French National Health Insurance (Cnam), 50, Avenue du Professeur André Lemierre, 75986 Paris Cedex 20, France; Centre for Research in Epidemiology and Population Health, French National Institute of Health and Medical Research (INSERM U1018), Université Paris-Saclay, Université Paris-Sud, UVSQ, 16, Avenue Paul Vaillant Couturier, 94807 Villejuif Cedex, France.
French National Health Insurance (Cnam), 50, Avenue du Professeur André Lemierre, 75986 Paris Cedex 20, France.
J Clin Epidemiol. 2018 Nov;103:60-70. doi: 10.1016/j.jclinepi.2018.07.003. Epub 2018 Aug 6.
The objective of the study was to develop and validate two outcome-specific morbidity indices in a population-based setting: the Mortality-Related Morbidity Index (MRMI) predictive of all-cause mortality and the Expenditure-Related Morbidity Index (ERMI) predictive of health care expenditure.
A cohort including all beneficiaries of the main French health insurance scheme aged 65 years or older on December 31, 2013 (N = 7,672,111), was randomly split into a development population for index elaboration and a validation population for predictive performance assessment. Age, gender, and selected lists of conditions identified through standard algorithms available in the French health insurance database (SNDS) were used as predictors for 2-year mortality and 2-year health care expenditure in separate models. Overall performance and calibration of the MRMI and ERMI were measured and compared to various versions of the Charlson Comorbidity Index (CCI).
The MRMI included 16 conditions, was more discriminant than the age-adjusted CCI (c-statistic: 0.825 [95% confidence interval: 0.824-0.826] vs. 0.800 [0.799-0.801]), and better calibrated. The ERMI included 19 conditions, explained more variance than the cost-adapted CCI (21.8% vs. 13.0%), and was better calibrated.
The proposed MRMI and ERMI indices are performant tools to account for health-state severity according to outcomes of interest.
本研究旨在开发并验证两种基于人群的特定于结局的发病率指数：预测全因死亡率的死亡率相关发病率指数（MRMI）和预测医疗支出的支出相关发病率指数（ERMI）。
一个包含所有参加法国主要医疗保险计划、年龄在 2013 年 12 月 31 日 65 岁及以上的受益人的队列被随机分为指数制定的发展人群和预测性能评估的验证人群。年龄、性别和通过法国医疗保险数据库中可用的标准算法（SNDS）确定的一系列条件被用作预测 2 年死亡率和 2 年医疗支出的预测因子。在单独的模型中，分别测量和比较了 MRMI 和 ERMI 的整体性能和校准情况，以及各种版本的 Charlson 合并症指数（CCI）。
MRMI 包括 16 种疾病，比年龄调整的 CCI 更具区分度（C 统计量：0.825 [95%置信区间：0.824-0.826] vs. 0.800 [0.799-0.801]），且校准更好。ERMI 包括 19 种疾病，比成本调整的 CCI 解释了更多的方差（21.8% vs. 13.0%），且校准更好。
所提出的 MRMI 和 ERMI 指数是根据关注的结局来衡量健康状况严重程度的有效工具。
