ArticleAnnals of clinical epidemiology2026
Effect of educational intervention on polypharmacy management among community pharmacists: An interrupted time series analysis.
Article in Annals of clinical epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
backgroundPolypharmacy management represents a public health concern; however, intervention by community pharmacists remains limited. Therefore, we evaluated the effectiveness of community pharmacy-based educational intervention for improving polypharmacy management using interrupted time series analysis (ITSA).
methodsWe conducted the ITSA of an educational intervention implemented from June to September 2021 across pharmacies under Medical System Network Co., Ltd., Japan. We analyzed pharmacy claims data from April 2020 to May 2024, with no missing values. The intervention included lectures and workshops delivered via cascade training. The primary and secondary outcomes were the number of Fee for Medication Adjustment Support 2 (FMAS2) and Fee for Medication Adjustment Support 1 (FMAS1) per 100,000 patients, respectively. FMAS2 is claimed when pharmacists propose reducing medications for patients taking six or more medications from multiple institutions, and FMAS1 is claimed when the proposal leads to actual reduction.
resultsThe study included 404 pharmacies with an average of 569,909 patients per month. After intervention, FMAS2 claims immediately increased by 3.82 per 100,000 people (95% confidence interval (CI): 1.23 to 6.41, p = 0.005), with no significant trend change. FMAS1 claims first increased by 1.29 per 100,000 people (95% CI: 0.49 to 2.09, p = 0.002) but decreased thereafter (95% CI: -0.298 to -0.130, p < 0.001).
conclusionsEducational intervention increased FMAS2 and FMAS1 claims in the short term. However, the clinical impact of this intervention was small, and its long-term effectiveness is limited. Future efforts should focus on developing sustainable programs and follow-up systems.
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