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

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.