Kostopoulou Olga, Porat Talya, Corrigan Derek, Mahmoud Samhar, Delaney Brendan C
Department of Surgery and Cancer, Imperial College London, London.
Department of Primary Care and Public Health Sciences, King's College London, London.
Br J Gen Pract. 2017 Mar;67(656):e201-e208. doi: 10.3399/bjgp16X688417. Epub 2017 Jan 30.
Observational and experimental studies of the diagnostic task have demonstrated the importance of the first hypotheses that come to mind for accurate diagnosis. A prototype decision support system (DSS) designed to support GPs' first impressions has been integrated with a commercial electronic health record (EHR) system.
To evaluate the prototype DSS in a high-fidelity simulation.
Within-participant design: 34 GPs consulted with six standardised patients (actors) using their usual EHR. On a different day, GPs used the EHR with the integrated DSS to consult with six other patients, matched for difficulty and counterbalanced.
Entering the reason for encounter triggered the DSS, which provided a patient-specific list of potential diagnoses, and supported coding of symptoms during the consultation. At each consultation, GPs recorded their diagnosis and management. At the end, they completed a usability questionnaire. The actors completed a satisfaction questionnaire after each consultation.
There was an 8-9% absolute improvement in diagnostic accuracy when the DSS was used. This improvement was significant (odds ratio [OR] 1.41, 95% confidence interval [CI] = 1.13 to 1.77, <0.01). There was no associated increase of investigations ordered or consultation length. GPs coded significantly more data when using the DSS (mean 12.35 with the DSS versus 1.64 without), and were generally satisfied with its usability. Patient satisfaction ratings were the same for consultations with and without the DSS.
The DSS prototype was successfully employed in simulated consultations of high fidelity, with no measurable influences on patient satisfaction. The substantially increased data coding can operate as motivation for future DSS adoption.
对诊断任务的观察性和实验性研究表明，最初想到的假设对于准确诊断至关重要。一个旨在支持全科医生第一印象的原型决策支持系统（DSS）已与商业电子健康记录（EHR）系统集成。
在高保真模拟中评估该原型DSS。
参与者内设计：34名全科医生使用他们常用的EHR与6名标准化患者（演员）进行会诊。在不同的一天，全科医生使用集成了DSS的EHR与另外6名患者进行会诊，这些患者在难度上匹配且经过了平衡处理。
输入会诊原因会触发DSS，它会提供一份针对患者的潜在诊断列表，并在会诊期间支持对症状进行编码。每次会诊时，全科医生记录他们的诊断和管理措施。最后，他们完成一份可用性问卷。演员在每次会诊后完成一份满意度问卷。
使用DSS时，诊断准确性有8 - 9%的绝对提高。这种提高具有统计学意义（优势比[OR]为1.41，95%置信区间[CI] = 1.13至1.77，P<0.01）。所开具的检查或会诊时长没有相应增加。使用DSS时，全科医生编码的数据显著更多（使用DSS时平均为12.35，不使用时为1.64），并且总体上对其可用性感到满意。使用和不使用DSS的会诊中患者满意度评分相同。
DSS原型在高保真模拟会诊中成功应用，对患者满意度没有可测量的影响。大幅增加的数据编码可成为未来采用DSS的动力。
