Clinical Pharmacy Services, Marshfield Clinic Health System, Marshfield, Wisconsin, USA.
School of Pharmacy, Concordia University Wisconsin, Mequon, Wisconsin, USA.
J Am Med Inform Assoc. 2021 Jan 15;28(1):113-118. doi: 10.1093/jamia/ocaa259.
Wrong drug product errors occurring in community pharmacies often originate at the transcription stage. Electronic prescribing and automated product selection are strategies to reduce product selection errors. However, it is unclear how often automated product selection succeeds in outpatient pharmacy platforms.
The intake of over 800 e-prescriptions was observed at baseline and after intervention to assess the rate of automated product selection success. A dispensing accuracy audit was performed at baseline and postintervention to determine whether enhanced automated product selection would result in greater accuracy; data for both analyses were compared by 2x2 Chi square tests. In addition, an anonymous survey was sent to a convenience sample of 60 area community pharmacy managers.
At baseline, 79.8% of 888 e-prescriptions achieved automated product selection. After the intervention period, 84.5% of 903 e-prescriptions achieved automated product selection (P = .008). Analysis of dispensing accuracy audits detected a slight but not statistically significant improvement in accuracy rate (99.3% versus 98.9%, P = .359). Fourteen surveys were returned, revealing that other community pharmacies experience similar automated product selection failure rates.
Our results suggest that manual product selection by pharmacy personnel is required for a higher than anticipated proportion of e-prescriptions received and filled by community pharmacies, which may pose risks to both medication safety and efficiency.
The question of how to increase automated product selection rates and enhance interoperability between prescriber and community pharmacy platforms warrants further investigation.
社区药店中发生的错误用药产品通常起源于转录阶段。电子处方和自动产品选择是减少产品选择错误的策略。然而,尚不清楚自动产品选择在外用药房平台上的成功率有多高。
在基线和干预后观察了超过 800 份电子处方的摄入情况,以评估自动产品选择成功率。在基线和干预后进行了配药准确性审核,以确定增强自动产品选择是否会导致更高的准确性;通过 2x2 卡方检验比较这两种分析的数据。此外,还向 60 名地区社区药店经理的便利样本发送了匿名调查。
基线时,888 份电子处方中有 79.8%实现了自动产品选择。干预后,903 份电子处方中有 84.5%实现了自动产品选择(P =.008)。配药准确性审核分析发现准确性略有提高,但无统计学意义(99.3%对 98.9%,P =.359)。共收回 14 份调查,表明其他社区药店也经历了类似的自动产品选择失败率。
我们的结果表明,社区药店收到和填写的电子处方中,需要人工选择产品的比例高于预期,这可能对药物安全性和效率都构成风险。
如何提高自动产品选择率并增强开方者和社区药店平台之间的互操作性是一个值得进一步研究的问题。