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  • Title: Critical care nurse practitioners and clinical nurse specialists interface patterns with computer-based decision support systems.
    Author: Weber S.
    Journal: J Am Acad Nurse Pract; 2007 Nov; 19(11):580-90. PubMed ID: 17970858.
    Abstract:
    PURPOSE: The purposes of this review are to examine the types of clinical decision support systems in use and to identify patterns of how critical care advanced practice nurses (APNs) have integrated these systems into their nursing care patient management practices. The decision-making process itself is analyzed with a focus on how automated systems attempt to capture and reflect human decisional processes in critical care nursing, including how systems actually organize and process information to create outcome estimations based on patient clinical indicators and prognosis logarithms. Characteristics of APN clinicians and implications of these characteristics on decision system use, based on the body of decision system user research, are introduced. DATA SOURCES: A review of the Medline, Ovid, CINAHL, and PubMed literature databases was conducted using "clinical decision support systems,""computerized clinical decision making," and "APNs"; an examination of components of several major clinical decision systems was also undertaken. CONCLUSIONS: Use patterns among APNs and other clinicians appear to vary; there is a need for original research to examine how APNs actually use these systems in their practices in critical care settings. Because APNs are increasingly responsible for admission to, and transfer from, critical care settings, more understanding is needed on how they interact with this technology and how they see automated decision systems impacting their practices. IMPLICATIONS FOR PRACTICE: APNs who practice in critical care settings vary significantly in how they use the clinical decision systems that are in operation in their practice settings. These APNs must have an understanding of their use patterns with these systems and should critically assess whether their patient care decision making is affected by the technology.
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