Literature DB >> 11340007

Modeling a medical environment: an ontology for integrated medical informatics design.

J R Hajdukiewicz1, K J Vicente, D J Doyle, P Milgram, C M Burns.   

Abstract

Modern medical environments have seen an increase in technological complexity and pressures of handling more patients with fewer resources, resulting in higher demands on medical practitioners. Medical informatics designers will have to focus on the problem of organizing medical information more effectively to enable practitioners to cope with these challenges. This article addresses this research problem for the particular area of medical problem solving in patient care. First, we describe a traditional modeling approach for medical reasoning used as a basis for developing some decision support systems. We argue these models may be faithful to what is known about biomedical knowledge, but they have limitations for human problem solving, especially in unanticipated situations. Second, we present an ontological framework, known as the abstraction hierarchy (Rasmussen, IEEE Trans. Man. Cybernetics 15 (1985) 234-243), for integrating patient representations that are faithful to existing biomedical knowledge and that are consistent with what is known about human problem solving. Through an example of a critical event in the operating room, we reveal how this framework can support medical problem solving in unanticipated situations. Third, we show how to use these representations as a frame of reference for mapping medical roles, responsibilities, sensors, and controls in an operating room context. Finally, we provide some insight for medical informatics designers in using this framework to design novel training programs and human-computer displays.

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Year:  2001        PMID: 11340007     DOI: 10.1016/s1386-5056(01)00128-9

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  10 in total

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3.  A cognitive engineering framework for the specification of information requirements in medical imaging: application in image-guided neurosurgery.

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8.  Modeling Patient Treatment With Medical Records: An Abstraction Hierarchy to Understand User Competencies and Needs.

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9.  Using team cognitive work analysis to reveal healthcare team interactions in a birthing unit.

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10.  Factors affecting the adoption of electronic signature: Executives' perspective of hospital information department.

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  10 in total

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