Wolf E. Hautz

When making complex decisions, such as a medical diagnosis, decision makers typically gather, analyze, and synthesize (integrate) information. In a previous study, we showed that delegating such complex decisions to collaborating pairs increases decision quality substantially compared to that of individuals, without requiring different information gathering. Given the higher costs associated with teamwork, however, it is of great practical interest to understand when in the process the performance benefits of teams may arise, so that particular subtasks can be delegated to teams when most appropriate. We thus conducted an experimental study in which fourth‐year medical students ( n = 109) worked either in pairs or alone on two separate subtasks of the diagnostic process: (1) analyzing diagnostic test results (e.g., X‐rays) and (2) integrating previously interpreted test results into diagnoses. Linear mixed‐effects models revealed a small benefit of collaborating pairs over individuals in both subtasks. We conclude that collaborating with a peer may pay off both when analyzing information and when integrating it into a diagnosis as it provides the opportunity to correct each other's errors and to make use of a greater knowledge base. These findings encourage the strategic use of collaboration with a colleague when making complex decisions. Further research into the underlying processes is needed.

Objectives Existing computerized diagnostic decision support tools (CDDS) accurately return possible differential diagnoses (DDx) based on the clinical information provided. The German versions of the CDDS tools for clinicians (Isabel Pro) and patients (Isabel Symptom Checker) from ISABEL Healthcare have not been validated yet. Methods We entered clinical features of 50 patient vignettes taken from an emergency medical text book and 50 real cases with a confirmed diagnosis derived from the electronic health record (EHR) of a large academic Swiss emergency room into the German versions of Isabel Pro and Isabel Symptom Checker. We analysed the proportion of DDx lists that included the correct diagnosis. Results Isabel Pro and Symptom Checker provided the correct diagnosis in 82 and 71 % of the cases, respectively. Overall, the correct diagnosis was ranked in 71 , 61 and 37 % of the cases within the top 20, 10 and 3 of the provided DDx when using Isabel Pro. In general, accuracy was higher with vignettes than ED cases, i.e. listed the correct diagnosis more often (non-significant) and ranked the diagnosis significantly more often within the top 20, 10 and 3. On average, 38 ± 4.5 DDx were provided by Isabel Pro and Symptom Checker. Conclusions The German versions of Isabel achieved a somewhat lower accuracy compared to previous studies of the English version. The accuracy decreases substantially when the position in the suggested DDx list is taken into account. Whether Isabel Pro is accurate enough to improve diagnostic quality in clinical ED routine needs further investigation.