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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2019
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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. |
format | Online Article Text |
id | pubmed-6890178 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Dove |
record_format | MEDLINE/PubMed |
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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