根据控制图和决策树驱动的定义,测量,分析,改进和控制过程,减少国家医疗保险中的异常费用
Yen-Chang Chen1, Shui-Chuan Chen2, Ying-Sing Liu3
1School of Sport and Health, SanMing University, SanMing, China.
Health informatics journal
|September 20, 2023
概括
这项研究确定了台湾的败血症治疗医疗保险成本显著异常. 影响成本的关键因素包括病房,治疗,实验室和药品费用,指导有针对性的改进.
科学领域:
- 卫生经济学 卫生经济学
- 医疗信息学 医疗信息学
- 提高质量 提高质量
背景情况:
- 败血症治疗需要大量的医疗费用,需要有效的资源配置.
- 识别医疗保险索赔中的成本异常对于医疗保健系统的可持续性至关重要.
- 台湾的医疗保健系统在管理治疗毒症等复杂疾病的支出方面面临着挑战.
研究的目的:
- 分析与台湾败血症治疗相关的医疗保险费用.
- 确定导致毒症护理中异常申请费用的因素.
- 为降低成本和改善资源利用提出有针对性的干预措施.
主要方法:
- 应用了定义,测量,分析,改进,控制 (DMAIC) 方法.
- 使用统计测试,成本控制图表和C5.0决策树进行数据挖掘.
- 分析了来自四个诊断相关组 (DRG) 和70家诊所的353个有效样本的数据.
主要成果:
- 一个DRG和九个诊所的异常申请费是显著的,特别是对于伴随疾病的成年人.
- 病房费,治疗费,实验室费和制药服务费对成本产生了重大影响.
- 49号,44号和14号诊所,以及治疗和实验室费用,需要优先改进.
结论:
- 开发的模型有效地识别了败血症治疗中的过度医疗支出.
- 有针对性的干预措施可以提高台湾医疗资源使用的效率.
- 这种方法可用于分析和控制不同疾病的医疗保健成本.
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