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

Authors :
Kim K. Sommer
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
Christoph Dieterich
Source :
Life, Vol 12, Iss 5, p 749 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

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.

Details

Language :
English
ISSN :
20751729
Volume :
12
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Life
Publication Type :
Academic Journal
Accession number :
edsdoj.2af5f865521a43caa7101f243f4d83ae
Document Type :
article
Full Text :
https://doi.org/10.3390/life12050749