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Using the Observational Medical Outcomes Partnership Common Data Model for a multi-registry intensive care unit
Aasiyah Rashan1, Daniel P Püttmann2,3,4, Nicolette F de Keizer2,3,4
1Institute of Health Informatics, University College London, London WC1E 6BT, United Kingdom.
Federated analysis is feasible for critical care registries using the OMOP Common Data Model. Careful data preparation and clear documentation during OMOP CDM implementation are crucial for efficient and accurate benchmarking.
Area of Science:
- Health Informatics
- Critical Care Medicine
- Data Science
Background:
- Federated analysis enables collaborative research on sensitive health data without direct data sharing, crucial for international studies and privacy compliance.
- The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) standardizes diverse health datasets for analysis.
- Benchmarking mortality in critical care quality registries is essential for quality improvement.
Purpose of the Study:
- To evaluate the feasibility of federated analysis for benchmarking mortality in critical care quality registries.
- To identify and address challenges encountered when transforming registry data to the OMOP CDM for federated analysis.
- To provide recommendations for optimizing federated analysis on OMOP CDM-transformed data.
Main Methods:
- A 2-step approach involving naive implementation followed by solution development was used to identify challenges.
- The Acute Physiology and Chronic Health Evaluation II (APACHE II) model was applied to OMOP CDM-transformed adult ICU data (July 2019-December 2022).
- An analysis script calculated standardized mortality ratios at the registry level, with challenges categorized into data preparation, analysis, and interpretation.
Main Results:
- Seven challenges were identified: 4 in data preparation, 1 in data analysis, and 1 in data interpretation.
- Four of the seven challenges arose from decisions made during the OMOP CDM implementation phase.
- Recommended solutions were developed based on the encountered challenges.
Conclusions:
- Federated analysis is a viable method for critical care quality registries when utilizing a CDM.
- The efficiency and accuracy of federated analysis are significantly impacted by decisions made during CDM implementation.
- Publishing data dictionaries and using metadata are recommended to enhance future federated analyses.
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