Development of an ‘Enteral tube feeding decision support tool’ for hip fracture patients: A modified Delphi approach

2018 ◽  
Vol 37 (3) ◽  
pp. 217-223 ◽  
Author(s):  
Aye Su Mon ◽  
Chrys Pulle ◽  
Jack Bell
Keyword(s):  
Decision Support ◽  
Hip Fracture ◽  
Tube Feeding ◽  
Decision Support Tool ◽  
Support Tool ◽  
Enteral Tube Feeding ◽  
Modified Delphi ◽  
Delphi Approach ◽  
Feeding Decision

scholarly journals Why Don’t We Tube Feed Hip Fracture Patients? Findings from the Implementation of an Enteral Tube Feeding Decision Support Tool

Geriatrics ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 12
Author(s):  
Sally Barrimore ◽  
Madeleine Davey ◽  
Ranjeev Chrysanth Pulle ◽  
Alisa Crouch ◽  
Jack J. Bell
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Hip Fracture ◽  
Tube Feeding ◽  
Decision Support Tool ◽  
Support Tool ◽  
Enteral Tube Feeding ◽  
Post Evaluation ◽  
Vulnerable Patients ◽  
And Gender

Background: This study aimed to report (i) the prevalence of enteral tube feeding (ETF), (ii) investigate whether implementing a decision support tool influenced ETF rates, and (iii) understand reasons influencing decisions to offer ETF. Methods: A pre/post evaluation included consecutive patients admitted to a hip fracture unit. Following baseline data collection, a published ETF Decision Support Tool was implemented by the multidisciplinary team to determine the necessity and influencing reasons for offering ETF. Results: Pre-post groups (n = 90,86) were well matched for age (83 vs. 84.5 years; p = 0.304) and gender (females 57 vs. 57; p = 0.683). ETF rates remained low across groups (pre/post n = 4,2; p = 0.683) despite high malnutrition prevalence (41.6% vs. 50.6%; p = 0.238). Diverse and conflicting reasons were identified regarding decisions to offer ETF. Conclusion: A complex interplay of factors influences the team decision-making process to offer ETF to nutritionally vulnerable patients. These demands are individualised, rather than algorithmic, involving shared decision-making and informed consent processes.

VP163 Patient Involvement In The Development Of Multi-Criteria Decision Tool

2017 ◽  
Vol 33 (S1) ◽  
pp. 223-223
Author(s):  
Marie-Pierre Gagnon ◽  
Sylvain L'Espérance ◽  
Carmen Lindsay ◽  
Marc Rhainds ◽  
Martin Coulombe ◽  
...  
Keyword(s):  
Decision Support ◽  
Delphi Study ◽  
Value Added ◽  
Decision Support Tool ◽  
Strategic Choices ◽  
Healthcare Organizations ◽  
Support Tool ◽  
Health Technologies ◽  
Modified Delphi ◽  
Patient Representatives

INTRODUCTION:Healthcare organizations should assess the relevance of both existing and new practices. Involving patients in decisions regarding which health technologies and interventions should be prioritized could favor a better fit between strategic choices and patients needs.METHODS:Following a systematic review of existing multi-criteria decision support tools and a consultation with hospital clinicians and managers, a set of potentially relevant criteria was identified. A three-round modified Delphi study was then conducted among four groups (hospital managers, heads of department, clinicians, and patient representatives) in order to reach consensus on criteria that should be considered in the tool.RESULTS:In total, seventy-four participants completed the third round of the Delphi study. Consensus was obtained on twelve criteria. There were some significant differences between groups in priority scores given to criteria. Patient representatives differed significantly from other groups on two criteria. Their ranking of the accessibility criteria was higher, and their ranking of the organizational aspect criteria was lower than for the other groups.CONCLUSIONS:Patient representatives can be involved in the development of a multi-criteria decision support tool to identify, evaluate and prioritize high value-added health technologies and interventions in order to enhancing clinical appropriateness The fact that accessibility aspects were more important for patient representatives calls for specific attention to these criteria when prioritizing health technologies or interventions. Furthermore, we need to ensure that the decisions made regarding the relevance of these technologies and interventions also reflect patients’ preferences.

A Decision Support Tool for Evaluating Big Data Investment in Transport: Empirical evidence from European use cases of NOESIS project

2020 ◽  
Author(s):  
Christos Katrakazas ◽  
Natalia Sobrino ◽  
Ilias Trochidis ◽  
Jose Manuel Vassallo ◽  
Stratos Arampatzis ◽  
...  
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Empirical Evidence ◽  
Decision Support Tool ◽  
Use Cases ◽  
Support Tool
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