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  1. NTU Theses and Dissertations Repository
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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/103447
標題: 中醫診所數位轉型之研究:以雲端經營管理與病患服務效益為核心
A Study on the Digital Transformation of Traditional Chinese Medicine Clinics: Centering on the Benefits of Cloud-Based Operations Management and Patient Care
作者: 王伯綸
Po-Lun Wang
指導教授: 魏志平
Chih-Ping Wei
共同指導教授: 柯冠州
Kuan-Chou Ko
關鍵字: 中醫診所; 數位轉型; 企業流程再造(BPR); 病患關係管理(PRM/CRM); 雲端醫療系統; LINE@行動服務
Traditional Chinese Medicine (TCM) Clinics; Digital Transformation; Business Process Reengineering (BPR); Patient Relationship Management (PRM/CRM); Cloud Healthcare System; LINE@ Mobile Service
出版年 : 2026
學位: 碩士
摘要: 隨著醫療產業面臨宏觀環境變遷(PESTEL分析)與雙軸轉型趨勢,傳統中醫診所亟需透過數位科技突破營運與服務瓶頸。本研究旨在探討中醫診所推動數位轉型之實務需求與成效,捨棄傳統單純探討資訊系統技術品質的框架,轉而建構兼具「B2B診所營運管理」與「B2C病患關係價值」之雙軌評估指標。
本研究以「企業流程再造(BPR)」與「病患關係管理(PRM/CRM)」為核心理論基礎。透過雙軌問卷調查法,總計蒐集B2B診所端534份及B2C民眾端448份有效樣本,並運用柏拉圖功能優先排序與深度的分眾交叉分析,精準萃取中醫診所面對規模化發展時的數位剛需。
問卷調查顯示,中醫診所之數位轉型需求具有顯著的分眾差異與非線性成長特徵。在B2B診所端,當每日看診量跨越100人次的大型營運規模時,對於「智慧藥庫與供貨掌握」的需求呈現爆發性跳升(高達84.06%),證實流程再造 (BPR) 已成為維持跨院區營運的必備基礎設施;在B2C民眾端,數位服務能有效消除就醫不確定性,且出現清晰的任務移轉軌跡,其中51-60歲之中高齡族群對「看診前AI症狀整理功能」的需求居全區間之冠(達63.6%),打破長者排斥科技之迷思,凸顯透過 PRM 建立連續性照護價值的重要性。
綜合分析,本研究確立中醫診所之數位化應採「痛點導向(+AI)」而非「技術導向(AI+)」策略,並提出具高度商業落地價值之「三階段導入策略」:第一階段為基礎建設期(建置雲端HIS與LINE@解決掛號與庫存等高頻痛點)、第二階段為數據整合與關係深化期(強化跨院區數據與精準CRM)、第三階段為智慧賦能期(導入AI輔助與高階決策)。本研究不僅豐富智慧醫療領域之學術文獻,更為實務界提供清晰的數位轉型藍圖。
Facing macro-environmental changes (PESTEL) and the trend of dual transformation in the healthcare industry, traditional Chinese medicine (TCM) clinics urgently need digital technologies to overcome operational and service bottlenecks. This study aims to explore the practical needs and effectiveness of TCM clinics' digital transformation. Abandoning the traditional framework of solely evaluating information system technical quality, this research establishes a dual-track evaluation framework encompassing both "B2B Clinic Operational Management" and "B2C Patient Relationship Value".
Grounded in Business Process Reengineering (BPR) and Patient Relationship Management (PRM/CRM) theories, this research employed a dual-questionnaire survey method. A total of 534 valid B2B clinic samples and 448 valid B2C patient samples were collected. The study utilized Pareto functional priority ranking and in-depth cross-segmentation analysis to precisely extract the rigid digital demands of TCM clinics facing scalable development.
The survey results reveal that the digital transformation needs of TCM clinics exhibit significant segmentation differences and non-linear growth characteristics. In the B2B context, when the daily patient volume exceeds 100, the demand for "smart inventory and supply tracking" experiences an explosive jump (up to 84.06%), proving that BPR has become an essential infrastructure for maintaining cross-clinic operations. In the B2C context, digital services effectively eliminate medical uncertainty and show a clear task shift trajectory. Notably, the 51-60 age group exhibits the highest demand for the "pre-consultation AI symptom summary function" (63.6%), breaking the stereotype that elders reject technology and highlighting the importance of establishing continuous care value through PRM.
Based on the comprehensive analysis, this study concludes that TCM clinics should adopt a "pain-point-oriented (+AI)" strategy rather than a "technology-driven (AI+)" approach. Furthermore, it proposes a highly practical "Three-Stage Implementation Strategy": Stage 1 focuses on foundational infrastructure (implementing Cloud HIS and LINE@ to solve high-frequency pain points like registration and inventory); Stage 2 centers on data integration and relationship deepening (enhancing cross-clinic data and precise CRM); and Stage 3 aims at smart empowerment (introducing AI assistance and advanced decision-making). This study not only enriches the academic literature on smart healthcare but also provides a clear digital transformation blueprint for practitioners.
URI: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/103447
DOI: 10.6342/NTU202603353
全文授權: 同意授權(限校園內公開)
電子全文公開日期: 2026-08-19
顯示於系所單位:商學組

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