Department of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Center for Innovations in Quality, Effectiveness and Safety (IQuESt), Michael E DeBakey VA Medical Center, Houston, Texas, USA.
BMJ Open. 2023 Mar 29;13(3):e072649. doi: 10.1136/bmjopen-2023-072649.
Computerised diagnostic decision support systems (CDDS) suggesting differential diagnoses to physicians aim to improve clinical reasoning and diagnostic quality. However, controlled clinical trials investigating their effectiveness and safety are absent and the consequences of its use in clinical practice are unknown. We aim to investigate the effect of CDDS use in the emergency department (ED) on diagnostic quality, workflow, resource consumption and patient outcomes.
This is a multicentre, outcome assessor and patient-blinded, cluster-randomised, multiperiod crossover superiority trial. A validated differential diagnosis generator will be implemented in four EDs and randomly allocated to a sequence of six alternating intervention and control periods. During intervention periods, the treating ED physician will be asked to consult the CDDS at least once during diagnostic workup. During control periods, physicians will not have access to the CDDS and diagnostic workup will follow usual clinical care. Key inclusion criteria will be patients' presentation to the ED with either fever, abdominal pain, syncope or a non-specific complaint as chief complaint. The primary outcome is a binary diagnostic quality risk score composed of presence of an unscheduled medical care after discharge, change in diagnosis or death during time of follow-up or an unexpected upscale in care within 24 hours after hospital admission. Time of follow-up is 14 days. At least 1184 patients will be included. Secondary outcomes include length of hospital stay, diagnostics and data regarding CDDS usage, physicians' confidence calibration and diagnostic workflow. Statistical analysis will use general linear mixed modelling methods.
Approved by the cantonal ethics committee of canton Berne (2022-D0002) and Swissmedic, the Swiss national regulatory authority on medical devices. Study results will be disseminated through peer-reviewed journals, open repositories and the network of investigators and the expert and patients advisory board.
NCT05346523.
向医生建议鉴别诊断的计算机化诊断决策支持系统（CDDS）旨在改善临床推理和诊断质量。然而，目前缺乏关于其有效性和安全性的对照临床试验，其在临床实践中的使用后果尚不清楚。我们旨在研究急诊科（ED）使用 CDDS 对诊断质量、工作流程、资源消耗和患者结局的影响。
这是一项多中心、结局评估者和患者盲法、集群随机、多周期交叉优效性试验。将验证后的鉴别诊断生成器应用于四个 ED，并随机分配到六个交替干预和对照期的序列中。在干预期间，将要求治疗 ED 医生在诊断工作中至少咨询一次 CDDS。在对照期间，医生将无法访问 CDDS，诊断工作将遵循常规临床护理。主要纳入标准为患者因发热、腹痛、晕厥或非特异性主诉就诊 ED。主要结局是一个二进制诊断质量风险评分，由出院后接受非计划性医疗护理、诊断改变或随访期间死亡或入院后 24 小时内护理意外升级的情况组成。随访时间为 14 天。至少纳入 1184 例患者。次要结局包括住院时间、诊断和与 CDDS 使用相关的数据、医生的信心校准和诊断工作流程。统计分析将使用广义线性混合模型方法。
该研究已获得伯尔尼州伦理委员会（2022-D0002）和瑞士国家医疗器械监管机构 Swissmedic 的批准。研究结果将通过同行评议期刊、开放知识库以及调查人员网络和专家及患者咨询委员会进行传播。
NCT05346523。
