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Towards a framework for untangling complexity: The interprofessional decision‐making model for the complex patient
Author(s) -
Weinberger Hadas,
Cohen Jonathan,
Tadmor Boaz,
Singer Pierre
Publication year - 2015
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.23176
Subject(s) - vagueness , health care , perspective (graphical) , complexity science , quality (philosophy) , clinical decision making , decision support system , computer science , medical decision making , patient safety , medline , management science , psychology , data science , medicine , medical emergency , data mining , artificial intelligence , epistemology , family medicine , engineering , philosophy , fuzzy logic , law , political science , economics , economic growth
Decision making for the complex patient is challenging for doctors because of increased complexity, such as multiple co‐morbidities and interprofessionality for which evidence‐based literature and guidelines are currently lacking. The consequent uncertainty causes vagueness, threatening patient safety and the quality of care. This article is motivated by the design science paradigm and describes the interprofessional decision‐making model for the complex patient, namely, INDECO along with an example instantiation. Drawing on our experience in an intensive care unit of a tertiary hospital in Israel, the bi‐dimensional view of this model includes the medical‐ and the interprofessional perspective. Retrospective assessment of 3 case studies of complex patients is used for assessing the usefulness of INDECO in decision making. The study reported here draws support from relevant literature, including the information science, information systems, and the medical domains. The findings resonate with emerging research developments focusing on healthcare decision making.