Factors Associated with Staying for Patients in the Emergency

• Main Authors: Fung Ju Lin, 林芳如
• Other Authors: M. Chao
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/ak8wst

碩士 === 長庚大學 === 商管專業學院碩士學位學程在職專班醫務管理組 === 105 === Objective To compare the correlations between different factors and to analyze the correlation between the characteristics of patients with emergency medical treatment and the time of stay in order to provide information on the relationship between emergency medical treatment and emergency treatment Crowded phenomenon, the establishment of care for the quality of the reference direction. The object was a medical center in the north of 2015 emergency medical treatment 168,919 people hospital medical information management system login information, the results that emergency medical patients with male (53.5%), the age was less than 10 years old 36,105 person (21.4%) the most, but the older ones stay longer Long, due to the high severity of the disease, (60.6%), the disease of various morbid 37,287 person-time (22.1%), medical treatment time at 8.9879 person (5.8%), small night shift 68,536 person (40.6%) for the emergency attendance times; in the case of holiday and non-holiday distribution, (40.9%), non-holiday average stay time 10.6 hours average greater than the holiday 9.06 hours, the reason for the holiday for the mild patients (64.9%) more than the holiday medical treatment 59,328; (14.7%) on Monday, with a maximum of 109,696 person (64.9%) in the third grade, and the number of patients in the first week of the week, with a maximum of 109,696 person (64.9%). In the regression analysis, it was found that each additional one year of age left the emergency time increased by 0.16 hours, the sex ratio of male and female more than 1.31 hours, the holiday is shorter than the non-holiday 0.72 hours, the detection level is reduced for each level that is shortened 6.85 hour. Understand what the emergency medical treatment of the community, and can predict the patient left the emergency time to improve the patient's emergency care quality and reduce the urgency of emergency time, thereby improving the emergency cost of waste and upgrade Internal and external customer satisfaction.