employer over a 2-year period (baseline May 1, 2001—April 30, 2002; follow-up May 1, 2002—April 30, 2003). Continuously eligible subjects $10,000) and comparing the positive predictive value (PPV) within each cost grouping. Sensitivity and specificity were also individually examined. Analyses were additionally conducted within disease-specific subgroups, including diabetes, depression, asthma, and cardiovascular disease.

RESULTS: In the baseline year, approximately 70% and 75% of the 344,834 included subjects used medical and pharmacy services, respectively. Baseline total cost averaged $2,665 (median: $621) and pharmacy cost averaged $640 (median: $167). Follow-up mean actual total cost was $3193 (median: $748) and mean ACG-PM predicted costs were $2789 from both models without and with pharmacy costs (respective medians: $1638; $1635). Including pharmacy costs in the model increased the PPV, especially at high-cost groups: 40.77% to 48.74% (+7.97%) at >$10,000 and 23.97% to 28.18% (+4.21%) at $5,001–$10,000. PPVs were higher within disease-specific subgroups and increased with inclusion of pharmacy costs, with the highest PPVs in the depression cohort (>10,000: 51.31% (without pharmacy costs) to 58.92% (with pharmacy costs); $5,000-$10,000: 29.92% to 35.31%).

CONCLUSIONS: Addition of pharmacy cost data to the ACG-PM results in more accurate identification of future total health care costs, especially among high-cost members.

Cost Burden Evaluation,High-Impact Chronic Conditions,Total Disease Burden,United States

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