Remote decision support for wheeled mobility and seating devices

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• 作者：Kyoung-Yun Kim^a ; ^{kykim@eng.wayne.edu} ; Yun Seon Kim^b ; ¹ ; ^{sean0831@wayne.edu} ; Mark R. Schmeler^c ; ² ; ^{schmeler@pitt.edu}
• 关键词：Wheelchair prescription ; Remote wheelchair selection ; Telerehabilitation ; Decision support system ; Wheeled mobility device and seating
• 刊名：Expert Systems with Applications
• 出版年：2012
• 期刊代码：62_09574174
• 类别：et
• 出版时间：15 June, 2012
• 卷：39
• 期：8
• 页码：7345-7354
• 文件大小：1585 K

摘要

Current wheelchair selection and evaluation processes are time-consuming, often requiring cumbersome review and re-review of frequently changing wheelchair products and manufacturers. Telerehabilitation (TR) is an emerging field that complements the current in-person assessment for selecting an appropriate wheeled mobility and seating device in underserved areas. One of TR鈥檚 core functions is remote wheelchair selection (RWS), which requires detailed information on wheelchair characteristics and specifications, policy knowledge, and patient medical conditions including mobility limitation. Stakeholders currently have limited means to access comprehensive, reliable, monitored, and up-to-date information relative to wheeled mobility and seating devices, including performance, coverage criteria, or research evidence as to their benefits and short-comings. Centers for Medicare and Medicaid Services (CMS) implemented significant changes to the Healthcare Common Procedures Coding System (HCPCS) for wheeled mobility devices (WMDs) that includes expansion from 4 to 64 unique codes to identify different types of physical mobility devices (PMDs). This 16-fold increase can make it difficult to fully understand where a given product falls within the new structure. In our work we review the current TR research, wheelchair coverage policy issues, and the modern remote wheelchair selection paradigm. We introduce a framework for a web-based decision support system for remote wheelchair selection. These outcomes improve the wheelchair selection and evaluation processes through the capabilities of remote investigation of in-person assessment process, appropriated wheelchair alternatives, advanced wheelchair query and selection, a reusable wheelchair information repository, and systematic wheelchair evaluation. We also discuss lessons learned from a focus group study regarding the user acceptance of RWS-Advisor and the future direction of research on remote wheelchair selection.