Preventable Medical Errors Driven Modeling of Medical Best Practice Guidance Systems

Andrew Y.Z. Ou, Yu Jiang, Po Liang Wu, Lui Sha, Richard B. Berlin

Research output: Contribution to journalArticle

Abstract

In a medical environment such as Intensive Care Unit, there are many possible reasons to cause errors, and one important reason is the effect of human intellectual tasks. When designing an interactive healthcare system such as medical Cyber-Physical-Human Systems (CPHSystems), it is important to consider whether the system design can mitigate the errors caused by these tasks or not. In this paper, we first introduce five categories of generic intellectual tasks of humans, where tasks among each category may lead to potential medical errors. Then, we present an integrated modeling framework to model a medical CPHSystem and use UPPAAL as the foundation to integrate and verify the whole medical CPHSystem design models. With a verified and comprehensive model capturing the human intellectual tasks effects, we can design a more accurate and acceptable system. We use a cardiac arrest resuscitation guidance and navigation system (CAR-GNSystem) for such medical CPHSystem modeling. Experimental results show that the CPHSystem models help determine system design flaws and can mitigate the potential medical errors caused by the human intellectual tasks.

Original languageEnglish (US)
Article number9
JournalJournal of Medical Systems
Volume41
Issue number1
DOIs
StatePublished - Jan 1 2017

Keywords

  • Cardiac arrest resuscitation
  • Human intellectual tasks
  • Medical guidance systems

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Information Systems
  • Health Informatics
  • Health Information Management

Fingerprint Dive into the research topics of 'Preventable Medical Errors Driven Modeling of Medical Best Practice Guidance Systems'. Together they form a unique fingerprint.

  • Cite this