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Table 0; documenting the steps to go from clinical database to research dataset
Jip W T M de Kok1, Bas C T van Bussel2, Ronny Schnabel3
1Department of Intensive Care Medicine, Maastricht University Medical Centre+, Maastricht, The Netherlands; Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands.
Journal of Clinical Epidemiology
|April 4, 2024
Summary
Documenting the extraction of patient data from clinical databases is crucial for research validity. This case study shows how to create a definitive patient list, improving health data quality and analysis.
Area of Science:
- Health Informatics
- Clinical Data Management
- Observational Health Research
Background:
- Data-driven decision support tools are transforming healthcare.
- Research datasets are often built on clinical data without clear documentation of extraction methods.
- The process of data extraction significantly impacts dataset validity, interpretability, and downstream analyses.
Purpose of the Study:
- To illustrate the impact of selecting a definitive patient list from a clinical source database.
- To highlight the importance of documenting the data extraction process in health research.
- To present a case study on reporting patient list extraction from clinical databases.
Main Methods:
- A single-center observational study was conducted at an academic hospital.
- Admissions from a critical care database between January 1, 2013, and January 1, 2023, were utilized.
- An interdisciplinary team identified and addressed data insufficiency and uncertainty.
Main Results:
- A stepwise data preparation process reduced the initial database of 54,218 admissions to a definitive patient list of 21,553 admissions.
- Transparent documentation of data preparation enhanced the quality of the definitive patient list.
- Seven recommendations for preparing observational health data for research were generated.
Conclusions:
- Documenting data preparation is essential for understanding research datasets derived from clinical databases.
- Meticulous data preparation and documentation improve research validity and advance critical care.
- The findings contribute to establishing data standards for health data research.
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