Suppr超能文献

计算机化临床决策支持系统在肺血栓栓塞症诊断中的应用:一项临床前试点研究。

Computerised clinical decision support system for the diagnosis of pulmonary thromboembolism: a preclinical pilot study.

机构信息

Department of Medicine, University of Calgary Cumming School of Medicine, Calgary, Alberta, Canada

Computer Sciences, University of Calgary, Calgary, Alberta, Canada.

出版信息

BMJ Open Qual. 2023 Mar;12(1). doi: 10.1136/bmjoq-2022-001984.

Abstract

BACKGROUND

Recommendations for the diagnosis of pulmonary embolism are available for healthcare providers. Yet, real practice data show existing gaps in the translation of evidence-based recommendations. This is a study to assess the effect of a computerised decision support system (CDSS) with an enhanced design based on best practices in content and reasoning representation for the diagnosis of pulmonary embolism.

DESIGN

Randomised preclinical pilot study of paper-based clinical scenarios in the diagnosis of pulmonary embolism. Participants were clinicians (n=30) from three levels of experience: medical students, residents and physicians. Participants were randomised to two interventions for the diagnosis of pulmonary embolism: a didactic lecture versus a decision tree via a CDSS. The primary outcome of diagnostic pathway concordance (derived as a ratio of the number of correct diagnostic decision steps divided by the ideal number of diagnostic decision steps in diagnostic algorithms) was measured at baseline (five clinical scenarios) and after either intervention for a total of 10 clinical scenarios.

RESULTS

The mean of diagnostic pathway concordance improved in both study groups: baseline mean=0.73, post mean for the CDSS group=0.90 (p<0.001, 95% CI 0.10-0.24); baseline mean=0.71, post mean for didactic lecture group=0.85 (p<0.001, 95% CI 0.07-0.2). There was no statistically significant difference between the two study groups or between the three levels of participants.

INTERPRETATION

A computerised decision support system designed for both content and reasoning visualisation can improve clinicians' diagnostic decision-making.

摘要

背景

已有针对医疗保健提供者的肺栓塞诊断建议。然而,实际实践数据显示,证据为基础的推荐意见的转化存在差距。本研究旨在评估一种基于最佳内容和推理表示实践的计算机化决策支持系统(CDSS)在肺栓塞诊断中的应用效果。

设计

基于纸质临床情景的肺栓塞诊断的随机临床前试点研究。参与者为来自三个经验水平的临床医生(n=30):医学生、住院医师和医生。参与者被随机分为两种肺栓塞诊断干预措施:基于 CDSS 的决策树与讲座。诊断途径一致性(通过将正确诊断决策步骤的数量除以诊断算法中的理想诊断决策步骤数量得出的比值)是本研究的主要结局指标,在基线(5 个临床情景)和两种干预措施后(共 10 个临床情景)进行测量。

结果

两组研究对象的诊断途径一致性均有所提高:基线平均为 0.73,CDSS 组的术后平均为 0.90(p<0.001,95%CI 0.10-0.24);基线平均为 0.71,讲座组的术后平均为 0.85(p<0.001,95%CI 0.07-0.2)。两组研究对象之间或三个参与者水平之间均无统计学差异。

结论

一种为内容和推理可视化而设计的计算机化决策支持系统可提高临床医生的诊断决策能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e201/10030901/3428d6aab062/bmjoq-2022-001984f01.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验