資料庫行銷是實行關係行銷不可或缺的利器。以往國內的醫療產業,因為經營理念較為保守,以及法規的限制,並不太重視醫療行銷。近年來,消費者知識水準不斷的提升,民眾對於醫療服務品質的期望也隨之愈來愈高,病患及其家屬對於醫療服務評價的參與,也有明顯增加的趨勢。故各醫療院所在面對種種挑戰時,對醫病關係管理也漸趨重視,釵h醫院機構均導入 CRM 系統,希冀能透過調查與分析,瞭解病患對各項醫療服務的訴求,確實做好醫病關係管理,使病患對醫院的滿意度不斷的提升,並提升醫院形象。 本研究嘗試以醫療產業為研究對象,藉由健保局資料庫中個別病患的就診記錄,利用 RFM 模型,首先進行「最大概似估計法(MLE)」、「加權最大概似估計法(WMLE)」與「層級貝氏估計法(HB)」之平均就診期間分析;再進行病患活躍性分析、病患價值分析,與就診科別關聯性分析。並期能經由上述分析,研擬適當的策略,作為醫療機構醫病關係管理的參考。除了能減少病患往來醫院的次數,節省病患成本,亦能提升醫院形象及強化經營效率,且能成為民眾選擇就醫醫院的重要考量因素。
Database marketing is a useful method for implementing relationship marketing. In the past, the domestic medical institutions did not pay much attention to medical marketing because of the conservative mission and the restrictions of laws and regulations. Recently, however, as customers’ knowledge level is growing, and the expectations of high quality health care services are increasing, more and more patients and their family members evaluate the quality of the health care services. Today, many medical institutions realize the importance of patient relationship and start to implement CRM systems, trying to know the patients’ demands on health care services through investigations and analyses, and propose feasible strategies to improve hospital image and patient’s satisfactions, and sustain competitive advantage in the rapid changing environment. In this thesis, we use the database of universal health insurance as samples. First of all, we consider the patient’s inter-time analysis through RFM Model, including Maximum Likelihood Estimation, Weighted Maximum Likelihood Estimation and Hierarchical Bayesian Model. Then we conduct the patient active analysis and value analysis, and finally conduct department combination analysis. Through the analysis, we realize patient’s behavior, value more efficiently and execute high quality health care services precisely through patient relationship management, then hospitals can provide services making patients more convenient, and then it can promote the hospital’s image and improve the relations with patients substantially.