智慧復健病房之使用者需求分析

User requirements analysis for smart rehabilitation wards

10.6342/NTU201601868

梁蕙雯

智慧醫院 ； 復健 ； 失能 ； 層級分析法 ； 服務藍圖 ； smart hospitals ； rehabilitation ； disability ； analytic hierarchy process ； service printing

國立臺灣大學碩士在職專班商學組學位論文

2016年

碩士

陳鴻基

繁體中文

醫療界引進資訊溝通技術已有多年，隨著科技的發展，物聯網成為發展智慧醫院的新契機，然而，在建構系統之初，探討使用者需求是重要起步。有鑑於失能與老年人口增加，對於復健以及長期照護需求上升，本研究選定復健病房做為研究場域，希望藉由智慧病房之設計，延伸至未來之社區或居家復健。本研究之目的在利用服務藍圖、深度訪談以及層級分析法探討某醫學中心復健病房醫療團隊成員對於建置智慧病房之臨床需求，本研究完成之項目包括：1)繪製復健病房提供復健服務之服務藍圖；2)邀集復健團隊之資深人員，以深度訪談了解臨床待滿足的工作需求；3)彙整臨床服務之重要需求構面；4)以層級分析法針對重要需求構面評值其權重並進行排序，了解團隊整體以及不同職類人員給予之相對權重。分析結果顯示，整體復健醫療團隊對於特殊警示以及評估紀錄之需求權重最高，各職類人員的需求面權重不同，反映出醫療團隊中不同工作特性的互補性，在建構智慧病房系統時，可以藉此進行符合臨床工作者需求之設計。

Information communication technology has been incorporated into healthcare services for years. As the technology evolves, internet of things introduces new opportunities for constructing smart hospitals. It is important to explore the users’ requirement during early stage of development. Along with the growing numbers of disabilities and elderly, the need for rehabilitation and long-term care rises. The current research focused on the rehabilitation wards because of the possibilities of extension of the designs from hospitals to communities as the basis of telerehabilitation. We used service blueprinting, in-depth interviewing and Analytic Hierarchy Process to explore the users’ requirement of smart hospitals from the prospective of clinical workers in rehabilitation wards of a medical center. As the results, we 1) completed a service blueprinting for in-patient rehabilitation; 2) explored the unmet needs during clinical works by in-depth interviewing senior workers; 3) summarized the requirement domains during clinical works; 4) ranked the requirement domains by Analytic Hierarchy Process. Our results also showed the highest ranked requirements as clinical alerts and evaluation/recording. The different rankings of requirements among workers of different professions reflected the need of accommodation and customarization. The above findings would provide useful insights into clinical workers’ requirements for future system designs.

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