ECHO 项目糖尿病试验改善了医疗服务不足人群的治疗效果。

Diabetes care Pub Date : 2025-02-01 DOI:10.2337/dc24-2100
Ashby F Walker, Michael J Haller, Ananta Addala, Stephanie L Filipp, Rayhan A Lal, Matthew J Gurka, Lauren E Figg, Melanie Hechavarria, Dessi P Zaharieva, Keilecia G Malden, Korey K Hood, Sarah C Westen, Jessie J Wong, William T Donahoo, Marina Basina, Angelina V Bernier, David M Maahs
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引用次数: 0

摘要

目的:社区医疗保健成果推广项目(ECHO)模式已在 180 个国家使用,通过增强医疗服务提供者的能力和远程教育方法来解决慢性病护理问题。很少有研究采用随机设计严格评估该计划对患者治疗效果的影响:研究设计:采用阶梯式楔形设计对 ECHO 糖尿病项目的实施情况进行了评估,在加利福尼亚州和佛罗里达州招募了 20 家联邦合格医疗中心 (FQHC),以随机、分阶段的方式进入干预阶段。参与的联邦合格医疗中心(简称 "辐条")提供综合数据,包括医疗保健效果数据和信息集(HEDIS)以及糖尿病技术的使用情况。患者从辐条上招募,数据收集包括历史和前瞻性 HbA1c 测量、HEDIS 标记和前后调查。线性混合模型用于生成患者水平的每月 HbA1c 估计值并评估随时间的变化;泊松回归用于建立诊所水平的技术使用模型:发言人级队列包括 32,796 名 1 型糖尿病(T1D;3.4%)和 2 型糖尿病(T2D;96.6%)患者,其中 72.7% 有公共保险或无保险。患者队列包括 582 名成年糖尿病患者(33.0% 患有 T1D,67.0% 患有 T2D)。他们的平均年龄为 51.1 岁,80.7% 有公共保险或无保险,43.7% 为非西班牙裔白人,31.6% 为西班牙裔,7.9% 为非西班牙裔黑人,16.8% 为其他种族/族裔。在受访者层面,干预前后 HbA1c >9% 的受访者比例均有统计学意义上的显著下降(范围为 31.7% 至 26.7%;P = 0.033)。在患者层面,干预前后使用连续血糖监测(范围为 25.1% 至 36.8%;P < 0.0001)和血糖泵(范围为 15.3% 至 18.3%;P < 0.001)的患者人数均有显著增加:结论:ECHO 模式有望减少糖尿病患者的健康差异,并有助于我们了解项目在医疗服务提供者层面之外的益处。
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Project ECHO Diabetes Trial Improves Outcomes for Medically Underserved People.

Objective: The Project Extension for Community Healthcare Outcomes (ECHO) model is used in 180 countries to address chronic disease care through a provider empowerment, tele-education approach. Few studies have rigorously evaluated the impact of the program on patient outcomes using randomized designs.

Research design and methods: Implementation of an ECHO Diabetes program was evaluated using a stepped-wedge design with recruitment of 20 federally qualified health centers (FQHCs) across California and Florida with randomized, phased-in intervention entry. Participating FQHCs (referred to as "spokes") provided aggregate data, including the Healthcare Effectiveness Data and Information Set (HEDIS) and diabetes technology use. Patients were recruited from spokes, and data collection involved historical and prospective HbA1c measures, HEDIS markers, and pre/post surveys. Linear mixed models were used to generate patient-level monthly HbA1c estimates and evaluate change over time; Poisson regression was used to model clinic-level technology use.

Results: The spoke-level cohort included 32,796 people with type 1 diabetes (T1D; 3.4%) and type 2 diabetes (T2D; 96.6%), of whom 72.7% were publicly insured or uninsured. The patient-level cohort included 582 adults with diabetes (33.0% with T1D, 67.0% with T2D). Their mean age was 51.1 years, 80.7% were publicly insured or uninsured, 43.7% were non-Hispanic White, 31.6% were Hispanic, 7.9% were non-Hispanic Black, and 16.8% were in other race/ethnicity categories. At the spoke level, there were statistically significant reductions before and after the intervention in the proportion of people with HbA1c >9% (range 31.7% to 26.7%; P = 0.033). At the patient level, there were statistically significant increases in those using continuous glucose monitoring (range 25.1% to 36.8%; P < 0.0001) and pump use (range 15.3% to 18.3%; P < 0.001) before and after the intervention.

Conclusions: The ECHO model demonstrates promise for reducing health disparities in diabetes and contributes to our understanding of program benefits beyond the provider level.

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