Implementation of patient-centered prescription labeling in a safety-net ambulatory care network
Implementation of patient-centered prescription labeling in a safety-net ambulatory care network
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DOI:
10.2146/ajhp170821
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发表时间:
2018-08-15
影响因子:
2.7
通讯作者:
Sarkar, Urmimala
中科院分区:
文献类型:
--
作者:
Khoong, Elaine C.;Cherian, Roy;Sarkar, Urmimala
Purpose. An initiative to implement patient-centered medication labeling at 4 pharmacies within a publicly funded safety-net healthcare system is described.Summary. Medication nonadherence negatively affects patient outcomes and safety. Nonadherence has been attributed to poor understanding of instructions on medication labels. Research has demonstrated that patient-centered labeling (PCL) can improve adherence and produce safer medication-taking practices. As part of a mixed-methods study by a safety-net health system, audits of nearly 9,000 prescription labels generated at 4 pharmacy sites, as well as interviews with 6 stakeholder informants, were conducted to determine PCL adoption rates and factors contributing to success. Descriptive statistics were used to analyze audit data; constructs of the Consolidated Framework for Implementation Research were used to analyze interview data. Among the 4 sites, 3 pharmacies successfully converted more than 85% of audited prescriptions to a PCL format; 1 pharmacy converted less than 25% of prescriptions. Barriers to implementation included pharmacists' reluctance to modify prescriber instructions and inadequate real-time data on conversion rates. Interviewees perceived that leadership and policy directives promoted PCL conversion efforts. Successful pharmacies used adaptable software, had closer communication networks with prescribers, and/or used automation to facilitate PCL conversion.Conclusion. Three pharmacies successfully converted more than 85% of labels for audited prescriptions to a PCL format; 1 pharmacy converted less than 25% of prescriptions. Barriers to implementation included pharmacists' reluctance to modify prescriber instructions, inadequate real-time data on conversation rates, and lack of customizable software to automate changes.