临床决策支持增加急诊科纳洛酮处方:实施报告。

IF 3.1 3区 医学 Q2 MEDICAL INFORMATICS
Stuart W Sommers, Heather J Tolle, Katy E Trinkley, Christine G Johnston, Caitlin L Dietsche, Stephanie V Eldred, Abraham T Wick, Jason A Hoppe
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引用次数: 0

摘要

背景:纳洛酮与阿片类镇痛药同时处方是美国疾病控制与预防中心(CDC)降低阿片类药物过量致死风险的最佳做法,但急诊科临床医生很少同时处方纳洛酮,只有不到5%的情况下需要同时处方纳洛酮。临床决策支持(CDS)与纳洛酮处方的增加有关;然而,了解可复制性和有效性所必需的临床决策支持的关键设计特征和实用结果测量方法尚未见报道:本研究旨在严格评估和量化旨在改善急诊科(ED)纳洛酮共同处方的 CDS 的影响。我们假设,在一个大型医疗保健系统中,CDS 将增加纳洛酮的共同处方量以及急诊科出院病人的纳洛酮处方数量:按照以用户为中心的设计原则,我们设计并实施了一种基于电子健康记录的全自动、中断式 CDS,以促使临床医生在开具高风险阿片类药物处方时同时开具纳洛酮处方。"高风险 "阿片类药物处方的定义是:任何阿片类镇痛药处方的总吗啡毫克当量每天≥90 毫克,或处方中的患者曾被诊断为阿片类药物使用障碍或阿片类药物过量。我们采用了 "普及、有效性、采用、实施和维持"(RE-AIM)框架来评估 CDS 在普及、有效性、采用、实施和维持方面的实际效果。有效性是主要的评估结果,其评估方法是:(1)构建一个贝叶斯结构时间序列模型,计算实施 CDS 前后使用纳洛酮处方的急诊就诊次数;(2)计算与 CDS 相关的纳洛酮处方中在门诊药房配药的百分比。Mann-Kendall 检验用于评估采用 CDS 的纵向趋势。所有结果均使用 R(4.2.2 版;R 核心团队)进行分析:2019年11月至2023年7月期间,共有1,994,994次急诊就诊。在所有就诊者中,有 0.83% (16,566/1,994,994)的临床医生采用了 CDS;在出院时开具阿片类药物处方的 ED 就诊者中,有 15.99% (16,566/103,606)的临床医生采用了 CDS。临床医生采用了 CDS,在 34.36% (6613/19246)的警报中共同处方了纳洛酮。CDS 效果显著,纳洛酮处方量比基线每周增加了 18.1(95% CI 17.9-18.3)份,即增加了 2327%(95% CI 3390-3490)。患者开出的纳洛酮处方占 43.80%(1989/4541)。CDS 在每个急诊室同时实施,实施后未对 CDS 进行调整。电子病历系统在研究期结束后继续使用并保持其效果,采用率随时间推移而增加(τ=0.454;PC结论:我们的研究结果进一步证明,基于电子健康记录的 CDS 增加了纳洛酮处方的数量,并改善了纳洛酮的分布。我们的时间序列分析对世俗趋势进行了控制,有力地证明了最小中断性 CDS 显著改善了过程结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Clinical Decision Support to Increase Emergency Department Naloxone Coprescribing: Implementation Report.

Background: Coprescribing naloxone with opioid analgesics is a Centers for Disease Control and Prevention (CDC) best practice to mitigate the risk of fatal opioid overdose, yet coprescription by emergency medicine clinicians is rare, occurring less than 5% of the time it is indicated. Clinical decision support (CDS) has been associated with increased naloxone prescribing; however, key CDS design characteristics and pragmatic outcome measures necessary to understand replicability and effectiveness have not been reported.

Objective: This study aimed to rigorously evaluate and quantify the impact of CDS designed to improve emergency department (ED) naloxone coprescribing. We hypothesized CDS would increase naloxone coprescribing and the number of naloxone prescriptions filled by patients discharged from EDs in a large health care system.

Methods: Following user-centered design principles, we designed and implemented a fully automated, interruptive, electronic health record-based CDS to nudge clinicians to coprescribe naloxone with high-risk opioid prescriptions. "High-risk" opioid prescriptions were defined as any opioid analgesic prescription ≥90 total morphine milligram equivalents per day or for patients with a prior diagnosis of opioid use disorder or opioid overdose. The Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework was used to evaluate pragmatic CDS outcomes of reach, effectiveness, adoption, implementation, and maintenance. Effectiveness was the primary outcome of interest and was assessed by (1) constructing a Bayesian structural time-series model of the number of ED visits with naloxone coprescriptions before and after CDS implementation and (2) calculating the percentage of naloxone prescriptions associated with CDS that were filled at an outpatient pharmacy. Mann-Kendall tests were used to evaluate longitudinal trends in CDS adoption. All outcomes were analyzed in R (version 4.2.2; R Core Team).

Unlabelled: Between November 2019 and July 2023, there were 1,994,994 ED visits. CDS reached clinicians in 0.83% (16,566/1,994,994) of all visits and 15.99% (16,566/103,606) of ED visits where an opioid was prescribed at discharge. Clinicians adopted CDS, coprescribing naloxone in 34.36% (6613/19,246) of alerts. CDS was effective, increasing naloxone coprescribing from baseline by 18.1 (95% CI 17.9-18.3) coprescriptions per week or 2,327% (95% CI 3390-3490). Patients filled 43.80% (1989/4541) of naloxone coprescriptions. The CDS was implemented simultaneously at every ED and no adaptations were made to CDS postimplementation. CDS was maintained beyond the study period and maintained its effect, with adoption increasing over time (τ=0.454; P<.001).

Conclusions: Our findings advance the evidence that electronic health record-based CDS increases the number of naloxone coprescriptions and improves the distribution of naloxone. Our time series analysis controls for secular trends and strongly suggests that minimally interruptive CDS significantly improves process outcomes.

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来源期刊
JMIR Medical Informatics
JMIR Medical Informatics Medicine-Health Informatics
CiteScore
7.90
自引率
3.10%
发文量
173
审稿时长
12 weeks
期刊介绍: JMIR Medical Informatics (JMI, ISSN 2291-9694) is a top-rated, tier A journal which focuses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals. Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2016: 5.175), JMIR Med Inform has a slightly different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.
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