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Mobile Diabetes Intervention Study of Patient Engagement and Impact on Blood Glucose: Mixed Methods Analysis

BACKGROUND: Successful treatment of diabetes includes patient self-management behaviors to prevent or delay complications and comorbid diseases. On the basis of findings from large clinical trials and professional guidelines, diabetes education programs and health providers prescribe daily regimens...

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Autores principales: Quinn, Charlene Connolly, Butler, Erin C, Swasey, Krystal K, Shardell, Michelle D, Terrin, Michael D, Barr, Erik A, Gruber-Baldini, Ann L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5816260/
https://www.ncbi.nlm.nih.gov/pubmed/29396389
http://dx.doi.org/10.2196/mhealth.9265
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author Quinn, Charlene Connolly
Butler, Erin C
Swasey, Krystal K
Shardell, Michelle D
Terrin, Michael D
Barr, Erik A
Gruber-Baldini, Ann L
author_facet Quinn, Charlene Connolly
Butler, Erin C
Swasey, Krystal K
Shardell, Michelle D
Terrin, Michael D
Barr, Erik A
Gruber-Baldini, Ann L
author_sort Quinn, Charlene Connolly
collection PubMed
description BACKGROUND: Successful treatment of diabetes includes patient self-management behaviors to prevent or delay complications and comorbid diseases. On the basis of findings from large clinical trials and professional guidelines, diabetes education programs and health providers prescribe daily regimens of glucose monitoring, healthy eating, stress management, medication adherence, and physical activity. Consistent, long-term commitment to regimens is challenging. Mobile health is increasingly being used to assist patients with lifestyle changes and self-management behaviors between provider visits. The effectiveness of mobile health to improve diabetes outcomes depends on patient engagement with a technology, content, or interactions with providers. OBJECTIVES: In the current analysis, we aimed to identify patient engagement themes in diabetes messaging with diabetes providers and determine if differences in engagement in the Mobile Diabetes Intervention Study (MDIS) influenced changes in glycated hemoglobin A(1c) (HbA(1c)) over a 1-year treatment period (1.9% absolute decrease in the parent study). METHODS: In the primary MDIS study, 163 patients were enrolled into 1 of 3 mobile intervention groups or a usual care control group based on their physician cluster randomization assignment. The control group received care from their physicians as usual. Participants in each intervention group had access to a patient portal where they could record monitoring values for blood glucose, blood pressure, medication changes, or other self-management information while also assigned to varying levels of physician access to patient data. Intervention participants could choose to send and receive messages to assigned certified diabetes educators with questions or updates through the secure Web portal. For this secondary analysis, patient engagement was measured using qualitative methods to identify self-care themes in 4109 patient messages. Mixed methods were used to determine the impact of patient engagement on change in HbA(1c) over 1 year. RESULTS: Self-care behavior themes that received the highest engagement for participants were glucose monitoring (75/107, 70.1%), medication management (71/107, 66.4%), and reducing risks (71/107, 66.4%). The average number of messages sent per patient were highest for glucose monitoring (9.2, SD 14.0) and healthy eating (6.9, SD 13.2). Compared to sending no messages, sending any messages about glucose monitoring (P=.03) or medication (P=.01) led to a decrease in HbA(1c) of 0.62 and 0.72 percentage points, respectively. Sending any messages about healthy eating, glucose monitoring, or medication combined led to a decrease in HbA(1c) of 0.54 percentage points compared to not sending messages in these themes (P=.045). CONCLUSIONS: The findings from this study help validate the efficacy of the mobile diabetes intervention. The next step is to determine differences between patients who engage in mobile interventions and those who do not engage and identify methods to enhance patient engagement. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01107015; https://clinicaltrials.gov/ct2/show/NCT01107015 (Archived by WebCite at http://www.webcitation.org/6wh4ekP4R)
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spelling pubmed-58162602018-02-23 Mobile Diabetes Intervention Study of Patient Engagement and Impact on Blood Glucose: Mixed Methods Analysis Quinn, Charlene Connolly Butler, Erin C Swasey, Krystal K Shardell, Michelle D Terrin, Michael D Barr, Erik A Gruber-Baldini, Ann L JMIR Mhealth Uhealth Original Paper BACKGROUND: Successful treatment of diabetes includes patient self-management behaviors to prevent or delay complications and comorbid diseases. On the basis of findings from large clinical trials and professional guidelines, diabetes education programs and health providers prescribe daily regimens of glucose monitoring, healthy eating, stress management, medication adherence, and physical activity. Consistent, long-term commitment to regimens is challenging. Mobile health is increasingly being used to assist patients with lifestyle changes and self-management behaviors between provider visits. The effectiveness of mobile health to improve diabetes outcomes depends on patient engagement with a technology, content, or interactions with providers. OBJECTIVES: In the current analysis, we aimed to identify patient engagement themes in diabetes messaging with diabetes providers and determine if differences in engagement in the Mobile Diabetes Intervention Study (MDIS) influenced changes in glycated hemoglobin A(1c) (HbA(1c)) over a 1-year treatment period (1.9% absolute decrease in the parent study). METHODS: In the primary MDIS study, 163 patients were enrolled into 1 of 3 mobile intervention groups or a usual care control group based on their physician cluster randomization assignment. The control group received care from their physicians as usual. Participants in each intervention group had access to a patient portal where they could record monitoring values for blood glucose, blood pressure, medication changes, or other self-management information while also assigned to varying levels of physician access to patient data. Intervention participants could choose to send and receive messages to assigned certified diabetes educators with questions or updates through the secure Web portal. For this secondary analysis, patient engagement was measured using qualitative methods to identify self-care themes in 4109 patient messages. Mixed methods were used to determine the impact of patient engagement on change in HbA(1c) over 1 year. RESULTS: Self-care behavior themes that received the highest engagement for participants were glucose monitoring (75/107, 70.1%), medication management (71/107, 66.4%), and reducing risks (71/107, 66.4%). The average number of messages sent per patient were highest for glucose monitoring (9.2, SD 14.0) and healthy eating (6.9, SD 13.2). Compared to sending no messages, sending any messages about glucose monitoring (P=.03) or medication (P=.01) led to a decrease in HbA(1c) of 0.62 and 0.72 percentage points, respectively. Sending any messages about healthy eating, glucose monitoring, or medication combined led to a decrease in HbA(1c) of 0.54 percentage points compared to not sending messages in these themes (P=.045). CONCLUSIONS: The findings from this study help validate the efficacy of the mobile diabetes intervention. The next step is to determine differences between patients who engage in mobile interventions and those who do not engage and identify methods to enhance patient engagement. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01107015; https://clinicaltrials.gov/ct2/show/NCT01107015 (Archived by WebCite at http://www.webcitation.org/6wh4ekP4R) JMIR Publications 2018-02-02 /pmc/articles/PMC5816260/ /pubmed/29396389 http://dx.doi.org/10.2196/mhealth.9265 Text en ©Charlene Connolly Quinn, Erin C Butler, Krystal K Swasey, Michelle D Shardell, Michael D Terrin, Erik A Barr, Ann L Gruber-Baldini. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 02.02.2018. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Quinn, Charlene Connolly
Butler, Erin C
Swasey, Krystal K
Shardell, Michelle D
Terrin, Michael D
Barr, Erik A
Gruber-Baldini, Ann L
Mobile Diabetes Intervention Study of Patient Engagement and Impact on Blood Glucose: Mixed Methods Analysis
title Mobile Diabetes Intervention Study of Patient Engagement and Impact on Blood Glucose: Mixed Methods Analysis
title_full Mobile Diabetes Intervention Study of Patient Engagement and Impact on Blood Glucose: Mixed Methods Analysis
title_fullStr Mobile Diabetes Intervention Study of Patient Engagement and Impact on Blood Glucose: Mixed Methods Analysis
title_full_unstemmed Mobile Diabetes Intervention Study of Patient Engagement and Impact on Blood Glucose: Mixed Methods Analysis
title_short Mobile Diabetes Intervention Study of Patient Engagement and Impact on Blood Glucose: Mixed Methods Analysis
title_sort mobile diabetes intervention study of patient engagement and impact on blood glucose: mixed methods analysis
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5816260/
https://www.ncbi.nlm.nih.gov/pubmed/29396389
http://dx.doi.org/10.2196/mhealth.9265
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