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Yusuf, K.O.* ; Chaplinskaya-Sobol, I.* ; Schoneberg, A.* ; Hanss, S.* ; Valentin, H.* ; Lorenz-Depiereux, B. ; Hansch, S.* ; Fiedler, K.* ; Scherer, M.* ; Sikdar, S.* ; Miljukov, O.* ; Reese, J.P.* ; Wagner, P.* ; Bröhl, I.* ; Geißler, R.* ; Vehreschild, J.J.* ; Blaschke, S.* ; Bellinghausen, C.* ; Milovanovic, M.* ; Krefting, D.*

Impact of clinical study implementation on data quality assessments - using contradictions within interdependent health data items as a pilot indicator.

Stud. Health Technol. Inform. 307, 152-158 (2023)
Verlagsversion DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
INTRODUCTION: Contradiction is a relevant data quality indicator to evaluate the plausibility of interdependent health data items. However, while contradiction assessment is achieved using domain-established contradictory dependencies, recent studies have shown the necessity for additional requirements to reach conclusive contradiction findings. For example, the oral or rectal methods used in measuring the body temperature will influence the thresholds of fever definition. The availability of this required information as explicit data items must be guaranteed during study design. In this work, we investigate the impact of activities related to study database implementation on contradiction assessment from two perspectives including: 1) additionally required metadata and 2) implementation of checks within electronic case report forms to prevent contradictory data entries. METHODS: Relevant information (timestamps, measurement methods, units, and interdependency rules) required for contradiction checks are identified. Scores are assigned to these parameters and two different studies are evaluated based on the fulfillment of the requirements by two selected interdependent data item sets. RESULTS: None of the studies have fulfilled all requirements. While timestamps and measurement units are found, missing information about measurement methods may impede conclusive contradiction assessment. Implemented checks are only found if data are directly entered. DISCUSSION: Conclusive contradiction assessment typically requires metadata in the context of captured data items. Consideration during study design and implementation of data capture systems may support better data quality in studies and could be further adopted in primary health information systems to enhance clinical anamnestic documentation.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Contradictions ; Data Quality ; Electronic Data Capture ; Metadata Definition
Sprache englisch
Veröffentlichungsjahr 2023
HGF-Berichtsjahr 2023
ISSN (print) / ISBN 0926-9630
Quellenangaben Band: 307, Heft: , Seiten: 152-158 Artikelnummer: , Supplement: ,
Verlag IOS Press
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Epidemiology (EPI)
POF Topic(s) 30202 - Environmental Health
Forschungsfeld(er) Genetics and Epidemiology
PSP-Element(e) G-504091-004
Scopus ID 85170631434
PubMed ID 37697849
Erfassungsdatum 2023-10-18