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Volume 16
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10.3390/life16060941
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Article

Quality Assessment in Paediatric Cardiology: Experiences from Leveraging a Clinical Data Warehouse

by
Wolfgang Wällisch
1,*,
Sven Dittrich
1,
Ariawan Purbojo
2,
Isabelle Schöffl
1,
Thomas Ganslandt
3,
Hans-Ulrich Prokosch
3,
Lorenz A. Kapsner
3,4 and
Jonathan M. Mang
5
1
Department of Paediatric Cardiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany
2
Department of Paediatric Cardiac Surgery, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany
3
Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91058 Erlangen, Germany
4
Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany
5
Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, 91054 Erlangen, Germany
*
Author to whom correspondence should be addressed.
Life 2026, 16(6), 941; https://doi.org/10.3390/life16060941
Submission received: 4 May 2026 / Revised: 22 May 2026 / Accepted: 26 May 2026 / Published: 2 June 2026
(This article belongs to the Special Issue Pediatric Cardiology Frontiers: Innovations in Diagnosis and Treatment)
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Abstract

Background: The generation of quality metrics for paediatric heart centre programmes frequently relies on registry data, with all the known benefits and disadvantages. This retrospective monocentric study introduces an algorithm capable of processing unedited clinical data to identify mortality risk factors following paediatric cardiac surgery. Methods: Patients who had undergone cardiac surgery in the department during the period from 2011 to 2020 were included when aged < 18 years. Congenital heart disease (CHD) was categorised into four diagnosis groups through hierarchical integration of the index surgery and CHD diagnosis. We evaluated preoperative, demographic, periprocedural, and postsurgical risk factors. Results: A total of 1700 patients with 2157 hospitalization encounters were included. The risk factors for elevated mortality with the highest degree of significance were extracorporeal membrane oxygenation (hazard ratio 13.97, p < 0.001), weight < 2500 g, patients in the univentricular heart group I, and the creatinine ratio. Conclusions: Beyond confirming established predictors such as ECMO and low body weight < 2500 g, the present analysis highlights the creatinine ratio as a strong laboratory-based predictor of mortality. The applied framework serves as a foundational step towards enabling the real-time utilisation of raw datasets across multiple centres, thereby supporting privacy-preserving and efficient quality metric assessment as well as enhanced risk stratification.
Keywords: congenital heart defects (CHDs); risk stratification; mortality; data processing; real-time analytics; quality metrics congenital heart defects (CHDs); risk stratification; mortality; data processing; real-time analytics; quality metrics

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MDPI and ACS Style

Wällisch, W.; Dittrich, S.; Purbojo, A.; Schöffl, I.; Ganslandt, T.; Prokosch, H.-U.; Kapsner, L.A.; Mang, J.M. Quality Assessment in Paediatric Cardiology: Experiences from Leveraging a Clinical Data Warehouse. Life 2026, 16, 941. https://doi.org/10.3390/life16060941

AMA Style

Wällisch W, Dittrich S, Purbojo A, Schöffl I, Ganslandt T, Prokosch H-U, Kapsner LA, Mang JM. Quality Assessment in Paediatric Cardiology: Experiences from Leveraging a Clinical Data Warehouse. Life. 2026; 16(6):941. https://doi.org/10.3390/life16060941

Chicago/Turabian Style

Wällisch, Wolfgang, Sven Dittrich, Ariawan Purbojo, Isabelle Schöffl, Thomas Ganslandt, Hans-Ulrich Prokosch, Lorenz A. Kapsner, and Jonathan M. Mang. 2026. "Quality Assessment in Paediatric Cardiology: Experiences from Leveraging a Clinical Data Warehouse" Life 16, no. 6: 941. https://doi.org/10.3390/life16060941

APA Style

Wällisch, W., Dittrich, S., Purbojo, A., Schöffl, I., Ganslandt, T., Prokosch, H.-U., Kapsner, L. A., & Mang, J. M. (2026). Quality Assessment in Paediatric Cardiology: Experiences from Leveraging a Clinical Data Warehouse. Life, 16(6), 941. https://doi.org/10.3390/life16060941

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