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Remote glucose monitoring is feasible for patients and providers using a commercially available population health platform
OBJECTIVE: Remote patient monitoring (RPM) holds potential to enable more individualized and effective care for patients with type 1 diabetes (T1D), but requires population analytics to focus limited clinical resources on patients most in need. We explored the feasibility of RPM from patient and pro...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931729/ https://www.ncbi.nlm.nih.gov/pubmed/36817610 http://dx.doi.org/10.3389/fendo.2023.1063290 |
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author | Crossen, Stephanie S. Romero, Crystal C. Lewis, Carrie Glaser, Nicole S. |
author_facet | Crossen, Stephanie S. Romero, Crystal C. Lewis, Carrie Glaser, Nicole S. |
author_sort | Crossen, Stephanie S. |
collection | PubMed |
description | OBJECTIVE: Remote patient monitoring (RPM) holds potential to enable more individualized and effective care for patients with type 1 diabetes (T1D), but requires population analytics to focus limited clinical resources on patients most in need. We explored the feasibility of RPM from patient and provider standpoints using a commercially available data analytic platform (glooko Population Health) among a cohort of youth with T1D. STUDY DESIGN: Patients aged 1-20 years with established T1D (≥12 months) and CGM use (≥3 months) were recruited to participate. Participants’ CGM devices were connected to the glooko app and linked to the research team’s glooko account during a one-month baseline period. This was followed by a six-month intervention period during which participants with >15% of glucose values >250 mg/dl or >5% of values <70 mg/dl each month were contacted with personalized diabetes management recommendations. Participants were surveyed about their experiences, and effects on glycemic control were estimated via change in glucose management indicator (GMI) generated from CGM data at baseline and completion. Changes in time spent within various glucose ranges were also evaluated, and all glycemic metrics were compared to a non-randomized control group via difference-in-difference regression, adjusting for baseline characteristics. RESULTS: Remote data-sharing was successful for 36 of 39 participants (92%). Between 33%-66% of participants merited outreach each month, and clinician outreach required a median of 10 minutes per event. RPM was reported to be helpful by 94% of participants. RPM was associated with a GMI change of -0.25% (P=0.047) for the entire cohort, and stratified analysis revealed greatest treatment effects among participants with baseline GMI of 8.0-9.4% (GMI change of -0.68%, P=0.047; 19.84% reduction in time spent >250 mg/dl, P=0.005). CONCLUSIONS: This study demonstrates the feasibility of RPM for patients with T1D using a commercially available population health platform, and suggests that RPM with clinician-initiated outreach may be particularly beneficial for patients with suboptimal glycemic control at entry. However, larger randomized studies are needed to fully explore the glycemic impact of RPM. CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT04696640, identifier NCT04696640. |
format | Online Article Text |
id | pubmed-9931729 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99317292023-02-17 Remote glucose monitoring is feasible for patients and providers using a commercially available population health platform Crossen, Stephanie S. Romero, Crystal C. Lewis, Carrie Glaser, Nicole S. Front Endocrinol (Lausanne) Endocrinology OBJECTIVE: Remote patient monitoring (RPM) holds potential to enable more individualized and effective care for patients with type 1 diabetes (T1D), but requires population analytics to focus limited clinical resources on patients most in need. We explored the feasibility of RPM from patient and provider standpoints using a commercially available data analytic platform (glooko Population Health) among a cohort of youth with T1D. STUDY DESIGN: Patients aged 1-20 years with established T1D (≥12 months) and CGM use (≥3 months) were recruited to participate. Participants’ CGM devices were connected to the glooko app and linked to the research team’s glooko account during a one-month baseline period. This was followed by a six-month intervention period during which participants with >15% of glucose values >250 mg/dl or >5% of values <70 mg/dl each month were contacted with personalized diabetes management recommendations. Participants were surveyed about their experiences, and effects on glycemic control were estimated via change in glucose management indicator (GMI) generated from CGM data at baseline and completion. Changes in time spent within various glucose ranges were also evaluated, and all glycemic metrics were compared to a non-randomized control group via difference-in-difference regression, adjusting for baseline characteristics. RESULTS: Remote data-sharing was successful for 36 of 39 participants (92%). Between 33%-66% of participants merited outreach each month, and clinician outreach required a median of 10 minutes per event. RPM was reported to be helpful by 94% of participants. RPM was associated with a GMI change of -0.25% (P=0.047) for the entire cohort, and stratified analysis revealed greatest treatment effects among participants with baseline GMI of 8.0-9.4% (GMI change of -0.68%, P=0.047; 19.84% reduction in time spent >250 mg/dl, P=0.005). CONCLUSIONS: This study demonstrates the feasibility of RPM for patients with T1D using a commercially available population health platform, and suggests that RPM with clinician-initiated outreach may be particularly beneficial for patients with suboptimal glycemic control at entry. However, larger randomized studies are needed to fully explore the glycemic impact of RPM. CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT04696640, identifier NCT04696640. Frontiers Media S.A. 2023-02-02 /pmc/articles/PMC9931729/ /pubmed/36817610 http://dx.doi.org/10.3389/fendo.2023.1063290 Text en Copyright © 2023 Crossen, Romero, Lewis and Glaser https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Crossen, Stephanie S. Romero, Crystal C. Lewis, Carrie Glaser, Nicole S. Remote glucose monitoring is feasible for patients and providers using a commercially available population health platform |
title | Remote glucose monitoring is feasible for patients and providers using a commercially available population health platform |
title_full | Remote glucose monitoring is feasible for patients and providers using a commercially available population health platform |
title_fullStr | Remote glucose monitoring is feasible for patients and providers using a commercially available population health platform |
title_full_unstemmed | Remote glucose monitoring is feasible for patients and providers using a commercially available population health platform |
title_short | Remote glucose monitoring is feasible for patients and providers using a commercially available population health platform |
title_sort | remote glucose monitoring is feasible for patients and providers using a commercially available population health platform |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931729/ https://www.ncbi.nlm.nih.gov/pubmed/36817610 http://dx.doi.org/10.3389/fendo.2023.1063290 |
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