Literature DB >> 12827103

Hemodynamic team decision making in the cardiac surgical intensive care context.

Judy Currey1, Mari Botti, Jan Browne.   

Abstract

PURPOSE: The purpose of this study was to explore the extent and sources of variability of critical care nurses' hemodynamic decision making as a function of contextual factors in the immediate 2-hour period after cardiac surgery.
METHODS: A qualitative exploratory design with observation and interview was used. Eight critical care nurses were observed on different occasions in clinical practice for a 2-hour period. A brief interview immediately followed each observation to clarify observation data.
FINDINGS: Analysis of the data revealed that patient management decisions were made both by individual nurses and by a team of nurses and health professionals. Team decision making (TDM) is described in this study as integrated or non-integrated and refers to an intra-professional nursing team. During displays of integrated TDM, the primary nurse, who was assigned to care for the patient, made most hemodynamic decisions and nurses who assisted the primary nurse deferred decisions. During displays of non-integrated TDM, nurses assisting the primary nurse assumed responsibilities for most patient-related decisions. Non-integrated TDM occurred more frequently when inexperienced cardiac surgical intensive care nurses were in the role of primary nurse, whereas integrated TDM was more common among experienced cardiac surgical intensive care nurses.
CONCLUSIONS: This observed variability can occur in multiple ways and in hemodynamic decision making has implications for patient outcomes as behaviors of non-integrated TDM led to nurses sensing a loss of control of patient management.

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Year:  2003        PMID: 12827103     DOI: 10.1016/s0147-9563(03)00041-4

Source DB:  PubMed          Journal:  Heart Lung        ISSN: 0147-9563            Impact factor:   2.210


  1 in total

1.  Do nurses reason 'adaptively' in time limited situations: the findings of a descriptive regression analysis.

Authors:  Huiqin Yang; Carl Thompson; Martin Bland
Journal:  BMC Med Inform Decis Mak       Date:  2014-11-15       Impact factor: 2.796

  1 in total

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