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    標題: 長期照顧關鍵字與醫學中心曝光度之研究
    A study on the visibility on Taiwan medical centers of the long-term care keywords
    作者: 苑證恩
    貢獻者: 醫務管理系
    潘大永
    關鍵字: 醫學中心
    長期照顧
    曝光度
    搜尋引擎
    Rasch分析
    網際網路
    Medical center
    long-term care
    exposure
    search engine
    Rasch analysis
    internet
    日期: 2018
    上傳時間: 2019-02-27 16:50:51 (UTC+8)
    摘要: 隨著老年人口的快速成長及對長期照顧(簡稱長照)的需求增加,醫學中心於長照2.0的服務體系下,提供長照的責任與角色亦且加重。網路上提供長照的服務內容與介紹,遂成為一項值得比較與分析的主題。
    利用試題反應理論的Rasch分析,比較醫學中心長照服務內容與介紹的關鍵字曝光度,提供醫院經營決策的參考。
    於2017年6月自華藝期刊資料庫以「長期照顧」關鍵字搜尋2005年以來的中文期刊355篇,擷取其關鍵字855個,扣除重複者及使用Google搜尋19家醫學中心在前10頁內呈現之長照關鍵字後,總計75個有效關鍵字作為本研究之測量題目,19家醫學中心為其研究對象,利用(1)Rasch模式Winsteps軟體估計受試者(即醫學中心)測量分數與題目難度、計算Fit統計指標及其標準化殘差;(2)座標散佈圖[logit分數及偏離(Outfit)均方誤]及其95%信賴區間,挑出不擬合模式的醫院及關鍵字;(3)社群網絡軟體觀察關鍵字和醫學中心之集群現象。
    研究結果顯示:(1)長期照顧關鍵字最多的是"失智症"、"疼痛"、"跌倒",最少的是"長期照護機構"、"健康照護"、"主要照顧者";(2)Rasch內聚(Infit)均方誤皆介於0.5至1.5間而構成一具單向度測量;(3)座標散佈圖顯示在95%信賴區間(即曝光度高且穩定)外計有3家醫學中心,另有6家醫學中心則呈現不穩定之現象;(4)社群網絡分析出以奇美醫院、國泰醫院、萬芳醫院、及林口長庚為代表的集群現象。
    本研究搜尋長照相關中文期刊的關鍵字,探討19家醫學中心在Google搜尋網頁之曝光度,再以Rasch模式評估其能力值與不擬合模式的異常情形,建議醫院管理者參考同儕醫院的表現,調整醫院長照相關策略與運作模式,以提升醫院長照管理的效能。
    Objective:
    With the rapid growth of the elder population and the increasing demand on long-term care in Taiwan, medical centers were participated in the long-term care plan 2.0(LTC 2.0),the role and responsibilities of the medical center in providing long-term care services under the LTC 2.0 plan are increasing. Thus, there is a need to study the visibility on Taiwan medical centers website of the long-term care keywords.
    Methods:
    Nineteen medical center websites were compared. Seventy-five keywords (as items) and 19 medical centers (as examinees) were fitted to the Rasch model (1960) after a serial Rasch analysis was performed. The extremely worldwide popular search engine, Google, incorporated with a computer program to facilitate searching efficiency was used in the present study. After>16,425 web page searches, a Likert-type 0-9 score was analyzed to estimate the visibility of each medical center website.
    Results:
    There were 75 items and 19 medical centers that fit to the Rasch model expectation. The easiest items to search on hospital websites were ”dementia”, “pain” and “fall”. The most difficult items to search on medical center websites were “long-term care institutions”, “health care” and “main caregivers”.
    The representatives of clusters classified by SNA were Chi Mei Medical Center, Cathay General Hospital, Taipei Municipal Wanfang Hospital, and Linkou Chang Gung Memorial Hospital, respectively.
    Conclusion:
    We suggest that medical center managers focus not only on website content, but on information architecture and meta-data to increase the visibility of the medical center website.
    關聯: 電子全文公開日期:2020-07-30,學年度:106, 88頁
    Appears in Collections:[醫務管理系(所)] 博碩士論文

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