Medical error management and the role of information technology--a new approach to investigating medical handover in acute care settings.
While identifying reasons why medical errors occur and constructing models of how to manage them has proved relatively straightforward, implementing and meaningfully evaluating solutions in 'real-world' settings has proven considerably more difficult. From an information systems (IS) perspective, although the promise of technology remains powerful, the continuing high incidence of medical errors suggest that eHealth approaches are struggling to acquire a clear understanding of the complex, dynamic and multi-layered nature of acute care settings and clinical practices, and to respond effectively to address the range of errors that actually occur. Using medical handover as a field-site, this research-in-progress paper presents an adaptation of James Reason's 'Swiss Cheese Model' to conceptualize the complex factors at play in medical errors in terms of human, system and informational elements. This research paper then examines how drawing on this model it is possible to generate and implement a methodological approach that both enhances a holistic understanding of medical error management and illuminates criteria that can be used to meaningfully identify an appropriate role for information technology in medical error mitigation. This research-in-progress paper aims to make a significant contribution to research into medical error management in 'real-world' acute care settings. This research is part of a bigger project that aims to develop, implement and evaluate an information technology artefact as part of an holistic information systems approach to improving medical error management at medical handover.
Yee
Kwang Chien
KC
Royal Hobart Hospital, Tasmania, Australia.
Wong
Ming Chao
MC
Turner
Paul
P
D003266:Continuity of Patient Care / Q000458:organization & administration*; D003422:Critical Care; D006302:Health Services Research; D006751:Hospital Information Systems; D006801:Humans; D019300:Medical Errors / Q000517:prevention & control*; D008962:Models, Theoretical; D013648:Tasmania