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算法和人工智能应用于改善初级保健药物管理的潜力:系统评价。

Potentiality of algorithms and artificial intelligence adoption to improve medication management in primary care: a systematic review.

机构信息

Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy.

Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Roma, Italy.

出版信息

BMJ Open. 2023 Mar 23;13(3):e065301. doi: 10.1136/bmjopen-2022-065301.

Abstract

OBJECTIVES

The aim of this study is to investigate the effect of artificial intelligence (AI) and/or algorithms on drug management in primary care settings comparing AI and/or algorithms with standard clinical practice. Second, we evaluated what is the most frequently reported type of medication error and the most used AI machine type.

METHODS

A systematic review of literature was conducted querying PubMed, Cochrane and ISI Web of Science until November 2021. The search strategy and the study selection were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and the Population, Intervention, Comparator, Outcome framework. Specifically, the Population chosen was general population of all ages (ie, including paediatric patients) in primary care settings (ie, home setting, ambulatory and nursery homes); the Intervention considered was the analysis AI and/or algorithms (ie, intelligent programs or software) application in primary care for reducing medications errors, the Comparator was the general practice and, lastly, the Outcome was the reduction of preventable medication errors (eg, overprescribing, inappropriate medication, drug interaction, risk of injury, dosing errors or in an increase in adherence to therapy). The methodological quality of included studies was appraised adopting the Quality Assessment of Controlled Intervention Studies of the National Institute of Health for randomised controlled trials.

RESULTS

Studies reported in different ways the effective reduction of medication error. Ten out of 14 included studies, corresponding to 71% of articles, reported a reduction of medication errors, supporting the hypothesis that AI is an important tool for patient safety.

CONCLUSION

This study highlights how a proper application of AI in primary care is possible, since it provides an important tool to support the physician with drug management in non-hospital environments.

摘要

目的

本研究旨在探讨人工智能(AI)和/或算法在初级保健环境中的药物管理效果,将 AI 和/或算法与标准临床实践进行比较。其次,我们评估了最常报告的药物错误类型和最常用的 AI 机器类型。

方法

对PubMed、Cochrane 和 ISI Web of Science 进行了系统的文献检索,检索时间截至 2021 年 11 月。根据系统评价和荟萃分析的首选报告项目以及人群、干预、比较、结果框架进行了搜索策略和研究选择。具体来说,选择的人群是初级保健环境(即家庭环境、门诊和养老院)中所有年龄段的一般人群(即包括儿科患者);干预措施是分析 AI 和/或算法(即智能程序或软件)在初级保健中应用以减少药物错误,比较组是一般实践,最后,结果是减少可预防的药物错误(例如,过度处方、用药不当、药物相互作用、受伤风险、剂量错误或增加对治疗的依从性)。采用美国国立卫生研究院的对照干预研究质量评估方法评估纳入研究的方法学质量。

结果

有 10 项研究(占纳入文章的 71%)以不同的方式报告了药物错误有效减少的结果,支持了 AI 是患者安全的重要工具这一假设。

结论

这项研究强调了在初级保健中正确应用 AI 的可能性,因为它为医生在非医院环境中进行药物管理提供了重要工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ded/10040015/14e9ba7c14dc/bmjopen-2022-065301f01.jpg

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