Using a Genetic Algorithm through Demographic Information to Identify Optimal Locations for Automated External Defibrillator in Taipei City

• Main Authors: Fong Jie Huang, 黃逢傑
• Other Authors: C. Y. Huang
• Format: Others
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/38408200590075033619

碩士 === 長庚大學 === 資訊工程學系 === 101 === Emergency Medical Services Systems (EMS) serve as the front line of our healthcare system during medical emergencies. The locations of emergency medical facilities directly affect the chances of survival of emergency patients. However, Taiwan is far behind other advanced nations in terms of the effectiveness of the EMS. Insufficiency of emergency medical facilities and deployment of these facilities without comprehensive considerations may pose a threat to the life of our people. This study used out-of-hospital cardiac arrest (OHCA) cases in Taipei City during 2010 as the sample. Taking advantage of the 24-hour operation of convenience stores in the city, this study used a genetic algorithm to search for the optimal stores to deploy automated external defibrillators (AED) with consideration of demographic and geographic characteristics of the sample to address the insufficiency of resources in our current EMS. The results suggested 100 stores to deploy AEDs. These stores could offer first aid to 53% of the 1625 OHCA cases in Taipei during 2010. For the 750 OHCA cases within the coverage of these stores, the expected value of resuscitation by AED could be increased to 56%. We used only 1/6 of the cost of deploying AEDs to achieve 80% of the optimal expected value of resuscitation for OHCA cases. This significant improvement in cost-effectiveness of AEDs highlights.