Feasibility of structuring electronic health record data to facilitate real-world data research: ICAREdata methods applied to multicenter cancer clinical trials
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View abstract on PubMed
Summary
This summary is machine-generated.Structuring electronic health record (EHR) data using the minimal Common Oncology Data Elements (mCODE) model is feasible for cancer clinical trials. The ICAREdata project demonstrated this approach can improve data extraction and sharing for research.
Area Of Science
- Oncology
- Health Informatics
- Clinical Trials
Background
- Electronic health record (EHR) data often lacks structure and standardization, hindering its use in research.
- The Integrating Clinical Trials and Real-World Endpoints Data (ICAREdata) project aimed to address this by structuring EHR data.
Purpose Of The Study
- To structure key research data elements within EHRs using the minimal Common Oncology Data Elements (mCODE) data model.
- To extract and transmit this structured data for research purposes.
Main Methods
- The ICAREdata project focused on capturing cancer disease status and treatment plan changes from EHRs.
- Data were extracted from clinical sites using Fast Healthcare Interoperability Resource (FHIR) messaging and compared against electronic data capture (EDC) systems.
- Implementation occurred in sites participating in Alliance for Clinical Trials in Oncology trials.
Main Results
- Data extraction and transmission were completed from 10 sites for 35 patients across 15 trials.
- Concordance rates for treatment plan change and cancer disease status were 79% and 34%, respectively.
- Agreement on cancer disease status reached 87% when evaluated by both EHR and EDC systems.
Conclusions
- Structuring EHR data using mCODE and ICAREdata methods is achievable in multi-institutional cancer clinical trials.
- EDC systems serve as valuable references for assessing EHR data completeness.
- Future efforts will prioritize elements with shared definitions and streamlined workflows.
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