Virtual Patient Simulation

Medical diagnosis has begun to draw attention as a patient safety concern that is valid, yet difficult to study. In the current study, we implement a virtual patient simulation to assess different information sampling techniques practiced by a variety of health care providers including physicians, nurses, health technicians, and pharmacists who were tasked with diagnosing a virtual patient. Results suggest there are three different information sampling approaches used to arrive at a medical diagnosis: iteration, batch, and haste. In the iterative approach, clinicians sampled a series of hypothesis-generating sources of information (e.g., patient history, physical exam, etc.) that were immediately followed by a series of diagnostic tests (e.g., X-ray, EKG, etc.) and this process was repeated for 2-4 cycles before arriving at a diagnosis. In the batch approach, hypothesis-generating sources of information were sampled in a single series or “batch” that was then followed by a single series of diagnostic tests. In the haste approach, only a few sources of hypothesis-generating information were sampled before arriving at a medical diagnosis, and none of the information sampled was tested using diagnostic tests. Results suggest virtual patient simulation is a useful format to observe the emergence of clinicians’ diagnostic process and to collect a variety of measures and outcomes associated with medical diagnosis.