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系統識別號 U0026-1808201408122000
論文名稱(中文) 以商業智慧法分析醫學中心門診作業績效之研究
論文名稱(英文) A Business Intelligence Approach to Assessing Operating Performance of Outpatient Services in a Medical Center
校院名稱 成功大學
系所名稱(中) 高階管理碩士在職專班(EMBA)
系所名稱(英) Executive Master of Business Administration (EMBA)
學年度 102
學期 2
出版年 103
研究生(中文) 江美佳
研究生(英文) Mei-Chia Chiang
學號 R07014869
學位類別 碩士
語文別 中文
論文頁數 86頁
口試委員 指導教授-李昇暾
口試委員-林清河
口試委員-耿伯文
口試委員-李經維
中文關鍵字 商業智慧  門診作業績效  候診時間  建議報到時間 
英文關鍵字 Business Intelligence  Operating Performance of Outpatient Services  waiting time  suggested arrival time 
學科別分類
中文摘要 台灣醫療產業除了要面對外部競爭激烈的環境,提升營運績效之外,經常要因應衛生主管機關的評鑑或督考所帶來對於內部管理的沉重壓力。因此,若能藉由商業智慧法(Business intelligence),透過資料的萃取、整合及分析,優化門診病人就醫流程所產生的資訊,以快速、正確的資料支援決策,將可提升醫院的服務品質,帶動醫院營運效率及競爭力,有效因應變化快速的環境。
為了改善以往醫療人員缺乏組織及低效率的資料整理方法,提高行政效率,本研究運用商業智慧法,透過OLAP分析門診作業績效的現況。首先進行資料庫建置,再經過資料清理、轉換等步驟,利用Star Schema多維度的資料結構,依需求透過OLAP直覺式的操作,快速處理複雜及大量資料,進行各類查詢分析,即時產生各項報表或是視覺化呈現結果,建立豐富且具有互動性的分析結果,讓決策者能夠導出真知灼見。
經本研究之分析探討,得到以下兩項結論及相關建議:1.透過商業智慧法建置決策支援系統,可以節省人力、增加工作效益,加快決策及投注資源速度,因此,建議醫院資訊單位協助建置門診資料倉儲,及對醫院同仁進行資料分析能力之培訓教育課程,以提升行政管理效率。2.加強以下三點以提升門診作業績效:(1)提升管理效率及服務品質:每月監測並管理門診作業績效品質;提高利用健保卡插卡報到之使用率;將延診時間過久且病人數過多之診別,以切診方式處理,以減少延診之情形。(2)提高門診服務量:增加開診時段且每月監測及管理開診數;策略性地提高初診率及複診率;提高門診空間使用率。(3)縮短病人候診時間:鼓勵病人善用各種預約方式以提高預約掛號病人比例;鼓勵病人善用看診進度查詢功能,減少就醫民眾早到率;定期監測建議報到時間之準確率並修正設定值,以提高準確率。
英文摘要 英文延伸摘要
SUMMARY
This study applies business intelligence solution to healthcare providers in order to improve non-integrated database and inefficient data processing system that hospital and clinical organization have been struggling in the past. The research aims to use the Business Intelligent “BI” as data processing methodology to analyze huge volume of clinical data collected from outpatient during the procedure flow of receiving treatment. The big data of the hospital and clinic can be derived and transformed to meaningful intelligent knowledge by advancing data process system. The innovative data analysis system-BI allows the healthcare organization leader to get access to the insight of effective hospital operation management.

INTRODUCTION
The length of human life is greatly extended in the last decade because of the healthcare technical advancement. Baby given born rate is keeping downturn while aging generation era is coming. People pay more attention on keeping physical health. Therefore, the need of the healthcare in Taiwan is rapidly growing. Citizens are care about clinical treatment quality. The healthcare providers work hard to provide better medical treatment service to patients. Also, Healthcare providers strive to gain operational performance while they are facing a big challenge. It is not only from outside healthcare competition but also the pressure and scrutiny from the Food and Drug Administration authorities. This research utilize business intelligence (BI) solution to support managerial decision making, provide quick and easy access to the data with predefined report designs and improve patient treatment satisfaction based on patient oriented service policy. To enhance the level of hospital service quality, researcher attempt to extract, aggregate and analyze the clinical huge volumes of data that is collected from day-to-day hospital operation. Eventually, the healthcare provider can get fast response to the environment alteration.

MATERIALS AND METHODS
This paper uses BI as a strategic initiative data management methodology to improve the hospital operation by implementing Online Analytical processing (OLAP). It can deal with the raw data quickly and response the need of healthcare providers and executive administration to make effective decision in the future.
BI consist a lot of function, such as integration, information delivery and analysis. Information technology center of hospital need to build up a data warehouse for BI system to extract the clinical big data and transform to the database. The data warehouse is a great system to conduct data mining exercises along with OLAP in which user can perform multi-dimensional analysis of data, for instance, roll up, drill down, slice and dice, pivot, sort, filter data to discover patterns. It is possible to realize the potential of data collected within healthcare organization as day-to-day clinical data under analysis is massive, multi-dimensional, distributed and uncertain by applying OLAP data mining techniques.
By using OLAP, analysts can deliver the operational and monitoring reports based on interactive visualized format, like graph or chart. Executive leaders an base on the aggregated data and insightful graphic to make strategic decision and predict what will happen in the future.

RESULTS AND DISCUSSION
In this paper, it shows business intelligent system can provide healthcare provider management the real time analysis result, generate visualized operational and monitoring report to track the strategic performance and provide best optimized strategic to make right decision in the future.
We found that there are some points of view regarding the case study of the hospital uncertain from this research. Furthermore, we suggest the approach can take the following perspectives into consideration in order to enhance data reliability:
1.The utilization rate of the examination room can simply stand for the real usage during the hospital operation hours. The hospital of the case study actually uses the non-utilized room for other operational purpose which is not accounted for the physician utilization rate. As a result, the rate of the physician room might be under estimated. The actual rate of hospital physician usage should be higher than the statistical figure collected from clinical database.
2.To improve profitability through increasing the physician examination and treatment schedule or strategically raising the number of the first visit patient and increasing current patient return visit.
The above-mentioned strategies proposed in this paper might be challenged because there might be ceiling effect existing in the operation cost constraint based on Taiwan current citizen health insurance coverage and reimbursement policy. To increase the patient visit does not necessarily stand for the growth of the profit. More patient visit per physician working hours might cause profit down. However, reducing patient visit cannot meet the operation performance target. Hence, the possible way for hospital to gain profit is to implement cost reduction strategy, for instance, downsize the operation team. On the other hand, there might be side effect by lean the operation staff because the service of the treatment or patient data analysis quality might be impacted due to insufficient human resource.
Healthcare managers should pay attention to this problem of hospital operation.

CONCLUSION
From the research, we gain two conclusions and some relative suggestions:
Using healthcare BI, hospital executive level management can build up strategic digital decision making flow system, to support lean organization structure, enhance operational effectiveness and eventually affiliate the collaborative communication and resource allocation. Therefore, we suggest the information technology department would create clinical patient data base and implement data base analytical training course to the front end operation staff, to improve clinic administrator working efficiency. 2. Highlight the following three actions to improve hospital and clinic physician consultation performance:
1.The ways to increase the managerial efficiency and service quality:
(1)Monitoring and Managing the operational performance of physician examination monthly.
(2)Splitting the overloaded physician to two separate consultation room to reduce the physician hour extension.
2.Increasing the insured patient visit:
Open night physician consultation shift strategically to increase the first visit or return visit patient and raise the usage of consultation room.
3.Squeezing the patient consultation time:
(1)Encourage patient to register through multiple route to reach higher visit number.
(2)Encourage patient to check consultation status to avoid early arrival.
(3)Monitor the accuracy of patient arrival time and to adjust the suggested arrival time on mobile consultation status check system.
論文目次 摘要 I
誌謝 VI
目 錄 VIII
表目錄 X
圖目錄 X
第一章 緒論1
1.1研究背景與動機1
1.2研究目的2
1.3研究架構4
第二章文獻回顧5
2.1醫療服務品質與病患滿意度5
2.2門診作業績效管理9
2.3商業智慧10
2.3.1商業智慧方法論11
2.3.2線上分析處理12
第三章研究方法16
3.1研究工具16
3.2商業智慧雛型系統的建置19
3.3商業智慧的程序21
3.3.1資料倉儲21
3.3.2資料倉儲的資料維度模式23
3.3.3資料倉儲建置流程24
3.4線上即時分析處理26
3.5運用商業智慧系統協助日常管理與經營決策需求28
3.6運用商業智慧系統解決經營需求29
第四章研究結果及討論30
4.1門診作業資料庫之商業智慧雛型系統30
4.2門診服務量分析31
4.2.1每月/各科/各醫師週開診數分析31
4.2.2門診病人數成長分析 34
4.2.3院初診及院複診病人數分析36
4.2.4現場掛號與預約掛號病人數分析37
4.3門診看診診間使用率分析39
4.4病人以健保IC卡報到之使用率分析43
4.5建議報到時間分析45
4.5.1建議報到時間之設定執行率分析46
4.5.2建議報到時間之準確率分析47
4.6門診候診時間分析55
4.6.1平均每病人次候診時間分析55
4.6.2現場掛號與預約掛號病人之候診時間分析 56
4.6.3初診與複診病人之候診時間分析57
4.7門診看診時間分析58
4.7.1平均每病人次看診時間分析58
4.7.2現場掛號與預約掛號病人之看診時間分析 60
4.7.3初診與複診病人之平均看診時間分析61
4.7.4病人到診與醫師看診之情境分析62
4.8病人報到尖峰及離峰流量分析68
4.8.1每日病人報到尖峰及離峰流量分析68
4.8.2每日各候診區病人報到尖峰及離峰流量分析69
4.9門診延診分析72
4.9.1各科延診及全院延診時間最大值分析72
4.10系統效益75
第五章結論與建議76
5.1結論與建議76
5.2研究限制78
5.3管理意涵79
5.4未來展望80
參考文獻82
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網站資料
College & Mills,1962. 1960s — General Mills and Dartmouth College, in a joint research project, develop the terms dimensions and facts http://en.wikipedia.org/wiki/Data_warehouse
DIGITIMES中文網 http://www.digitimes.com.tw/tw/dt/n/shwnws.asp?CnlID=10&cat=55&id=0000123627_5VH7B0SG1AKQW98UJXAR7&ct=2#ixzz38eYK0XZL
董事基金會http://nutri.jtf.org.tw/index.php?idd=23&aid=45&bid=&cid=1809
衛生福利部中央健康保險署http://www.nhi.gov.tw/
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