Experience modeling and analyzing medical processes: UMass/baystate medical safety project overview

  • Authors:

  • George S. Avrunin;Lori A. Clarke;Leon J. Osterweil;Stefan C. Christov;Bin Chen;Elizabeth A. Henneman;Philip L. Henneman;Lucinda Cassells;Wilson Mertens

  • Affiliations:

  • University of Massachusetts, Amherst, MA, USA;University of Massachusetts, Amherst, MA, USA;University of Massachusetts, Amherst, MA, USA;University of Massachusetts, Amherst, MA, USA;University of Massachusetts, Amherst, MA, USA;University of Massachusetts, Amherst, MA, USA;Tufts-Baystate Medical Center, Springfield, MA, USA;Baystate Medical Center/Tufts University School of Medicine, Springfield, MA, USA;Baystate Medical Center/Tufts University School of Medicine, Springfield, MA, USA

  • Venue:
  • Proceedings of the 1st ACM International Health Informatics Symposium
  • Year:
  • 2010

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Abstract

This paper provides an overview of the UMass/Baystate Medical Safety project, which has been developing and evaluating tools and technology for modeling and analyzing medical processes. We describe the tools that currently comprise the Process Improvement Environment, PIE. For each tool, we illustrate the kinds of information that it provides and discuss how that information can be used to improve the modeled process as well as provide useful information that other tools in the environment can leverage. Because the process modeling notation that we use has rigorously defined semantics and supports creating relatively detailed process models (for example, our models can specify alternative ways of dealing with exceptional behavior and concurrency), a number of powerful analysis techniques can be applied. The cost of eliciting and maintaining such a detailed model is amortized over the range of analyses that can be applied to detect errors, vulnerabilities, and inefficiencies in an existing process or in proposed process modifications before they are deployed.