A Business Intelligence Approach to Assessing Operating Performance of Outpatient Services in a Medical Center

• Main Authors: Mei-ChiaChiang, 江美佳
• Other Authors: Sheng-Tun Li
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/ejrz5v

碩士 === 國立成功大學 === 高階管理碩士在職專班(EMBA) === 102 === 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.