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Claims-based pharmacy markers for comprehensive medication management program case identification: Validation against concurrent and prospective healthcare costs and utilization

Abstract

Background

Three claims-based pharmacy markers (complex, costly and risky medications) were developed to help automatically identify patients for comprehensive medication management.

Objective

To evaluate the association between newly-developed markers and healthcare outcomes.

Methods

This was a two-year retrospective cohort study using PharMetrics Plus patient-level administrative claims in 2014 and 2015. We included all claims from 1,541,873 individuals with: (1) 24-month medical and pharmacy enrollment in 2014 and 2015, (2) aged between 18 and 63 in 2014, and (3) known gender. Independent/control variables came from 2014 while outcomes came from 2014 (concurrent analysis) and 2015 (prospective analysis). Three pharmacy markers, separately or together, were added to four base models to predict concurrent and prospective healthcare costs (total, medical, and pharmacy) and utilization (having any hospitalization, having any emergency department visit, and having any readmission). We applied linear regression for costs while logistic regression for utilization. Measures of model performances and coefficients were derived from a 5-fold cross-validation repeated 20 times.

Results

Individuals with 1+ complex, risky or costly medication markers had higher comorbidity, healthcare costs and utilization than their counterparts. Nine binary risky category markers performed the best among the three types of risky medication markers; the Medication Complexity Score and three-level complex category both outperformed a simpler complex medication indicator. Adding three novel pharmacy markers separately or together into the base models provided the greatest improvement in explaining pharmacy costs, compared with medical (non-medication) costs. These pharmacy markers also added value in explaining healthcare utilization among the simple base models.

Conclusions

Three claims-based pharmacy indicators had positive associations with healthcare outcomes and added value in predicting them. This initial study suggested that these novel markers can be used by pharmacy case management programs to help identify potential high-risk patients most likely to benefit from clinical pharmacist review and other interventions.