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TeDia - A Telemedicine-Based Treatment Model for Inpatient and Interprofessional Diabetes Care

INTRODUCTION: The proportion of hospitalized patients with diabetes as a secondary diagnosis increases continuously. Therefore, we have developed a team-based interprofessional and telemedicine-based diabetes management system named TeDia (“Telemedical Diabetology”) and implemented it in an inpatien...

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Autores principales: Röhling, Martin, Redaélli, Marcus, Simic, Dusan, Lorrek, Kristina, Samel, Christina, Schneider, Paul, Kempf, Kerstin, Stock, Stephanie, Martin, Stephan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6890178/
https://www.ncbi.nlm.nih.gov/pubmed/31819573
http://dx.doi.org/10.2147/DMSO.S229933
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author Röhling, Martin
Redaélli, Marcus
Simic, Dusan
Lorrek, Kristina
Samel, Christina
Schneider, Paul
Kempf, Kerstin
Stock, Stephanie
Martin, Stephan
author_facet Röhling, Martin
Redaélli, Marcus
Simic, Dusan
Lorrek, Kristina
Samel, Christina
Schneider, Paul
Kempf, Kerstin
Stock, Stephanie
Martin, Stephan
author_sort Röhling, Martin
collection PubMed
description INTRODUCTION: The proportion of hospitalized patients with diabetes as a secondary diagnosis increases continuously. Therefore, we have developed a team-based interprofessional and telemedicine-based diabetes management system named TeDia (“Telemedical Diabetology”) and implemented it in an inpatient setting. The aim of the retrospective real-world study was to show the clinical impact of TeDia following its implementation. MATERIAL AND METHODS: TeDia is characterized by an interpersonal and telemedicine-based exchange of hospital routine data between specially trained nurses (“diabetes managers”) and external diabetologists. It was implemented in three acute hospitals of the Düsseldorf Catholic Hospital Group in Düsseldorf, Germany. Clinical awareness of diabetes, diabetes-related complications and diagnosis-related group (DRG)-based revenues were analyzed using ICD routine coding. Furthermore, the frequency of HbA1c determinations as well as hospitalization days were investigated. RESULTS: Before (2010), during (2012) and after the implementation of TeDia (2014), the number of patients with ICD coding for diabetes, decompensated diabetes, diabetic neuropathy, diabetic nephropathy as well as complicated diabetes increased by +18%, +93%, +101%, +113% and +89%, respectively. Using the same DRG grouper, revenues increased by +53% (from 27 (2013) to 42 (2014) DRG points). Frequency of HbA1c determinations rose by +85%, whereas the time for an average length of stay decreased by −12% (−0, 91 days) in comparison to patients without diabetes. CONCLUSION: TeDia improved clinical awareness for diabetes and its complications. This new treatment model increased revenues and reduced hospital days indicating enhanced treatment quality. Our findings emphasize the necessity of novel technologies in inpatient settings for the improvement of efficacy, safety and efficiency of diabetes care.
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spelling pubmed-68901782019-12-09 TeDia - A Telemedicine-Based Treatment Model for Inpatient and Interprofessional Diabetes Care Röhling, Martin Redaélli, Marcus Simic, Dusan Lorrek, Kristina Samel, Christina Schneider, Paul Kempf, Kerstin Stock, Stephanie Martin, Stephan Diabetes Metab Syndr Obes Original Research INTRODUCTION: The proportion of hospitalized patients with diabetes as a secondary diagnosis increases continuously. Therefore, we have developed a team-based interprofessional and telemedicine-based diabetes management system named TeDia (“Telemedical Diabetology”) and implemented it in an inpatient setting. The aim of the retrospective real-world study was to show the clinical impact of TeDia following its implementation. MATERIAL AND METHODS: TeDia is characterized by an interpersonal and telemedicine-based exchange of hospital routine data between specially trained nurses (“diabetes managers”) and external diabetologists. It was implemented in three acute hospitals of the Düsseldorf Catholic Hospital Group in Düsseldorf, Germany. Clinical awareness of diabetes, diabetes-related complications and diagnosis-related group (DRG)-based revenues were analyzed using ICD routine coding. Furthermore, the frequency of HbA1c determinations as well as hospitalization days were investigated. RESULTS: Before (2010), during (2012) and after the implementation of TeDia (2014), the number of patients with ICD coding for diabetes, decompensated diabetes, diabetic neuropathy, diabetic nephropathy as well as complicated diabetes increased by +18%, +93%, +101%, +113% and +89%, respectively. Using the same DRG grouper, revenues increased by +53% (from 27 (2013) to 42 (2014) DRG points). Frequency of HbA1c determinations rose by +85%, whereas the time for an average length of stay decreased by −12% (−0, 91 days) in comparison to patients without diabetes. CONCLUSION: TeDia improved clinical awareness for diabetes and its complications. This new treatment model increased revenues and reduced hospital days indicating enhanced treatment quality. Our findings emphasize the necessity of novel technologies in inpatient settings for the improvement of efficacy, safety and efficiency of diabetes care. Dove 2019-11-29 /pmc/articles/PMC6890178/ /pubmed/31819573 http://dx.doi.org/10.2147/DMSO.S229933 Text en © 2019 Röhling et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Röhling, Martin
Redaélli, Marcus
Simic, Dusan
Lorrek, Kristina
Samel, Christina
Schneider, Paul
Kempf, Kerstin
Stock, Stephanie
Martin, Stephan
TeDia - A Telemedicine-Based Treatment Model for Inpatient and Interprofessional Diabetes Care
title TeDia - A Telemedicine-Based Treatment Model for Inpatient and Interprofessional Diabetes Care
title_full TeDia - A Telemedicine-Based Treatment Model for Inpatient and Interprofessional Diabetes Care
title_fullStr TeDia - A Telemedicine-Based Treatment Model for Inpatient and Interprofessional Diabetes Care
title_full_unstemmed TeDia - A Telemedicine-Based Treatment Model for Inpatient and Interprofessional Diabetes Care
title_short TeDia - A Telemedicine-Based Treatment Model for Inpatient and Interprofessional Diabetes Care
title_sort tedia - a telemedicine-based treatment model for inpatient and interprofessional diabetes care
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6890178/
https://www.ncbi.nlm.nih.gov/pubmed/31819573
http://dx.doi.org/10.2147/DMSO.S229933
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