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SAT135 Prospective Analysis For Improvement For Glycemic Control Using A Patient Portal And Automated Messages

Disclosure: C.C. Cristancho: None. M. Brandao: None. A. Lema Morocho: None. T. Amorim: None. Background: Type II diabetes is a complex metabolic disorder which is influenced in part by patient dietary choices, medication adherence, and environmental factors. Behavioral health interventions offer an...

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Autores principales: Cristancho, Cagney C, Brandao, Marjorie, Morocho, Alexandra Lema, Amorim, Talmas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10555428/
http://dx.doi.org/10.1210/jendso/bvad114.1000
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author Cristancho, Cagney C
Brandao, Marjorie
Morocho, Alexandra Lema
Amorim, Talmas
author_facet Cristancho, Cagney C
Brandao, Marjorie
Morocho, Alexandra Lema
Amorim, Talmas
author_sort Cristancho, Cagney C
collection PubMed
description Disclosure: C.C. Cristancho: None. M. Brandao: None. A. Lema Morocho: None. T. Amorim: None. Background: Type II diabetes is a complex metabolic disorder which is influenced in part by patient dietary choices, medication adherence, and environmental factors. Behavioral health interventions offer an opportunity to potentially affect patient outcomes in a cost-effective manner. Purpose: To study whether automated clinical messaging via the electronic medical chart would be associated with improvement in diabetes-related health measures. Methods: We created an automated clinical messaging system (January 2020) via our electronic medical record. Patients who opted-in for this service received bi-weekly messages which included reminders about diabetes medication adherence as well as exercise and dietary recommendations. We then performed a retrospective longitudinal analysis of patients followed in our diabetes clinic, comparing those who opted-in for messing vs those who did not, and assessed diabetes-related biomarkers including baseline and follow-up hemoglobin A1c, lipid markers, and BMI using linear mixed-effects regression models. Results: 69 patients who had at least 2 measures of hemoglobin A1c were followed longitudinally, of whom 37 (54%) had opted to receive automated messaging. Patients who opted-in were younger (53±12 vs 62±11 years old, p<0.1), but not different in terms of sex (60% F vs 61% F), BMI (31±6 vs 30±7, p=0.84), or A1c (9.4±2.3 vs 8.8±2.7, p=0.34). In the group that received messages, we did not find any significant pre-post differences in A1c, LDL, or BMI over time. In the opt-in group, mean change (over average follow-up of 256 days) in HgbA1c was -0.4 (p=0.42) compared to a change of 0.0 in the non-opt-in group (p=0.99). Discussion: Patients who opted-in to electronic messaging were younger on average. We did not observe any significant longitudinal change in diabetes-related biomarkers within or between groups as related to an automated clinical messaging service, although there was a directional trend toward improvement. Given the cost-effectiveness and ease of this program, consideration should be given toward a trial with a larger sample size and longer follow-up. Presentation: Saturday, June 17, 2023
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spelling pubmed-105554282023-10-06 SAT135 Prospective Analysis For Improvement For Glycemic Control Using A Patient Portal And Automated Messages Cristancho, Cagney C Brandao, Marjorie Morocho, Alexandra Lema Amorim, Talmas J Endocr Soc Diabetes And Glucose Metabolism Disclosure: C.C. Cristancho: None. M. Brandao: None. A. Lema Morocho: None. T. Amorim: None. Background: Type II diabetes is a complex metabolic disorder which is influenced in part by patient dietary choices, medication adherence, and environmental factors. Behavioral health interventions offer an opportunity to potentially affect patient outcomes in a cost-effective manner. Purpose: To study whether automated clinical messaging via the electronic medical chart would be associated with improvement in diabetes-related health measures. Methods: We created an automated clinical messaging system (January 2020) via our electronic medical record. Patients who opted-in for this service received bi-weekly messages which included reminders about diabetes medication adherence as well as exercise and dietary recommendations. We then performed a retrospective longitudinal analysis of patients followed in our diabetes clinic, comparing those who opted-in for messing vs those who did not, and assessed diabetes-related biomarkers including baseline and follow-up hemoglobin A1c, lipid markers, and BMI using linear mixed-effects regression models. Results: 69 patients who had at least 2 measures of hemoglobin A1c were followed longitudinally, of whom 37 (54%) had opted to receive automated messaging. Patients who opted-in were younger (53±12 vs 62±11 years old, p<0.1), but not different in terms of sex (60% F vs 61% F), BMI (31±6 vs 30±7, p=0.84), or A1c (9.4±2.3 vs 8.8±2.7, p=0.34). In the group that received messages, we did not find any significant pre-post differences in A1c, LDL, or BMI over time. In the opt-in group, mean change (over average follow-up of 256 days) in HgbA1c was -0.4 (p=0.42) compared to a change of 0.0 in the non-opt-in group (p=0.99). Discussion: Patients who opted-in to electronic messaging were younger on average. We did not observe any significant longitudinal change in diabetes-related biomarkers within or between groups as related to an automated clinical messaging service, although there was a directional trend toward improvement. Given the cost-effectiveness and ease of this program, consideration should be given toward a trial with a larger sample size and longer follow-up. Presentation: Saturday, June 17, 2023 Oxford University Press 2023-10-05 /pmc/articles/PMC10555428/ http://dx.doi.org/10.1210/jendso/bvad114.1000 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the Endocrine Society. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Diabetes And Glucose Metabolism
Cristancho, Cagney C
Brandao, Marjorie
Morocho, Alexandra Lema
Amorim, Talmas
SAT135 Prospective Analysis For Improvement For Glycemic Control Using A Patient Portal And Automated Messages
title SAT135 Prospective Analysis For Improvement For Glycemic Control Using A Patient Portal And Automated Messages
title_full SAT135 Prospective Analysis For Improvement For Glycemic Control Using A Patient Portal And Automated Messages
title_fullStr SAT135 Prospective Analysis For Improvement For Glycemic Control Using A Patient Portal And Automated Messages
title_full_unstemmed SAT135 Prospective Analysis For Improvement For Glycemic Control Using A Patient Portal And Automated Messages
title_short SAT135 Prospective Analysis For Improvement For Glycemic Control Using A Patient Portal And Automated Messages
title_sort sat135 prospective analysis for improvement for glycemic control using a patient portal and automated messages
topic Diabetes And Glucose Metabolism
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10555428/
http://dx.doi.org/10.1210/jendso/bvad114.1000
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