Opportunities of Digital Infrastructures for Disease Management—Exemplified on COVID-19-Related Change in Diagnosis Counts for Diabetes-Related Eye Diseases
<b>Background:</b> Retrospective research on real-world data provides the ability to gain evidence on specific topics especially when running across different sites in research networks. Those research networks have become increasingly relevant in recent years; not least due to the speci...
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MDPI AG
2022-05-01
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Series: | Nutrients |
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Online Access: | https://www.mdpi.com/2072-6643/14/10/2016 |
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author | Franziska Bathelt Ines Reinecke Yuan Peng Elisa Henke Jens Weidner Martin Bartos Robert Gött Dagmar Waltemath Katrin Engelmann Peter EH Schwarz Martin Sedlmayr |
author_facet | Franziska Bathelt Ines Reinecke Yuan Peng Elisa Henke Jens Weidner Martin Bartos Robert Gött Dagmar Waltemath Katrin Engelmann Peter EH Schwarz Martin Sedlmayr |
author_sort | Franziska Bathelt |
collection | DOAJ |
description | <b>Background:</b> Retrospective research on real-world data provides the ability to gain evidence on specific topics especially when running across different sites in research networks. Those research networks have become increasingly relevant in recent years; not least due to the special situation caused by the COVID-19 pandemic. An important requirement for those networks is the data harmonization by ensuring the semantic interoperability. <b>Aims:</b> In this paper we demonstrate (1) how to facilitate digital infrastructures to run a retrospective study in a research network spread across university and non-university hospital sites; and (2) to answer a medical question on COVID-19 related change in diagnostic counts for diabetes-related eye diseases. <b>Materials and methods:</b> The study is retrospective and non-interventional and runs on medical case data documented in routine care at the participating sites. The technical infrastructure consists of the OMOP CDM and other OHDSI tools that is provided in a transferable format. An ETL process to transfer and harmonize the data to the OMOP CDM has been utilized. Cohort definitions for each year in observation have been created centrally and applied locally against medical case data of all participating sites and analyzed with descriptive statistics. <b>Results:</b> The analyses showed an expectable drop of the total number of diagnoses and the diagnoses for diabetes in general; whereas the number of diagnoses for diabetes-related eye diseases surprisingly decreased stronger compared to non-eye diseases. Differences in relative changes of diagnoses counts between sites show an urgent need to process multi-centric studies rather than single-site studies to reduce bias in the data. <b>Conclusions:</b> This study has demonstrated the ability to utilize an existing portable and standardized infrastructure and ETL process from a university hospital setting and transfer it to non-university sites. From a medical perspective further activity is needed to evaluate data quality of the utilized real-world data documented in routine care and to investigate its eligibility of this data for research. |
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institution | Directory Open Access Journal |
issn | 2072-6643 |
language | English |
last_indexed | 2024-03-10T03:15:29Z |
publishDate | 2022-05-01 |
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series | Nutrients |
spelling | doaj.art-8a9393f10f1146609cbc744863f0d3f52023-11-23T12:28:41ZengMDPI AGNutrients2072-66432022-05-011410201610.3390/nu14102016Opportunities of Digital Infrastructures for Disease Management—Exemplified on COVID-19-Related Change in Diagnosis Counts for Diabetes-Related Eye DiseasesFranziska Bathelt0Ines Reinecke1Yuan Peng2Elisa Henke3Jens Weidner4Martin Bartos5Robert Gött6Dagmar Waltemath7Katrin Engelmann8Peter EH Schwarz9Martin Sedlmayr10Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, 01307 Dresden, GermanyInstitute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, 01307 Dresden, GermanyInstitute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, 01307 Dresden, GermanyInstitute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, 01307 Dresden, GermanyInstitute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, 01307 Dresden, GermanyDepartment of Computer Science, Klinikum Chemnitz gGmbH, Flemmingstr. 2, 09116 Chemnitz, GermanyCore Unit Datenintegrationszentrum, Universitätsmedizin Greifswald, Walther-Rathenau-Str. 48, 17475 Greifswald, GermanyCore Unit Datenintegrationszentrum, Universitätsmedizin Greifswald, Walther-Rathenau-Str. 48, 17475 Greifswald, GermanyDepartment of Ophthalmology, Klinikum Chemnitz gGmbH, Flemmingstr. 2, 09116 Chemnitz, GermanyDepartment of Medicine, University of Dresden, Carl Gustav Carus, 01307 Dresden, GermanyInstitute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, 01307 Dresden, Germany<b>Background:</b> Retrospective research on real-world data provides the ability to gain evidence on specific topics especially when running across different sites in research networks. Those research networks have become increasingly relevant in recent years; not least due to the special situation caused by the COVID-19 pandemic. An important requirement for those networks is the data harmonization by ensuring the semantic interoperability. <b>Aims:</b> In this paper we demonstrate (1) how to facilitate digital infrastructures to run a retrospective study in a research network spread across university and non-university hospital sites; and (2) to answer a medical question on COVID-19 related change in diagnostic counts for diabetes-related eye diseases. <b>Materials and methods:</b> The study is retrospective and non-interventional and runs on medical case data documented in routine care at the participating sites. The technical infrastructure consists of the OMOP CDM and other OHDSI tools that is provided in a transferable format. An ETL process to transfer and harmonize the data to the OMOP CDM has been utilized. Cohort definitions for each year in observation have been created centrally and applied locally against medical case data of all participating sites and analyzed with descriptive statistics. <b>Results:</b> The analyses showed an expectable drop of the total number of diagnoses and the diagnoses for diabetes in general; whereas the number of diagnoses for diabetes-related eye diseases surprisingly decreased stronger compared to non-eye diseases. Differences in relative changes of diagnoses counts between sites show an urgent need to process multi-centric studies rather than single-site studies to reduce bias in the data. <b>Conclusions:</b> This study has demonstrated the ability to utilize an existing portable and standardized infrastructure and ETL process from a university hospital setting and transfer it to non-university sites. From a medical perspective further activity is needed to evaluate data quality of the utilized real-world data documented in routine care and to investigate its eligibility of this data for research.https://www.mdpi.com/2072-6643/14/10/2016diabeteseye-diseaseOMOPCOVID |
spellingShingle | Franziska Bathelt Ines Reinecke Yuan Peng Elisa Henke Jens Weidner Martin Bartos Robert Gött Dagmar Waltemath Katrin Engelmann Peter EH Schwarz Martin Sedlmayr Opportunities of Digital Infrastructures for Disease Management—Exemplified on COVID-19-Related Change in Diagnosis Counts for Diabetes-Related Eye Diseases Nutrients diabetes eye-disease OMOP COVID |
title | Opportunities of Digital Infrastructures for Disease Management—Exemplified on COVID-19-Related Change in Diagnosis Counts for Diabetes-Related Eye Diseases |
title_full | Opportunities of Digital Infrastructures for Disease Management—Exemplified on COVID-19-Related Change in Diagnosis Counts for Diabetes-Related Eye Diseases |
title_fullStr | Opportunities of Digital Infrastructures for Disease Management—Exemplified on COVID-19-Related Change in Diagnosis Counts for Diabetes-Related Eye Diseases |
title_full_unstemmed | Opportunities of Digital Infrastructures for Disease Management—Exemplified on COVID-19-Related Change in Diagnosis Counts for Diabetes-Related Eye Diseases |
title_short | Opportunities of Digital Infrastructures for Disease Management—Exemplified on COVID-19-Related Change in Diagnosis Counts for Diabetes-Related Eye Diseases |
title_sort | opportunities of digital infrastructures for disease management exemplified on covid 19 related change in diagnosis counts for diabetes related eye diseases |
topic | diabetes eye-disease OMOP COVID |
url | https://www.mdpi.com/2072-6643/14/10/2016 |
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