风险调整和激励机制在医疗保险编码强度的机制
Caroline S Carlin1, Roger Feldman2, Jeah Jung3
1Department of Family Medicine and Community Health, School of Medicine, University of Minnesota, Minneapolis, Minnesota, USA.
Health services research
|January 11, 2024
概括
研究了医疗保险优势 (MA) 和传统医疗保险 (TM) 计划中的诊断编码强度. 虽然CMS 2024模型的更改可能会降低强度,但它们并不能完全解决敏感的层次条件类别 (HCC) 组.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 卫生经济学 卫生经济学
- 医疗信息学 医疗信息学
背景情况:
- 诊断编码强度影响医疗保险计划支付.
- 医疗保险和医疗补助服务中心 (CMS) 实施了2024年的新风险模型.
- 了解编码强度的变化对于准确的风险调整至关重要.
研究的目的:
- 分析传统医疗保险 (TM) 和医疗保险优势 (MA) 计划中的诊断编码强度.
- 评估CMS 2024风险模型变化对编码强度的影响.
- 为了识别受编码强度影响最大的层次条件类别 (HCC) 群体.
主要方法:
- 利用了TM受益者和MA入学者的CMS索赔和遭遇数据.
- 为MA,TM负责护理组织 (ACO) 和TM非ACO受益者创建了队列.
- 使用2019年CMS HCC软件计算HCC患病率和得分,包括健康风险评估 (HRA) 和图表审查 (CR) 数据.
主要成果:
- 倾向性得分匹配的MA和TM ACO队列显示出可比的基线健康风险;TM非ACO的风险较低.
- 随着激励,HRA诊断的附加风险增加了: +0.9% (TM非ACO), +1.2% (TM ACO), +3.6% (MA).
- 随着HRA和CR数据的使用,MA风险得分增加了9.8%;特定的HCC组对编码强度高度敏感.
结论:
- 与HRA和CR记录相关的MA的健康风险增加,与之前的研究一致.
- 医疗风险评估对TM覆盖群体的健康风险测量有重大影响.
- 虽然CMS的2024年模型变化可能会抑制编码强度,但并不能全面解决所有敏感的HCC层次结构.
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