Studying Rigorously Defined Health Care Processes Using a Formal Process Modeling Language, Clinical Simulation, Observation, and Eye Tracking

摘要

Motivation - The complex nature of health care processes requires new methods for describing, capturing and improving these processes. Research approach - We deployed a novel combination of methods - formal process modeling using a language called Little-JIL, simulations with embedded errors, observations, and eye tracking technology - to gauge how health care providers complete one complex process, patient identification. Findings/Design - These methods allowed us to thoroughly analyze how health care providers completed the patient identification process with and without embedded errors, and to record exactly what participants looked at during the simulations. Research limitations/Implications - We have used this set of methods to analyze only one type of health care process to-date. Originality/Value - We can use these approaches to inform health care provider training, process redesign, and the design of technologies to support health care providers as they verify patients' identities.