Predictive value positive of MTM eligibility criteria under MMA and ACA in identifying individuals with medication utilization issues. Issue 4 (7th September 2018)

• Record Type: Journal Article
• Authors: Qiao, Yanru; Spivey, Christina A.; Wang, Junling; Shih, Ya‐Chen Tina; Wan, Jim Y.; Kuhle, Julie; Dagogo‐Jack, Samuel; Cushman, William C.; Chisholm‐Burns, Marie
• Is Part Of: Journal of pharmaceutical health services research. Volume 9:Issue 4(2018:Dec.)
• Page Start: 393
• Page End: 401
• Publication Date: 2018-09-07
• Subjects: eligibility criteria -- Medicare Prescription Drug, Improvement and Modernization Act -- medication therapy management services -- medication utilization issues -- Patient Protection and Affordable Care Act -- predictive value positive; Pharmacy -- Research -- Periodicals; Drugs -- Research -- Periodicals; Medical care -- Research -- Periodicals; Public health -- Research -- Periodicals; Pharmaceutical industry -- Periodicals; Health Services Research -- Periodicals; Economics, Pharmaceutical -- Periodicals; 615.1072
• DOI: 10.1111/jphs.12266
• Languages: English
• ISSNs: 1759-8885

Abstract

Abstract: Objectives: To compare the predictive value positives (PVP) of medication therapy management eligibility criteria under the Medicare Modernization Act (MMA) and Affordable Care Act (ACA) in identifying individuals with medication utilization issues (MUI). Methods: This is a retrospective analysis of Medicare database (2012–2013). MUI were determined based on medication utilization measures related to Medicare Part D Star Ratings. PVP or proportions of individuals with MUI were compared between individuals eligible for medication therapy management (MTM) under MMA and ACA. Need‐based and demand‐based logistic regression was used to adjust for patient characteristics. MTM eligibility thresholds in 2009 and 2013 and proposed 2015 MTM eligibility thresholds under MMA were examined. Main/sensitivity/disease‐specific analyses were conducted to cover the range of eligibility thresholds and combinations. Key Findings: MMA has higher PVP in identifying patients with MUI than ACA. Proportions of individuals with MUI were higher based on MMA than ACA (e.g. 74.96% for 2009 MMA, 73.51% for 2013 MMA, and 62.46% for proposed 2015 MMA vs. 52.17% for ACA in main analysis; P < 0.05). Adjusted findings were similar. For example, based on the demand‐based model in the main analysis, the odds ratios were 2.474 (95% CI: 2.454–2.494) for 2013 MMA in comparison to ACA. These numbers indicate that the MMA MTM eligibility criteria for 2013 had 147.4% higher PVP in identifying patients with MUI than ACA. Similar patterns were found in most sensitivity and disease‐specific analyses. Conclusions: MMA has higher PVP than ACA in identifying patients with MUI. This study may inform the government on future MTM policy.