An increasing number of diagnostic decision support systems (DDSS) exist to support patients and physicians in establishing the correct diagnosis as early as possible. However, little evidence exists that supports the effectiveness of these DDSS. The objectives were to compare the diagnostic accuracy of medical students, with and without the use of a DDSS, and the diagnostic accuracy of the DDSS system itself, regarding the typical rheumatic diseases and to analyze the user experience. A total of 102 medical students were openly recruited from a university hospital and randomized (unblinded) to a control group (CG) and an intervention group (IG) that used a DDSS (Ada – Your Health Guide) to create an ordered diagnostic hypotheses list for three rheumatic case vignettes. Diagnostic accuracy, measured as the presence of the correct diagnosis first or at all on the hypothesis list, was the main outcome measure and evaluated for CG, IG, and DDSS. The correct diagnosis was ranked first (or was present at all) in CG, IG, and DDSS in 37% (40%), 47% (55%), and 29% (43%) for the first case; 87% (94%), 84% (100%), and 51% (98%) in the second case; and 35% (59%), 20% (51%), and 4% (51%) in the third case, respectively. No significant benefit of using the DDDS could be observed. In a substantial number of situations, the mean probabilities reported by the DDSS for incorrect diagnoses were actually higher than for correct diagnoses, and students accepted false DDSS diagnostic suggestions. DDSS symptom entry greatly varied and was often incomplete or false. No significant correlation between the number of symptoms extracted and diagnostic accuracy was seen. It took on average 7 min longer to solve a case using the DDSS. In IG, 61% of students compared to 90% in CG stated that they could imagine using the DDSS in their future clinical work life. The diagnostic accuracy of medical students was superior to the DDSS, and its usage did not significantly improve students’ diagnostic accuracy. DDSS usage was time-consuming and may be misleading due to prompting wrong diagnoses and probabilities. DRKS.de, DRKS00024433 . Retrospectively registered on February 5, 2021.

中文翻译：

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诊断决策支持系统在三种代表性风湿病诊断中的准确性和可用性：医学生随机对照试验


越来越多的诊断决策支持系统 (DDSS) 可以支持患者和医生尽早做出正确的诊断。然而，几乎没有证据支持这些 DDSS 的有效性。目的是比较医学生在使用和不使用 DDSS 的情况下对典型风湿性疾病的诊断准确性以及 DDSS 系统本身的诊断准确性，并分析用户体验。从一所大学医院公开招募 102 名医学生，并随机（非盲法）分为对照组 (CG) 和干预组 (IG)，使用 DDSS（Ada – 您的健康指南）创建有序的诊断假设列表三个风湿病病例小插曲。诊断准确性是主要的结果指标，以 CG、IG 和 DDSS 的主要结果衡量标准来衡量，即首先或根本上是否存在正确的诊断。第一个病例的正确诊断率在 CG、IG 和 DDSS 中排名第一（或根本存在），分别为 37% (40%)、47% (55%) 和 29% (43%)；第二种情况为 87% (94%)、84% (100%) 和 51% (98%)；第三种情况分别为 35% (59%)、20% (51%) 和 4% (51%)。没有观察到使用 DDDS 的显着好处。在很多情况下，DDSS 报告的错误诊断的平均概率实际上高于正确诊断的平均概率，并且学生接受了错误的 DDSS 诊断建议。 DDSS 症状条目差异很大，而且常常不完整或错误。提取的症状数量和诊断准确性之间没有显着相关性。使用 DDSS 解决案件平均需要多花 7 分钟。 在 IG 中，61% 的学生表示他们可以想象在未来的临床工作生活中使用 DDSS，而 CG 中的这一比例为 90%。医学生的诊断准确性优于DDSS，并且其使用并没有显着提高学生的诊断准确性。 DDSS 的使用非常耗时，并且可能会由于提示错误的诊断和概率而产生误导。 DRKS.de，DRKS00024433。追溯注册日期为2021年2月5日。