Cost-Effectiveness of Medication Therapy Management Program Across Racial and Ethnic Groups Among Medicare Beneficiaries [Editor's Choice]

Abstract

Objectives

Equity and effectiveness of the medication therapy management (MTM) program in Medicare has been a policy focus since its inception. The objective of this study was to evaluate the cost-effectiveness of the Medicare MTM program in improving medication utilization quality across racial and ethnic groups.

Methods

This study analyzed 2017 Medicare data linked to the Area Health Recourses File. A propensity score was used to match MTM enrollees and nonenrollees, and an incremental cost-effectiveness ratio between the 2 groups was calculated. Effectiveness was measured as the proportion of appropriate medication utilization based on medication utilization measures developed by Pharmacy Quality Alliance. Net monetary benefits were compared across racial and ethnic groups at various societal willingness-to-pay (WTP) thresholds. The 95% confidence intervals were obtained by nonparametric bootstrapping.

Results

MTM dominated non-MTM among the total sample (N = 699 992), as MTM enrollees had lower healthcare costs ($31 135.89 vs $32 696.69) and higher proportions of appropriate medication utilization (87.47% vs 85.31%) than nonenrollees. MTM enrollees had both lower medication costs ($10 681.21 vs $11 003.08) and medical costs ($20 454.68 vs $21 693.61) compared with nonenrollees. The cost-effectiveness of MTM was higher among Black patients than White patients across the WTP thresholds. For instance, at a WTP of $3006 per percentage point increase in effectiveness, the net monetary benefit for Black patients was greater than White patients by $2334.57 (95% confidence interval $1606.53-$3028.85).

Conclusions

MTM is cost-effective in improving medication utilization quality among Medicare beneficiaries and can potentially reduce disparities between Black and White patients. Expansion of the current MTM program could maximize these benefits.

Authors

Chi Chun Steve Tsang Ya-Chen Tina Shih Xiaobei Dong Joseph Garuccio Jamie A. Browning Jim Y. Wan Marie A. Chisholm-Burns Samuel Dagogo-Jack William C. Cushman Rose Zeng Junling Wang

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