利用医疗补助公司的索赔来绘制复杂的慢性病的地图,以应急准备
Jaclyn M Hall1, Madison R McCraney, Christina A Vincent
1Author Affiliations: Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida (Drs Hall and Mkuu); College of Medicine, Florida State University, Tallahassee, Florida (Ms McCraney and Mr Lurk); Department of Anthropology, Florida State University, Tallahassee, Florida (Dr Chakrabarti); Data Science Team, Knowli Data Science, Tallahassee, FL (Ms Vincent and Dr Erichsen); Department of Medicine, University of Florida, College of Medicine, Gainesville, Florida (Dr Cogle).
佛罗里达医疗补助公司使用索赔数据识别了患有复杂慢性疾病 (CCC) 的易受伤害的入学者. 该系统有助于应急准备,并确保在紧急情况下为高风险人群提供持续的护理.
科学领域:
- 公共卫生 公共卫生
- 医疗信息学 医疗信息学
- 应急管理 应急管理
背景情况:
- 患有复杂慢性疾病 (CCC) 和技术依赖的医疗补助计划入学者在灾难期间面临高风险.
- 各国往往缺乏系统,以快速识别这些易受伤害的人口,以便进行灾害规划.
研究的目的:
- 开发和实施基于索赔的方法来识别佛罗里达州的医疗补助注册人与CCC,包括那些需要医疗技术.
- 支持弱势群体的应急准备和应对活动.
主要方法:
- 利用佛罗里达医疗补助管理信息系统和经过验证的代码框架将入学者分为12个CCC类别.
- 根据年龄,地理和技术依赖性分析数据.
- 为风 (2022-2024) 之前和之后的健康计划提供实时报告.
主要成果:
- 在440万名入学者中,发现有7.2%的人有CCC;其中18.2%的人依赖技术.
- 地理地图显示,灾难易发生的农村和沿海地区的度更高.
- 卫生计划使用这些数据在风恢复期间为成员推广和服务协调.
结论:
- 证明了使用索赔数据用于灾害管理的可行性和实用性.
- 其他州可以采用这种方法,以加强对医疗脆弱的医疗补助人口的紧急响应和护理连续性.
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