導入醫院智能作業系統並探討病患等候時間──某醫學中心門診抽血室之初探研究

Importing Hospital Intelligent Operating System to Analyze the Waiting Time of Outpatients–A Pilot Study of the Phlebotomy Station of the Medical Center

門診服務質量直接影響醫院形象與病患滿意度。醫院導入智能作業系統可改善病患等候時間，智能化抽血櫃台亦可提升門診抽血服務品質。本次研究目的包含兩點：第一為探討智能作業系統在門診抽血尖峰時段對病人等候時間現況；第二是透過數據分析找出影響門診抽血病人等候時間的重要因素。本研究以某醫學中心已導入智能作業系統的門診抽血室作為研究場域，研究對象為該門診抽血室服務的病人，研究自變項包含時間屬性因子、病人屬性因子、抽血櫃台屬性因子，依變項為病患的等候時間與抽血時間。研究資料收集期間為2019年1月到12月，扣除不完整與無法辨識之數據，經篩選後共計201,253筆資料，其中男性佔103,108人(51.23%)，女性佔98,145人(48.77%)；九月平均等候時間最久為20.17分鐘；星期一與星期二抽血人數最多，分別佔總數的22.56與21.97%，平均等候時間為(21.67、19.92)分鐘；早上7:00~8:30為人潮尖峰的報到時段，服務人次佔早上時段的24.11%，且平均等候時間為18.47分鐘。近年來醫療的智能化作業系統發展迅速，透過本次的門診抽血智能作業系統的數據分析，研究結果可提供各醫療機構參考以進一步改善門診抽血於尖峰時段的等候時間，提高醫療服務品質。

Outpatient is an important service department of a hospital, and the quality of service directly affects the image of the hospital and patient satisfaction. The introduction of an intelligent operating system in the hospital can improve patient waiting time, and the intelligent blood sampling counter can improve the quality of outpatient blood drawing services. The purpose of this study consists of two parts. The first one is the intelligent medical system to explore the current situation of patient waiting time during the peak period of blood sampling clinics. The second part is to analyze the data to find out the main factors for the prolonged service time of phlebotomy stations. This study uses an outpatient phlebotomy station in a New Taipei City medical center that has built an intelligent blood sampling counter as the research field. The research subject is the patient at the outpatient phlebotomy station of the hospital. The research independent variables include time attribute factors, patient attribute factors, and blood sampling counter attribute factors, the dependent variable, as well as the waiting time and blood drawing time of patients at the phlebotomy station of this medical center. The research period is from January to December 2019, the research data deducts incomplete and unidentifiable data. After selection, a total of 201,253 data items are available. Among them, 103,108 were male (51.23%) and 98,145 were female (48.77%); the longest waiting time in September was 20.17 minutes; the largest number of blood drawing were drawn on Monday and Tuesday, accounting for 22.56 and 21.97% of the total respectively, and the average waiting time It is (21.67, 19.92) minutes. 7:00~8:30 in the morning is the peak check-in and arrival time, The number of patients served accounts for 24.11% of the morning time, and the average waiting time is 18.47 minutes. In recent years, the development of intelligent medical operating systems has made rapid progress. This research attempts to identify important variables that affect the waiting time for blood sampling, which will help different medical institutions to improve the intelligent blood sampling system or resource allocation, and carry out the crowds during peak hours. In addition, to avoid the public complaining about the long waiting time for blood drawing during peak hours, resulting in the risk of reduced service quality