Discriminant analysis of loyal patient between main competetive hospitals in Taitung.

• Main Authors: Chih-Hui Huang, 黃志暉
• Other Authors: Yong-Yuan Chuang
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/50973530284617975168

碩士 === 高雄醫學大學 === 公共衛生學研究所碩士在職專班 === 92 === Global Budgeting of Hospitals had been adopted to our National Health Insurance. In order to maintain their profit most hospitals have to expand their market and raise business competitiveness. But due to the cap on the budget of all hospitals, the reimbursement for every point they declared decreased a lot as well as their profit. So, all hospitals should try to avoid the so called “Game Strait” as soon as possible and cooperate with each other to continue and improve business. Market segmentation strategy is the best way to reduce vicious competition between the hospitals. Among them, “loyal patient” is one of the simplest and most feasible ways. All we have to do is increase the loyalty of the loyal patient in hand. That doesn’t cost much. In this research we tried to find out the differences between loyal patients of the three main competitive hospitals in Taitung by the statistical method. Our hope was to be able to distinguish them by discriminant functions. Eventually, we found that there are obviously some significant differences between them, i.e.: basic demographic characteristics (e.g. vocation, race, educational level, and religion), medical accessibility (e.g. dwelling location, vehicles they took, time consumed on the journey to the hospital, yearly income of the whole family), medical utilization (frequency to visit all hospitals last year, frequency to the favorite hospital last year, frequency of the family’s admission to the favorite hospital last year, had chronic disease or not). Considering the factors concerning hospital selection, there are also some significant differences between loyal patients of these hospitals, i.e.: physician factor, medical accessibility, and medical environment. Unfortunately, the attempt to distinguish “loyal patients” of these three hospitals by discriminant functions has failed because of low accuracy forecast rate. However, we strongly believed that this model is eventually feasible. We merely have to find out some other variables that are more powerful and distinguishable them. That will be left for future research to struggle with. Finally, after analyzing the appraisals by these “loyal patients”, we also gave some advice to these three main competitive hospitals as to improve their service quality and consumer marketing strategy. .