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
{"title":"ECHO 项目糖尿病试验改善了医疗服务不足人群的治疗效果。","authors":"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","doi":"10.2337/dc24-2100","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>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.</p><p><strong>Research design and methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>The ECHO model demonstrates promise for reducing health disparities in diabetes and contributes to our understanding of program benefits beyond the provider level.</p>","PeriodicalId":93979,"journal":{"name":"Diabetes care","volume":" ","pages":"243-250"},"PeriodicalIF":0.0000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11770159/pdf/","citationCount":"0","resultStr":"{\"title\":\"Project ECHO Diabetes Trial Improves Outcomes for Medically Underserved People.\",\"authors\":\"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\",\"doi\":\"10.2337/dc24-2100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>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.</p><p><strong>Research design and methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>The ECHO model demonstrates promise for reducing health disparities in diabetes and contributes to our understanding of program benefits beyond the provider level.</p>\",\"PeriodicalId\":93979,\"journal\":{\"name\":\"Diabetes care\",\"volume\":\" \",\"pages\":\"243-250\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11770159/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Diabetes care\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2337/dc24-2100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes care","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2337/dc24-2100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.