4.5 Article

The development of a clinical management algorithm for early physical activity and mobilization of critically ill patients: synthesis of evidence and expert opinion and its translation into practice

Journal

CLINICAL REHABILITATION
Volume 25, Issue 9, Pages 771-787

Publisher

SAGE PUBLICATIONS LTD
DOI: 10.1177/0269215510397677

Keywords

Physiotherapy; rehabilitation; ICU; Delphi; critical care

Categories

Funding

  1. Medical Research Council of South Africa [N05/10/185]

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Objective: To facilitate knowledge synthesis and implementation of evidence supporting early physical activity and mobilization of adult patients in the intensive care unit and its translation into practice, we developed an evidence-based clinical management algorithm. Methods: Twenty-eight draft algorithm statements extracted from the extant literature by the primary research team were verified and rated by scientist clinicians (n = 7) in an electronic three round Delphi process. Algorithm statements which reached a priori defined consensus - semi-interquartile range <0.5 - were collated into the algorithm. Results: The draft algorithm statements were edited and six additional statements were formulated. The 34 statements related to assessment and treatment were grouped into three categories. Category A included statements for unconscious critically ill patients; Category B included statements for stable and cooperative critically ill patients, and Category C included statements related to stable patients with prolonged critical illness. While panellists reached consensus on the ratings of 94% (32/34) of the algorithm statements, only 50% (17/34) of the statements were rated essential. Conclusion: The evidence-based clinical management algorithm developed through an established Delphi process of consensus by an international inter-professional panel provides the clinician with a synthesis of current evidence and clinical expert opinion. This framework can be used to facilitate clinical decision making within the context of a given patient. The next step is to determine the clinical utility of this working algorithm.

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