Impact of a Clinical Pharmacist-Led, Artificial Intelligence-Supported Medication Adherence Program on Medication Adherence Performance, Chronic Disease Control Measures, and Cost Savings.

IF 2.5 4区 医学 Q3 PHARMACOLOGY & PHARMACY
Charles Worrall, David Shirley, Jeff Bullard, Ashley Dao, Taylor Morrisette
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Abstract

Background: Chronic diseases are the leading cause of disability and death in the United States. Clinical pharmacists have been shown to optimize health outcomes and reduce healthcare expenditures in patients with chronic diseases through improving medication adherence.

Objective: The primary objective of this study was to evaluate a pharmacist-led, artificial intelligence-supported medication adherence program on medication adherence, select disease control measures, and healthcare expenditures.

Methods: This was a multicenter, retrospective, quasi-experimental evaluation from January 2019 to December 2019 (pre-implementation) and January 2021 to December 2021 (post-implementation). This pharmacy-driven service focuses on improving medication adherence and patient outcomes through artificial intelligence-supported analytics, individual patient case review, and pharmacist-led individual patient outreach. The primary endpoint was to determine if implementation improved medication adherence in three medication-related measures: medication adherence for hypertension (MAH), medication adherence for cholesterol (MAC), and medication adherence for diabetes (MAD). Secondary outcomes were to evaluate reductions in select chronic diseases control measures and cost savings of this service following implementation of this service.

Results: This medication adherence service was deployed across 10,477 patients: 60.6% of patients were in at least one medication-related measure, generating 2,762 actionable medication adherence gaps. Following the implementation of this pharmacist-led program, medication adherence improved in all three disease state measures (MAH: 5.9% improvement; MAC: 7.9% improvement; MAD: 6.4% improvement), and Medicare Star ratings also improved. The percentage of patients with diabetes who reached their A1c goal also increased (75.5% to 81.7%). Furthermore, reductions in overall healthcare expenditures were seen per member per month in patients that were adherent in comparison to those who were non-adherent (hypertension: 31% cost savings; hyperlipidemia 25% cost savings; diabetes: 32% cost savings).

Conclusion: This clinical pharmacist driven service leveraged technology and patient connection to increase medication adherence in patients with chronic disease states and led to improvement in select disease control measures and substantial healthcare cost savings.

临床药剂师主导、人工智能支持的用药依从性计划对用药依从性表现、慢性病控制措施和成本节约的影响。
背景:在美国,慢性病是导致残疾和死亡的主要原因。临床药剂师通过改善慢性病患者的用药依从性,已被证明能优化健康结果并减少医疗支出:本研究的主要目的是评估由药剂师主导、人工智能支持的用药依从性计划对用药依从性、特定疾病控制措施和医疗支出的影响:这是一项多中心、回顾性、准实验性评估,评估时间为 2019 年 1 月至 2019 年 12 月(实施前)和 2021 年 1 月至 2021 年 12 月(实施后)。这项药学驱动的服务侧重于通过人工智能支持的分析、个体患者病例审查和药剂师主导的个体患者外联活动,改善患者的用药依从性和治疗效果。主要终点是确定该服务的实施是否改善了三种用药相关指标的用药依从性:高血压用药依从性(MAH)、胆固醇用药依从性(MAC)和糖尿病用药依从性(MAD)。次要结果是评估实施这项服务后,某些慢性病控制措施的减少情况以及这项服务的成本节约情况:结果:10,477 名患者接受了这项服药依从性服务:60.6%的患者至少有一项用药相关措施,产生了 2762 个可操作的用药依从性差距。在实施这项由药剂师主导的计划后,三种疾病状态的用药依从性均有所改善(MAH:改善了 5.9%;MAC:改善了 7.9%;MAD:改善了 6.4%),医疗保险星级评价也有所提高。达到 A1c 目标的糖尿病患者比例也有所提高(从 75.5% 提高到 81.7%)。此外,与未坚持治疗的患者相比,坚持治疗的患者每人每月的总体医疗支出有所减少(高血压:节省 31% 的费用;高脂血症:节省 25% 的费用;糖尿病:节省 32% 的费用):这项由临床药剂师推动的服务利用技术和与患者的联系来提高慢性病患者的用药依从性,从而改善了选定的疾病控制措施,节省了大量医疗成本。
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来源期刊
CiteScore
3.30
自引率
14.30%
发文量
336
审稿时长
46 days
期刊介绍: The Journal of the American Pharmacists Association is the official peer-reviewed journal of the American Pharmacists Association (APhA), providing information on pharmaceutical care, drug therapy, diseases and other health issues, trends in pharmacy practice and therapeutics, informed opinion, and original research. JAPhA publishes original research, reviews, experiences, and opinion articles that link science to contemporary pharmacy practice to improve patient care.
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