Coleman, Susanne;
Wray, Faye;
Hudson, Kristian;
Forster, Anne;
Conroy, Simon;
Tremyl, Jonathan;
Shenkin, Susan D;
... Teale, Elizabeth; + view all
(2022)
Using consensus methods to prioritize modifiable risk factors for development of manifestations of frailty in hospitalized older adults.
Nursing Open
10.1002/nop2.1370.
(In press).
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Abstract
AIM: The aim of the study was to reach consensus on modifiable risk factors for a novel system of care to address Manifestations of Frailty in hospitalized older adults. DESIGN: Consensus study. METHOD: A modified nominal group technique, incorporating expert group face-to-face interaction, review of existing evidence and pre/post-meeting questionnaire completion was undertaken November 2019–February 2020. RESULTS: Seventy-one risk factors, within seven risk factor domains (pain, medication, fluid and nutrition intake, mobility, elimination, infection, additional patient factors) were considered. It was agreed that 44 risk factors incorporating patient, organizational and environmental risk factors were modifiable and should be included in a novel system of care.
Type: | Article |
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Title: | Using consensus methods to prioritize modifiable risk factors for development of manifestations of frailty in hospitalized older adults |
Location: | United States |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1002/nop2.1370 |
Publisher version: | https://doi.org/10.1002/nop2.1370 |
Language: | English |
Additional information: | © 2022 The Authors. Nursing Open published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/). |
Keywords: | acute care, consensus methods, frailty |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10162307 |
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