Evidence map›Paper›PMID 31819573›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2019

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

Martin Röhling, Marcus Redaélli, Dusan Simic, Kristina Lorrek, Christina Samel, Paul Schneider, Kerstin Kempf, Stephanie Stock, Stephan Martin

Open access · goldAbstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Martin Röhling *West-German Center of Diabetes and Health, Düsseldorf Catholic Hospital Group, Düsseldorf, Germany.ORCID 0000-0002-2258-0582
Marcus Redaélli *Institute of Health Economics and Clinical Epidemiology, University Hospital of Cologne, Cologne, Germany.
Dusan SimicInstitute of Health Economics and Clinical Epidemiology, University Hospital of Cologne, Cologne, Germany.
Kristina LorrekInstitute of Health Economics and Clinical Epidemiology, University Hospital of Cologne, Cologne, Germany.
Christina SamelInstitute of Medical Statistics and Computational Biology, Faculty of Medicine, University of Cologne, Cologne, Germany.
Paul SchneiderDüsseldorf Catholic Hospital Group, Düsseldorf, Germany.
Kerstin KempfWest-German Center of Diabetes and Health, Düsseldorf Catholic Hospital Group, Düsseldorf, Germany.ORCID 0000-0003-4285-3127
Stephanie StockInstitute of Health Economics and Clinical Epidemiology, University Hospital of Cologne, Cologne, Germany.
Stephan MartinWest-German Center of Diabetes and Health, Düsseldorf Catholic Hospital Group, Düsseldorf, Germany.
University Hospital Cologne · DEDeutsches Diabetes-Zentrum e.V. · DEUniversity of Cologne · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe 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

methodsTeDia 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.

resultsBefore (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.

conclusionTeDia 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.

Indexed as

diabetesinpatient caretelemedicine

Identifiers

PMID31819573
PMCPMC6890178
OpenAlexW2990292679

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.