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Structured, Harmonized, and Interoperable Integration of Clinical Routine Data to Compute Heart Failure Risk Scores

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Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Carl-Neuberg-Straße 1, 30625 Hannover, Germany
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Department of Internal Medicine III (Cardiology, Angiology, and Pneumology), University Hospital Heidelberg, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany
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German Center of Cardiovascular Research (DZHK), Partner Site Heidelberg/Mannheim, 69120 Heidelberg, Germany
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Department of Cardiology and Angiology, Hannover Medical School, Carl-Neuberg-Straße, 130625 Hannover, Germany
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Institute of Clinical Epidemiology and Biometry, University of Würzburg, Am Schwarzenberg 15, 97078 Würzburg, Germany
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Core Facility IT, Berlin Institute of Health at Charité—Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
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Medizinisches Datenintegrationszentrum, Charité—Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
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Department of Medical Informatics, University Medical Center Göttingen, Robert-Koch-Str. 40, 37075 Göttingen, Germany
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Center Digital Health, Berlin Institute of Health at Charité—Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
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Datenintegrationszentrum (DIZ), Servicezentrum Informatik (SMI), Universitätsklinikum Würzburg (UKW), Schweinfurter Strasse 4, 97078 Würzburg, Germany
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Medizinische Klinik für Kardiologie, Charité—Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
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Department of Cardiology and Pneumology/Heart Center, University Medical Center Göttingen, Robert-Koch-Str. 40, 37075 Göttingen, Germany
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Department Klinische Forschung und Epidemiologie, Deutsches Zentrum für Herzinsuffizienz, Am Schwarzenberg 15, 97078 Würzburg, Germany
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Medizinische Klinik I, Universitätsklinikum Würzburg (UKW), Oberdürrbacherstraße 6, 97080 Würzburg, Germany
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German Center of Cardiovascular Research (DZHK), Partner Site Göttingen, Robert-Koch-Straße 42a, 37075 Göttingen, Germany
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Institute for Cardiomyopathies Heidelberg (ICH), Heidelberg University Hospital, Im Neuenheimer Feld 669, 69120 Heidelberg, Germany
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Institute of Medical Informatics, Heidelberg University Hospital, Im Neuenheimer Feld 130.3, 69120 Heidelberg, Germany
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Medical Informatics Group, Berlin Institute of Health at Charité—Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
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Klaus Tschira Institute for Integrative Computational Cardiology, Heidelberg University Hospital, Im Neuenheimer Feld 669, 69120 Heidelberg, Germany
*
Author to whom correspondence should be addressed.
The order of authors 2–25 is alphabetical.
Academic Editor: Piotr Wojtek Dabrowski
Life 2022, 12(5), 749; https://doi.org/10.3390/life12050749
Received: 6 May 2022 / Accepted: 12 May 2022 / Published: 18 May 2022
(This article belongs to the Special Issue Computational Analysis of Biomedical Data)
Risk prediction in patients with heart failure (HF) is essential to improve the tailoring of preventive, diagnostic, and therapeutic strategies for the individual patient, and effectively use health care resources. Risk scores derived from controlled clinical studies can be used to calculate the risk of mortality and HF hospitalizations. However, these scores are poorly implemented into routine care, predominantly because their calculation requires considerable efforts in practice and necessary data often are not available in an interoperable format. In this work, we demonstrate the feasibility of a multi-site solution to derive and calculate two exemplary HF scores from clinical routine data (MAGGIC score with six continuous and eight categorical variables; Barcelona Bio-HF score with five continuous and six categorical variables). Within HiGHmed, a German Medical Informatics Initiative consortium, we implemented an interoperable solution, collecting a harmonized HF-phenotypic core data set (CDS) within the openEHR framework. Our approach minimizes the need for manual data entry by automatically retrieving data from primary systems. We show, across five participating medical centers, that the implemented structures to execute dedicated data queries, followed by harmonized data processing and score calculation, work well in practice. In summary, we demonstrated the feasibility of clinical routine data usage across multiple partner sites to compute HF risk scores. This solution can be extended to a large spectrum of applications in clinical care. View Full-Text
Keywords: medical informatics initiative; HiGHmed; medical data integration center; clinical routine data; heart failure; risk prediction scores; semantic interoperability; openEHR medical informatics initiative; HiGHmed; medical data integration center; clinical routine data; heart failure; risk prediction scores; semantic interoperability; openEHR
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MDPI and ACS Style

Sommer, K.K.; Amr, A.; Bavendiek, U.; Beierle, F.; Brunecker, P.; Dathe, H.; Eils, J.; Ertl, M.; Fette, G.; Gietzelt, M.; Heidecker, B.; Hellenkamp, K.; Heuschmann, P.; Hoos, J.D.E.; Kesztyüs, T.; Kerwagen, F.; Kindermann, A.; Krefting, D.; Landmesser, U.; Marschollek, M.; Meder, B.; Merzweiler, A.; Prasser, F.; Pryss, R.; Richter, J.; Schneider, P.; Störk, S.; Dieterich, C. Structured, Harmonized, and Interoperable Integration of Clinical Routine Data to Compute Heart Failure Risk Scores. Life 2022, 12, 749. https://doi.org/10.3390/life12050749

AMA Style

Sommer KK, Amr A, Bavendiek U, Beierle F, Brunecker P, Dathe H, Eils J, Ertl M, Fette G, Gietzelt M, Heidecker B, Hellenkamp K, Heuschmann P, Hoos JDE, Kesztyüs T, Kerwagen F, Kindermann A, Krefting D, Landmesser U, Marschollek M, Meder B, Merzweiler A, Prasser F, Pryss R, Richter J, Schneider P, Störk S, Dieterich C. Structured, Harmonized, and Interoperable Integration of Clinical Routine Data to Compute Heart Failure Risk Scores. Life. 2022; 12(5):749. https://doi.org/10.3390/life12050749

Chicago/Turabian Style

Sommer, Kim K., Ali Amr, Udo Bavendiek, Felix Beierle, Peter Brunecker, Henning Dathe, Jürgen Eils, Maximilian Ertl, Georg Fette, Matthias Gietzelt, Bettina Heidecker, Kristian Hellenkamp, Peter Heuschmann, Jennifer D.E. Hoos, Tibor Kesztyüs, Fabian Kerwagen, Aljoscha Kindermann, Dagmar Krefting, Ulf Landmesser, Michael Marschollek, Benjamin Meder, Angela Merzweiler, Fabian Prasser, Rüdiger Pryss, Jendrik Richter, Philipp Schneider, Stefan Störk, and Christoph Dieterich. 2022. "Structured, Harmonized, and Interoperable Integration of Clinical Routine Data to Compute Heart Failure Risk Scores" Life 12, no. 5: 749. https://doi.org/10.3390/life12050749

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