The objective of this study was to describe a predictive modeling approach to risk stratify people with type 2 diabetes for diabetes self-management education and support (DSMES) services. With data from a large health system, a predictive model including age, glycated hemoglobin (HbA1c), and insulin use among other factors, was developed to assess risk of future high HbA1c. The model was retrospectively applied to a cohort of people who received DSMES over a 2-year period to assess the impact of DSMES on glycemia by risk strata. Of 6934 eligible people, 4014 (58%) were in the composite low-risk group and 2604 (38%) were in the composite high-risk group. Mean HbA1c change after DSMES was −0.38% in the low-risk group and −0.84% in the high-risk group. This analysis demonstrates the potential application of predictive modeling as one approach to target DSMES resources to people who will benefit most.

中文翻译：

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分配糖尿病教育和支持服务的风险分层方法

本研究的目的是描述一种预测建模方法，用于对 2 型糖尿病患者进行糖尿病自我管理教育和支持 (DSMES) 服务的风险分层。利用来自大型卫生系统的数据，开发了一个预测模型，包括年龄、糖化血红蛋白 (HbA1c) 和胰岛素使用等因素，以评估未来高 HbA1c 的风险。该模型被回顾性地应用于一组在 2 年期间接受 DSMES 的人群，以评估 DSMES 对风险层血糖的影响。在 6934 名符合条件的人中，4014 人 (58%) 属于复合低风险组，2604 人 (38%) 属于复合高风险组。DSMES 后平均 HbA1c 变化在低风险组为 -0.38%，在高风险组为 -0.84%。