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Association of technologically assisted integrated care with clinical outcomes in type 2 diabetes in Hong Kong using the prospective JADE Program: A retrospective cohort analysis
BACKGROUND: Diabetes outcomes are influenced by host factors, settings, and care processes. We examined the association of data-driven integrated care assisted by information and communications technology (ICT) with clinical outcomes in type 2 diabetes in public and private healthcare settings. METH...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7531841/ https://www.ncbi.nlm.nih.gov/pubmed/33007052 http://dx.doi.org/10.1371/journal.pmed.1003367 |
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author | Lim, Lee-Ling Lau, Eric S. H. Ozaki, Risa Chung, Harriet Fu, Amy W. C. Chan, Wendy Kong, Alice P. S. Ma, Ronald C. W. So, Wing-Yee Chow, Elaine Cheung, Kitty K. T. Yau, Tiffany Chow, C. C. Lau, Vanessa Yue, Rebecca Ng, Shek Zee, Benny Goggins, William Oldenburg, Brian Clarke, Philip M. Lau, Maggie Wong, Rebecca Tsang, C. C. Gregg, Edward W. Wu, Hongjiang Tong, Peter C. Y. Ko, Gary T. C. Luk, Andrea O. Y. Chan, Juliana C. N. |
author_facet | Lim, Lee-Ling Lau, Eric S. H. Ozaki, Risa Chung, Harriet Fu, Amy W. C. Chan, Wendy Kong, Alice P. S. Ma, Ronald C. W. So, Wing-Yee Chow, Elaine Cheung, Kitty K. T. Yau, Tiffany Chow, C. C. Lau, Vanessa Yue, Rebecca Ng, Shek Zee, Benny Goggins, William Oldenburg, Brian Clarke, Philip M. Lau, Maggie Wong, Rebecca Tsang, C. C. Gregg, Edward W. Wu, Hongjiang Tong, Peter C. Y. Ko, Gary T. C. Luk, Andrea O. Y. Chan, Juliana C. N. |
author_sort | Lim, Lee-Ling |
collection | PubMed |
description | BACKGROUND: Diabetes outcomes are influenced by host factors, settings, and care processes. We examined the association of data-driven integrated care assisted by information and communications technology (ICT) with clinical outcomes in type 2 diabetes in public and private healthcare settings. METHODS AND FINDINGS: The web-based Joint Asia Diabetes Evaluation (JADE) platform provides a protocol to guide data collection for issuing a personalized JADE report including risk categories (1–4, low–high), 5-year probabilities of cardiovascular-renal events, and trends and targets of 4 risk factors with tailored decision support. The JADE program is a prospective cohort study implemented in a naturalistic environment where patients underwent nurse-led structured evaluation (blood/urine/eye/feet) in public and private outpatient clinics and diabetes centers in Hong Kong. We retrospectively analyzed the data of 16,624 Han Chinese patients with type 2 diabetes who were enrolled in 2007–2015. In the public setting, the non-JADE group (n = 3,587) underwent structured evaluation for risk factors and complications only, while the JADE (n = 9,601) group received a JADE report with group empowerment by nurses. In a community-based, nurse-led, university-affiliated diabetes center (UDC), the JADE-Personalized (JADE-P) group (n = 3,436) received a JADE report, personalized empowerment, and annual telephone reminder for reevaluation and engagement. The primary composite outcome was time to the first occurrence of cardiovascular-renal diseases, all-site cancer, and/or death, based on hospitalization data censored on 30 June 2017. During 94,311 person-years of follow-up in 2007–2017, 7,779 primary events occurred. Compared with the JADE group (136.22 cases per 1,000 patient-years [95% CI 132.35–140.18]), the non-JADE group had higher (145.32 [95% CI 138.68–152.20]; P = 0.020) while the JADE-P group had lower event rates (70.94 [95% CI 67.12–74.91]; P < 0.001). The adjusted hazard ratios (aHRs) for the primary composite outcome were 1.22 (95% CI 1.15–1.30) and 0.70 (95% CI 0.66–0.75), respectively, independent of risk profiles, education levels, drug usage, self-care, and comorbidities at baseline. We reported consistent results in propensity-score–matched analyses and after accounting for loss to follow-up. Potential limitations include its nonrandomized design that precludes causal inference, residual confounding, and participation bias. CONCLUSIONS: ICT-assisted integrated care was associated with a reduction in clinical events, including death in type 2 diabetes in public and private healthcare settings. |
format | Online Article Text |
id | pubmed-7531841 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-75318412020-10-08 Association of technologically assisted integrated care with clinical outcomes in type 2 diabetes in Hong Kong using the prospective JADE Program: A retrospective cohort analysis Lim, Lee-Ling Lau, Eric S. H. Ozaki, Risa Chung, Harriet Fu, Amy W. C. Chan, Wendy Kong, Alice P. S. Ma, Ronald C. W. So, Wing-Yee Chow, Elaine Cheung, Kitty K. T. Yau, Tiffany Chow, C. C. Lau, Vanessa Yue, Rebecca Ng, Shek Zee, Benny Goggins, William Oldenburg, Brian Clarke, Philip M. Lau, Maggie Wong, Rebecca Tsang, C. C. Gregg, Edward W. Wu, Hongjiang Tong, Peter C. Y. Ko, Gary T. C. Luk, Andrea O. Y. Chan, Juliana C. N. PLoS Med Research Article BACKGROUND: Diabetes outcomes are influenced by host factors, settings, and care processes. We examined the association of data-driven integrated care assisted by information and communications technology (ICT) with clinical outcomes in type 2 diabetes in public and private healthcare settings. METHODS AND FINDINGS: The web-based Joint Asia Diabetes Evaluation (JADE) platform provides a protocol to guide data collection for issuing a personalized JADE report including risk categories (1–4, low–high), 5-year probabilities of cardiovascular-renal events, and trends and targets of 4 risk factors with tailored decision support. The JADE program is a prospective cohort study implemented in a naturalistic environment where patients underwent nurse-led structured evaluation (blood/urine/eye/feet) in public and private outpatient clinics and diabetes centers in Hong Kong. We retrospectively analyzed the data of 16,624 Han Chinese patients with type 2 diabetes who were enrolled in 2007–2015. In the public setting, the non-JADE group (n = 3,587) underwent structured evaluation for risk factors and complications only, while the JADE (n = 9,601) group received a JADE report with group empowerment by nurses. In a community-based, nurse-led, university-affiliated diabetes center (UDC), the JADE-Personalized (JADE-P) group (n = 3,436) received a JADE report, personalized empowerment, and annual telephone reminder for reevaluation and engagement. The primary composite outcome was time to the first occurrence of cardiovascular-renal diseases, all-site cancer, and/or death, based on hospitalization data censored on 30 June 2017. During 94,311 person-years of follow-up in 2007–2017, 7,779 primary events occurred. Compared with the JADE group (136.22 cases per 1,000 patient-years [95% CI 132.35–140.18]), the non-JADE group had higher (145.32 [95% CI 138.68–152.20]; P = 0.020) while the JADE-P group had lower event rates (70.94 [95% CI 67.12–74.91]; P < 0.001). The adjusted hazard ratios (aHRs) for the primary composite outcome were 1.22 (95% CI 1.15–1.30) and 0.70 (95% CI 0.66–0.75), respectively, independent of risk profiles, education levels, drug usage, self-care, and comorbidities at baseline. We reported consistent results in propensity-score–matched analyses and after accounting for loss to follow-up. Potential limitations include its nonrandomized design that precludes causal inference, residual confounding, and participation bias. CONCLUSIONS: ICT-assisted integrated care was associated with a reduction in clinical events, including death in type 2 diabetes in public and private healthcare settings. Public Library of Science 2020-10-02 /pmc/articles/PMC7531841/ /pubmed/33007052 http://dx.doi.org/10.1371/journal.pmed.1003367 Text en © 2020 Lim et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Lim, Lee-Ling Lau, Eric S. H. Ozaki, Risa Chung, Harriet Fu, Amy W. C. Chan, Wendy Kong, Alice P. S. Ma, Ronald C. W. So, Wing-Yee Chow, Elaine Cheung, Kitty K. T. Yau, Tiffany Chow, C. C. Lau, Vanessa Yue, Rebecca Ng, Shek Zee, Benny Goggins, William Oldenburg, Brian Clarke, Philip M. Lau, Maggie Wong, Rebecca Tsang, C. C. Gregg, Edward W. Wu, Hongjiang Tong, Peter C. Y. Ko, Gary T. C. Luk, Andrea O. Y. Chan, Juliana C. N. Association of technologically assisted integrated care with clinical outcomes in type 2 diabetes in Hong Kong using the prospective JADE Program: A retrospective cohort analysis |
title | Association of technologically assisted integrated care with clinical outcomes in type 2 diabetes in Hong Kong using the prospective JADE Program: A retrospective cohort analysis |
title_full | Association of technologically assisted integrated care with clinical outcomes in type 2 diabetes in Hong Kong using the prospective JADE Program: A retrospective cohort analysis |
title_fullStr | Association of technologically assisted integrated care with clinical outcomes in type 2 diabetes in Hong Kong using the prospective JADE Program: A retrospective cohort analysis |
title_full_unstemmed | Association of technologically assisted integrated care with clinical outcomes in type 2 diabetes in Hong Kong using the prospective JADE Program: A retrospective cohort analysis |
title_short | Association of technologically assisted integrated care with clinical outcomes in type 2 diabetes in Hong Kong using the prospective JADE Program: A retrospective cohort analysis |
title_sort | association of technologically assisted integrated care with clinical outcomes in type 2 diabetes in hong kong using the prospective jade program: a retrospective cohort analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7531841/ https://www.ncbi.nlm.nih.gov/pubmed/33007052 http://dx.doi.org/10.1371/journal.pmed.1003367 |
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