Mohapatra Sushmita, Cheung Kei-Long, Hiligsmann Mickaël, Anokye Nana
Department of Health Sciences, College of Health Medicine and Life Sciences, Brunel University London, London UB8 3PH, UK.
Department of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, 6200 MD Maastricht, The Netherlands.
Methods Protoc. 2021 May 6;4(2):27. doi: 10.3390/mps4020027.
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.
高效决策对于确保合理利用医疗资源进行充分康复至关重要。确定与康复服务决策相关的因素,对于指导临床工作人员为重症中风患者做出以患者为中心的康复决策非常重要。在本研究中,我们进行了一项最佳-最差尺度法(BWS)实验,以确定对于决定重症中风患者出院后可能接受的持续康复服务类型而言最重要的因素及其相对重要性权重。在调查设计方面采用了分数、高效的设计方法。将招募经常参与中风单元康复决策的关键多学科工作人员参与在线BWS调查。将使用分层贝叶斯估计作为主要分析方法,以最佳-最差计数分析作为次要分析。目前正在对该调查进行试点,然后再开始数据收集过程。预计2021年9月底得出结果。该研究将为当前关于中风康复临床决策的文献增添内容。研究结果将量化英国中风单元中参与中风后康复决策的关键多学科临床医生对各因素的偏好。