Iterative Development of a Clinical Decision Support Tool to Enhance Naloxone Co-Prescribing.

IF 2.1 2区 医学 Q4 MEDICAL INFORMATICS Applied Clinical Informatics Pub Date : 2024-10-25 DOI:10.1055/a-2447-8463
Richard Wu, Emily Foster, Qiyao Zhang, Tim Eynatian, Rebecca Grochow Mishuris, Nicholas Cordella
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Abstract

Background Opioid overdoses have contributed significantly to mortality in the United States. Despite long-standing recommendations from the Centers for Disease Control and Prevention to co-prescribe naloxone for patients receiving opioids who are at high risk of overdose, compliance with these guidelines has remained low. Objectives The objective of this study was to develop and evaluate a hospital-wide electronic health record (EHR)-based clinical decision support (CDS) tool designed to promote naloxone co-prescription for high-risk opioids. Methods We employed an iterative approach to develop a point-of-order, interruptive EHR alert as the primary intervention and assessed naloxone prescription rates, EHR efficiency metrics, and barriers to adoption. Data was obtained from our EHR's clinical data warehouse and analyzed using statistical process control and Chi-square analyses to assess statistically significant differences in prescribing rates during the intervention periods. Results The initial implementation phase of the intervention, spanning from April 2019 to May 2022, yielded a nearly 3-fold increase in the proportion of high-risk patients receiving naloxone, rising from 13.4% [95% CI, 12.9% - 13.8%] to 36.4% [95% CI, 35.2% - 37.5%; p = 1 x 10-38]. Enhancements to the CDS design and logic during the subsequent iteration's study period, June 2022 and December 2023, reduced the number of CDS triggers by more than 30-fold while simultaneously driving an additional increase in naloxone receipt to 42.7% [95% CI, 40.6% - 44.8%; p = 2 x 10-5]. The efficiency of the CDS demonstrated marked improvement, with prescribers accepting the naloxone co-prescription recommendation provided by the CDS in 41.1% of the encounters in version two, compared to 6.2% in version one (p = 6 x 10-9). Conclusion This study offers a sustainable and scalable model to address low rates of naloxone co-prescription and may also be used to target other opportunities for improving guideline-concordant prescribing practices.

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迭代开发临床决策支持工具,加强纳洛酮共同处方。
背景 在美国,阿片类药物过量是导致死亡的重要原因。尽管美国疾病控制和预防中心长期以来一直建议接受阿片类药物治疗的高危患者共同使用纳洛酮,但这些指南的依从性仍然很低。目的 本研究旨在开发和评估一种基于全院电子健康记录(EHR)的临床决策支持(CDS)工具,旨在促进纳洛酮对高风险阿片类药物的联合处方。方法 我们采用了一种迭代方法来开发一种订单点、中断式电子病历警报作为主要干预措施,并对纳洛酮处方率、电子病历效率指标和采用障碍进行了评估。数据来自我们 EHR 的临床数据仓库,并使用统计过程控制和卡方分析法进行分析,以评估干预期间处方率在统计学上的显著差异。结果 从 2019 年 4 月到 2022 年 5 月的干预初始实施阶段,接受纳洛酮治疗的高危患者比例增加了近 3 倍,从 13.4% [95% CI, 12.9% - 13.8%] 增加到 36.4% [95% CI, 35.2% - 37.5%; p = 1 x 10-38]。在随后的迭代研究期间(2022 年 6 月至 2023 年 12 月),对 CDS 设计和逻辑进行了改进,使 CDS 触发次数减少了 30 多倍,同时使纳洛酮接收率增加到 42.7% [95% CI, 40.6% - 44.8%; p = 2 x 10-5]。CDS 的效率显著提高,在第二版 CDS 中,41.1% 的就诊处方接受了 CDS 提供的纳洛酮联合处方建议,而在第一版 CDS 中,这一比例仅为 6.2%(p = 6 x 10-9)。结论 本研究为解决纳洛酮联合处方率低的问题提供了一种可持续、可扩展的模式,也可用于针对其他机会改善与指南一致的处方实践。
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来源期刊
Applied Clinical Informatics
Applied Clinical Informatics MEDICAL INFORMATICS-
CiteScore
4.60
自引率
24.10%
发文量
132
期刊介绍: ACI is the third Schattauer journal dealing with biomedical and health informatics. It perfectly complements our other journals Öffnet internen Link im aktuellen FensterMethods of Information in Medicine and the Öffnet internen Link im aktuellen FensterYearbook of Medical Informatics. The Yearbook of Medical Informatics being the “Milestone” or state-of-the-art journal and Methods of Information in Medicine being the “Science and Research” journal of IMIA, ACI intends to be the “Practical” journal of IMIA.
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