Using Clinical Simulations to Inform Process Improvement Interventions
Assistant Professor of Industrial Engineering
University of Massachusetts Amherst
Healthcare professionals must be accurate and efficient in their provision of care. The goal of this talk is to demonstrate how a novel approach - clinical simulation, observation, and eye tracking technology - can be used to specify how individuals complete health care processes, thereby informing process improvement interventions.
To assess health care professionals' levels of accuracy and efficiency, we engaged them (N=61) in realistic clinical scenarios to understand the processes by which they verify a patient's identity (ID). Emergency service associates (ESAs) placed an ID band on a patient, technical associates (TAs) drew and labeled a patient's blood specimen, and registered nurses (RNs) administered an intravenous medication to a patient. Participants needed to verify the patient's ID as a part of the task, and one of the three simulations contained an ID error. Participants wore an eye tracking device and were observed by an individual who recorded their specific actions.
We categorized participants based on whether they caught the ID error (proxy for accuracy) and by the number of steps they took to complete the process (proxy for efficiency). Each role-type varied in its accuracy-efficiency level. This finding suggests that each role-type requires a different set of process improvement interventions. We detail how process improvement interventions can be targeted at specific role-types, and sub-groups within each role-type, based on the ability of the intervention to improve accuracy and/or efficiency. We posit that this approach will lead to more cost-effective process improvement interventions.