We studied if clinicians could gain sufficient working knowledge of a computer-assisted diagnostic decision support system (DDSS) (SimulConsult), to make differential diagnoses (DDx) of genetic disorders. We hypothesized that virtual training could be convenient, asynchronous, and effective in teaching clinicians how to use a DDSS. We determined the efficacy of virtual, asynchronous teaching for clinicians to gain working knowledge to make computer-assisted DDx. Our study consisted of three surveys (Baseline, Training, and After Use) and a series of case problems sent to clinicians at Vanderbilt University Medical Center. All participants were able to generate computer-assisted DDx that achieved passing scores of the case problems. Between 75% and 92% agreed/completely agreed the DDSS was useful to their work and for clinical decision support and was easy to use. Participants' use of the DDSS resulted in statistically significant time savings in key tasks and in total time spent on clinical tasks. Our results indicate that virtual, asynchronous teaching can be an effective format to gain a working knowledge of a DDSS, and its clinical use could result in significant time savings across multiple tasks as well as facilitate synergistic interaction between clinicians and lab specialists. This approach is especially pertinent and offers value amid the COVID-19 pandemic.
Keywords: clinical decision support; education; genetics education; machine learning; teaching; virtual.
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