{"title":"在农村糖尿病自我管理教育和支持计划中采用耗时最少的方法进行定期、持续的成果评估:通过事后回顾性研究进行验证。","authors":"Xin Zhang, Tiaha E McGettigan","doi":"10.1177/26350106251315675","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>The purpose of this study was to introduce and validate a minimally time-consuming method for regular, ongoing assessments of practice- and individual-level outcomes in a rural diabetes self-management education and support (DSMES) program.</p><p><strong>Methods: </strong>The method involves a report developed within an electronic health record system to capture the initial A1C data of patients in the program and their most recent A1C data at the time the report is run. To validate the method's ability to continuously assess outcomes, 3 retrospective pre-post studies were conducted over 3 consecutive months: October, November, and December 2023. The subjects were individuals with type 2 or type 1 diabetes who completed their initial visits in the program during these months. A1C changes in patient cohorts and their statistical significance were analyzed as practice-level outcomes, and individual-level outcomes were monitored by plotting and analyzing patient data.</p><p><strong>Results: </strong>The report accurately captured data, enabling minimally time-consuming analyses. The method allowed both continuous assessment of program effectiveness based on A1C changes and monitoring of individual patient progress. Statistically significant reductions in average A1C were observed for subjects seen in October and December 2023 (but not in November) and across the combined data from all 3 months. Data plotting helped identify individual subjects who may benefit from follow-up.</p><p><strong>Conclusions: </strong>The method is feasible and accurate for ongoing outcome assessments, providing timely feedback to clinicians and promoting practice changes to improve patient outcomes. It is also flexible and adaptable to other DSMES programs.</p>","PeriodicalId":75187,"journal":{"name":"The science of diabetes self-management and care","volume":" ","pages":"26350106251315675"},"PeriodicalIF":0.0000,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Minimally Time-Consuming Method for Regular, Ongoing Outcome Assessments in a Rural Diabetes Self-Management Education and Support Program: Validation via Retrospective Pre-Post Studies.\",\"authors\":\"Xin Zhang, Tiaha E McGettigan\",\"doi\":\"10.1177/26350106251315675\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>The purpose of this study was to introduce and validate a minimally time-consuming method for regular, ongoing assessments of practice- and individual-level outcomes in a rural diabetes self-management education and support (DSMES) program.</p><p><strong>Methods: </strong>The method involves a report developed within an electronic health record system to capture the initial A1C data of patients in the program and their most recent A1C data at the time the report is run. To validate the method's ability to continuously assess outcomes, 3 retrospective pre-post studies were conducted over 3 consecutive months: October, November, and December 2023. The subjects were individuals with type 2 or type 1 diabetes who completed their initial visits in the program during these months. A1C changes in patient cohorts and their statistical significance were analyzed as practice-level outcomes, and individual-level outcomes were monitored by plotting and analyzing patient data.</p><p><strong>Results: </strong>The report accurately captured data, enabling minimally time-consuming analyses. The method allowed both continuous assessment of program effectiveness based on A1C changes and monitoring of individual patient progress. Statistically significant reductions in average A1C were observed for subjects seen in October and December 2023 (but not in November) and across the combined data from all 3 months. Data plotting helped identify individual subjects who may benefit from follow-up.</p><p><strong>Conclusions: </strong>The method is feasible and accurate for ongoing outcome assessments, providing timely feedback to clinicians and promoting practice changes to improve patient outcomes. It is also flexible and adaptable to other DSMES programs.</p>\",\"PeriodicalId\":75187,\"journal\":{\"name\":\"The science of diabetes self-management and care\",\"volume\":\" \",\"pages\":\"26350106251315675\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-02-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The science of diabetes self-management and care\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/26350106251315675\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The science of diabetes self-management and care","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/26350106251315675","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Minimally Time-Consuming Method for Regular, Ongoing Outcome Assessments in a Rural Diabetes Self-Management Education and Support Program: Validation via Retrospective Pre-Post Studies.
Purpose: The purpose of this study was to introduce and validate a minimally time-consuming method for regular, ongoing assessments of practice- and individual-level outcomes in a rural diabetes self-management education and support (DSMES) program.
Methods: The method involves a report developed within an electronic health record system to capture the initial A1C data of patients in the program and their most recent A1C data at the time the report is run. To validate the method's ability to continuously assess outcomes, 3 retrospective pre-post studies were conducted over 3 consecutive months: October, November, and December 2023. The subjects were individuals with type 2 or type 1 diabetes who completed their initial visits in the program during these months. A1C changes in patient cohorts and their statistical significance were analyzed as practice-level outcomes, and individual-level outcomes were monitored by plotting and analyzing patient data.
Results: The report accurately captured data, enabling minimally time-consuming analyses. The method allowed both continuous assessment of program effectiveness based on A1C changes and monitoring of individual patient progress. Statistically significant reductions in average A1C were observed for subjects seen in October and December 2023 (but not in November) and across the combined data from all 3 months. Data plotting helped identify individual subjects who may benefit from follow-up.
Conclusions: The method is feasible and accurate for ongoing outcome assessments, providing timely feedback to clinicians and promoting practice changes to improve patient outcomes. It is also flexible and adaptable to other DSMES programs.