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Impact of Star Rating Medication Adherence Measures on Adherence for Targeted and Nontargeted Medications.

Parekh N, Munshi KD, Hernandez I, Gellad WF, Henderson R, Shrank WH. Impact of Star Rating Medication Adherence Measures on Adherence for Targeted and Nontargeted Medications. Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research. 2019 Nov 1; 22(11):1266-1274.

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Abstract:

BACKGROUND: In 2012, Medicare incorporated medication adherence targeting oral antidiabetic medications, renin-angiotensin system (RAS) antagonists, and statins as highly weighted components in its Star Ratings Program. In the same year, health plans began receiving quality bonus payments for higher star ratings. OBJECTIVE: We aimed to assess how these policy changes affected adherence to targeted and other chronic disease medications in the United States. METHODS: We performed interrupted time series analyses to assess monthly changes in medication adherence from 2010 to 2016 using health plans' Medicare claims submitted to a large pharmacy benefits manager. We conducted 2 sets of analyses. The first examined whether policy changes affected adherence to the 3 targeted therapy classes, and the second assessed the association between policy changes and adherence to 5 chronic disease classes not targeted by star ratings. For the second analysis, we further compared adherence between members who concomitantly used and did not use targeted medications. RESULTS: For star-ratings analyses, we studied 240 811 members on oral antidiabetic medications, 500 958 on RAS antagonists, and 471 135 on statins. Adherence for all star rating-targeted and nontargeted medications increased after 2012 (P < .001). Oral antidiabetic, statin, and RAS antagonist adherence was, respectively, 11.2%, 3.7%, and 8.1% higher than adherence without policy changes (P < .001). Nontargeted antihypertensive and antihyperlipidemic adherence trends were higher among those concomitantly on star rating-targeted medications compared with those who were not (P < .001). CONCLUSIONS: As policy makers strive to identify optimal quality measures for improving healthcare delivery, it is important to consider that incentives can promote improved performance in both targeted measures and related outcomes.




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