Design and evaluation of an electronic prospective medication order review system for medication orders in the inpatient setting.

IF 2.5 Q2 HEALTH CARE SCIENCES & SERVICES
JAMIA Open Pub Date : 2024-01-27 eCollection Date: 2024-04-01 DOI:10.1093/jamiaopen/ooae003
Pooja Ojha, Benjamin J Anderson, Evan W Draper, Susan M Flaker, Mark H Siska, Kristin C Mara, Brian D Kennedy, Diana J Schreier
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引用次数: 0

Abstract

Objectives: Since the 1970s, a plethora of tools have been introduced to support the medication use process. However, automation initiatives to assist pharmacists in prospectively reviewing medication orders are lacking. The review of many medications may be protocolized and implemented in an algorithmic fashion utilizing discrete data from the electronic health record (EHR). This research serves as a proof of concept to evaluate the capability and effectiveness of an electronic prospective medication order review (EPMOR) system compared to pharmacists' review.

Materials and methods: A subset of the most frequently verified medication orders were identified for inclusion. A team of clinical pharmacist experts developed best-practice EPMOR criteria. The established criteria were incorporated into conditional logic built within the EHR. Verification outcomes from the pharmacist (human) and EPMOR (automation) were compared.

Results: Overall, 13 404 medication orders were included. Of those orders, 13 133 passed pharmacist review, 7388 of which passed EPMOR. A total of 271 medication orders failed pharmacist review due to order modification or discontinuation, 105 of which passed EPMOR. Of the 105 orders, 19 were duplicate orders correctly caught by both EPMOR and pharmacists, but the opposite duplicate order was rejected, 51 orders failed due to scheduling changes.

Discussion: This simulation was capable of effectively discriminating and triaging orders. Protocolization and automation of the prospective medication order review process in the EHR appear possible using clinically driven algorithms.

Conclusion: Further research is necessary to refine such algorithms to maximize value, improve efficiency, and minimize safety risks in preparation for the implementation of fully automated systems.

针对住院病人用药医嘱的电子前瞻性用药医嘱审查系统的设计与评估。
目标:自 20 世纪 70 年代以来,已经推出了大量工具来支持用药流程。然而,协助药剂师前瞻性审核用药指令的自动化措施却很缺乏。利用电子健康记录 (EHR) 中的离散数据,可以以算法方式对许多药物进行规程化审查和实施。本研究作为概念验证,旨在评估电子前瞻性用药医嘱审核(EPMOR)系统与药剂师审核相比的能力和有效性:材料和方法:研究人员确定了最常核查的药单子集。由临床药剂师组成的专家小组制定了 EPMOR 的最佳实践标准。已建立的标准被纳入电子病历中的条件逻辑。比较了药剂师(人工)和 EPMOR(自动化)的验证结果:结果:共纳入 13 404 份用药单。在这些订单中,13 133 份通过了药剂师的审核,其中 7388 份通过了 EPMOR 的审核。共有 271 份医嘱因修改或中止而未通过药剂师审核,其中 105 份通过了 EPMOR。在这 105 份医嘱中,有 19 份重复医嘱被 EPMOR 和药剂师同时正确捕获,但相反的重复医嘱却被拒绝,51 份医嘱因计划变更而未通过:讨论:该模拟程序能够有效地识别和分流订单。讨论:该模拟能够有效地分辨和分流医嘱,利用临床驱动的算法,在电子病历中实现预期用药医嘱审核流程的协议化和自动化似乎是可能的:结论:有必要进一步研究完善此类算法,以实现价值最大化、提高效率并将安全风险降至最低,为全自动系统的实施做好准备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JAMIA Open
JAMIA Open Medicine-Health Informatics
CiteScore
4.10
自引率
4.80%
发文量
102
审稿时长
16 weeks
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