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如何开发并实施一个整合了抗菌药物管理的计算机化决策支持系统?来自两个瑞士医院系统的经验。

How to Develop and Implement a Computerized Decision Support System Integrated for Antimicrobial Stewardship? Experiences From Two Swiss Hospital Systems.

作者信息

Catho Gaud, Centemero Nicolo S, Waldispühl Suter Brigitte, Vernaz Nathalie, Portela Javier, Da Silva Serge, Valotti Roberta, Coray Valentina, Pagnamenta Francesco, Ranzani Alice, Piuz Marie-Françoise, Elzi Luigia, Meyer Rodolphe, Bernasconi Enos, Huttner Benedikt D

机构信息

Division of Infectious Diseases, Geneva University Hospital, Geneva, Switzerland.

Faculty of Medicine, University of Geneva, Geneva, Switzerland.

出版信息

Front Digit Health. 2021 Feb 16;2:583390. doi: 10.3389/fdgth.2020.583390. eCollection 2020.


DOI:10.3389/fdgth.2020.583390
PMID:34713055
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8521958/
Abstract

Computerized decision support systems (CDSS) provide new opportunities for automating antimicrobial stewardship (AMS) interventions and integrating them in routine healthcare. CDSS are recommended as part of AMS programs by international guidelines but few have been implemented so far. In the context of the publicly funded COMPuterized Antibiotic Stewardship Study (COMPASS), we developed and implemented two CDSSs for antimicrobial prescriptions integrated into the in-house electronic health records of two public hospitals in Switzerland. Developing and implementing such systems was a unique opportunity for learning during which we faced several challenges. In this narrative review we describe key lessons learned. (1) During the initial planning and development stage, start by drafting the CDSS as an algorithm and use a standardized format to communicate clearly the desired functionalities of the tool to all stakeholders. (2) Set up a multidisciplinary team bringing together Information Technologies (IT) specialists with development expertise, clinicians familiar with "real-life" processes in the wards and if possible, involve collaborators having knowledge in both areas. (3) When designing the CDSS, make the underlying decision-making process transparent for physicians and start simple and make sure to find the right balance between force and persuasion to ensure adoption by end-users. (4) Correctly assess the clinical and economic impact of your tool, therefore try to use standardized terminologies and limit the use of free text for analysis purpose. (5) At the implementation stage, plan usability testing early, develop an appropriate training plan suitable to end users' skills and time-constraints and think ahead of additional challenges related to the study design that may occur (such as a cluster randomized trial). Stay also tuned to react quickly during the intervention phase. (6) Finally, during the assessment stage plan ahead maintenance, adaptation and related financial challenges and stay connected with institutional partners to leverage potential synergies with other informatics projects.

摘要

计算机化决策支持系统(CDSS)为抗菌药物管理(AMS)干预措施的自动化及其融入常规医疗保健提供了新机遇。国际指南推荐将CDSS作为AMS项目的一部分,但迄今为止很少有系统得到实施。在公共资助的计算机化抗生素管理研究(COMPASS)背景下,我们开发并实施了两个用于抗菌药物处方的CDSS,并将其集成到瑞士两家公立医院的内部电子健康记录中。开发和实施此类系统是一个独特的学习机会,在此过程中我们面临了诸多挑战。在这篇叙述性综述中,我们描述了汲取的关键经验教训。(1)在初始规划和开发阶段,首先将CDSS起草为一种算法,并使用标准化格式向所有利益相关者清晰传达该工具所需的功能。(2)组建一个多学科团队,汇聚具有开发专业知识的信息技术(IT)专家、熟悉病房“实际”流程的临床医生,如有可能,让具备这两个领域知识的合作者参与进来。(3)在设计CDSS时,使基础决策过程对医生透明,从简单做起,并确保在强制与劝说之间找到正确平衡,以确保最终用户采用。(4)正确评估工具的临床和经济影响,因此尽量使用标准化术语,并限制为分析目的使用自由文本。(5)在实施阶段,尽早计划可用性测试,制定适合最终用户技能和时间限制的适当培训计划,并提前考虑可能出现的与研究设计相关的其他挑战(如整群随机试验)。在干预阶段也要随时做好迅速反应的准备。(6)最后,在评估阶段提前规划维护、调整及相关财务挑战,并与机构合作伙伴保持联系,以利用与其他信息学项目的潜在协同效应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3999/8521958/23b611dcdb88/fdgth-02-583390-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3999/8521958/1c1b135e4dce/fdgth-02-583390-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3999/8521958/23b611dcdb88/fdgth-02-583390-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3999/8521958/1c1b135e4dce/fdgth-02-583390-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3999/8521958/23b611dcdb88/fdgth-02-583390-g0002.jpg

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[2]
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[3]
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[4]
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[5]
Impact of interactive computerised decision support for hospital antibiotic use (COMPASS): an open-label, cluster-randomised trial in three Swiss hospitals.

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[6]
Machine Learning and Antibiotic Management.

Antibiotics (Basel). 2022-2-24

本文引用的文献

[1]
Factors determining the adherence to antimicrobial guidelines and the adoption of computerised decision support systems by physicians: A qualitative study in three European hospitals.

Int J Med Inform. 2020-7-13

[2]
Evidence-Based Strategies in Using Persuasive Interventions to Optimize Antimicrobial Use in Healthcare: a Narrative Review.

J Med Syst. 2020-2-10

[3]
Live Usability Testing of Two Complex Clinical Decision Support Tools: Observational Study.

JMIR Hum Factors. 2019-4-15

[4]
Best practices for preventing malfunctions in rule-based clinical decision support alerts and reminders: Results of a Delphi study.

Int J Med Inform. 2018-8-2

[5]
Study protocol for a multicentre, cluster randomised, superiority trial evaluating the impact of computerised decision support, audit and feedback on antibiotic use: the COMPuterized Antibiotic Stewardship Study (COMPASS).

BMJ Open. 2018-6-27

[6]
Antimicrobial consumption and resistance in adult hospital inpatients in 53 countries: results of an internet-based global point prevalence survey.

Lancet Glob Health. 2018-4-23

[7]
Reasons For Physicians Not Adopting Clinical Decision Support Systems: Critical Analysis.

JMIR Med Inform. 2018-4-18

[8]
What is antimicrobial stewardship?

Clin Microbiol Infect. 2017-9-4

[9]
"Think aloud" and "Near live" usability testing of two complex clinical decision support tools.

Int J Med Inform. 2017-10

[10]
Optimization of infobutton design and Implementation: A systematic review.

J Biomed Inform. 2017-8-22

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