Using process modeling and analysis techniques to reduce errors in healthcare

Summary form only given. As has been widely reported in the news lately, healthcare errors are a major cause of death and suffering. In the University of Massachusetts Medical Safety Project, we are exploring the use of process modeling and analysis technologies to help reduce medical errors and improve efficiency. Specifically, we are modeling healthcare processes using a process definition language and then analyzing these processes using model checking, fault-tree analysis, discrete event simulation, and other techniques. Working with the UMASS School of Nursing and the Baystate Medical Center, we are undertaking in-depth case studies on error-prone and life-critical healthcare processes. In many ways, these processes are similar to complex, distributed systems with many interacting, concurrent threads and numerous exceptional conditions that must be handled carefully. This talk describes the technologies we are using, discusses case studies, and presents our observations and findings to date. Although presented in terms of the healthcare domain, the described approach could be applied to human-intensive processes in other domains to provide a technology-driven approach to process improvement.