There should be no decision making at all. You look at the objective damage diagnosis and choose the protocols that will fix that damage. Until we get to that level of specificity stroke survivors are screwed because your stroke medical professionals are shooting in the dark about how to get survivors 100% recovered.
Most Important Factors for Deciding Rehabilitation Provision for Severe Stroke Survivors Post Hospital Discharge: A Study Protocol for a Best–Worst Scaling Experiment
Sushmita Mohapatra 1,*
,† , Kei-Long Cheung 1,† , Mickaël Hiligsmann 2 and Nana Anokye 1
Citation: Mohapatra, S.; Cheung,
K.-L.; Hiligsmann, M.; Anokye, N.
Most Important Factors for Deciding
Rehabilitation Provision for Severe
Stroke Survivors Post Hospital
Discharge: A Study Protocol for a
Best–Worst Scaling Experiment.
Methods Protoc. 2021, 4, 27. https://
doi.org/10.3390/mps4020027
Academic Editor: Philip Hublitz
Received: 2 March 2021
Accepted: 28 April 2021
Published: 6 May 2021
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affiliations.
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1 Department of Health Sciences, College of Health Medicine and Life Sciences, Brunel University London,
London UB8 3PH, UK; keilong.cheung@brunel.ac.uk (K.-L.C.); nana.anokye@brunel.ac.uk (N.A.)
2 Department of Health Services Research, CAPHRI Care and Public Health Research Institute,
Maastricht University, 6200 MD Maastricht, The Netherlands; m.hiligsmann@maastrichtuniversity.nl
* Correspondence: sushmita.mohapatra@brunel.ac.uk; Tel.: +44-(0)-1895-266477
† These authors contributed equally to this work.
,† , Kei-Long Cheung 1,† , Mickaël Hiligsmann 2 and Nana Anokye 1
Citation: Mohapatra, S.; Cheung,
K.-L.; Hiligsmann, M.; Anokye, N.
Most Important Factors for Deciding
Rehabilitation Provision for Severe
Stroke Survivors Post Hospital
Discharge: A Study Protocol for a
Best–Worst Scaling Experiment.
Methods Protoc. 2021, 4, 27. https://
doi.org/10.3390/mps4020027
Academic Editor: Philip Hublitz
Received: 2 March 2021
Accepted: 28 April 2021
Published: 6 May 2021
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affiliations.
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1 Department of Health Sciences, College of Health Medicine and Life Sciences, Brunel University London,
London UB8 3PH, UK; keilong.cheung@brunel.ac.uk (K.-L.C.); nana.anokye@brunel.ac.uk (N.A.)
2 Department of Health Services Research, CAPHRI Care and Public Health Research Institute,
Maastricht University, 6200 MD Maastricht, The Netherlands; m.hiligsmann@maastrichtuniversity.nl
* Correspondence: sushmita.mohapatra@brunel.ac.uk; Tel.: +44-(0)-1895-266477
† These authors contributed equally to this work.
Abstract:
Efficient decision-making is crucial to ensure adequate rehabilitation with optimal use of
healthcare resources. Establishing the factors associated with making decisions concerning rehabilitation provision is important to guide clinical staff towards person-centred decisions for rehabilitation
after severe stroke. In this study we conduct a best–worst scaling (BWS) experiment to identify the
most important factors and their relative weight of importance for deciding the type of ongoing
rehabilitation services a person with severe stroke might receive post hospital discharge. Fractional,
efficient designs are applied regarding the survey design. Key multidisciplinary staff regularly
involved in making decisions for rehabilitation in a stroke unit will be recruited to participate in an
online BWS survey. Hierarchical Bayes estimation will be used as the main analysis method, with
the best–worst count analysis as a secondary analysis. The survey is currently being piloted prior
to commencing the process of data collection. Results are expected by the end of September 2021.
The research will add to the current literature on clinical decision-making in stroke rehabilitation.
Findings will quantify the preferences of factors among key multi-disciplinary clinicians working in
stroke units in the UK, involved in decision-making concerning rehabilitation after stroke.
healthcare resources. Establishing the factors associated with making decisions concerning rehabilitation provision is important to guide clinical staff towards person-centred decisions for rehabilitation
after severe stroke. In this study we conduct a best–worst scaling (BWS) experiment to identify the
most important factors and their relative weight of importance for deciding the type of ongoing
rehabilitation services a person with severe stroke might receive post hospital discharge. Fractional,
efficient designs are applied regarding the survey design. Key multidisciplinary staff regularly
involved in making decisions for rehabilitation in a stroke unit will be recruited to participate in an
online BWS survey. Hierarchical Bayes estimation will be used as the main analysis method, with
the best–worst count analysis as a secondary analysis. The survey is currently being piloted prior
to commencing the process of data collection. Results are expected by the end of September 2021.
The research will add to the current literature on clinical decision-making in stroke rehabilitation.
Findings will quantify the preferences of factors among key multi-disciplinary clinicians working in
stroke units in the UK, involved in decision-making concerning rehabilitation after stroke.
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