AI Summary
In this study, the feasibility of structuring electronic health record (EHR) data for research purposes using the ICAREdata project was examined in multicenter cancer clinical trials. The project utilized a minimal Common Oncology Data Elements (mCODE) data model to capture and transmit key research data elements in EHRs. Data extracted from EHRs were compared with data from the trial's electronic data capture (EDC) system, showing promising concordance rates for cancer disease status and treatment plan change elements. The study demonstrated that structuring EHR data using mCODE and ICAREdata methods is feasible in multi-institutional cancer clinical trials, with future initiatives focusing on efficient workflows and shared definitions for elements in clinical and research environments. The use of structured data could improve data sharing and reduce the need for manual data entry on electronic case report forms in clinical trials.
Abstract
Background
The use of electronic health record (EHR) data for research is limited by a lack of structure and a standard data model. The objective of the ICAREdata (Integrating Clinical Trials and Real-World Endpoints Data) project was to structure key research data elements in EHRs using a minimal Common Oncology Data Elements (mCODE) data model to extract and transmit data.
Methods
The ICAREdata project captured two EHR data elements essential to clinical trials: cancer disease status and treatment plan change. The project was implemented in clinical sites participating in Alliance for Clinical Trials in Oncology trials. Data were extracted from EHRs and sent by secure Fast Healthcare Interoperability Resource messaging (a standard for exchanging EHRs) to a database. Selected elements were compared with corresponding data from the trial’s electronic data capture (EDC) system, Medidata Rave.
Results
By December 2023, data were extracted and transmitted from 10 sites for 35 patients, involving 367 clinical encounters across 15 clinical trials. Data through March 2023 demonstrated that concordance for the elements treatment plan change and cancer disease status was 79% and 34%, respectively. When disease evaluation was reported by both EHR and EDC (n = 15), there was 87% agreement on cancer disease status.
Conclusions
Documentation, extraction, and aggregation of structured data elements in EHRs using mCODE and ICAREdata methods is feasible in multi-institutional cancer clinical trials. EDC as a reference data set allowed assessment of the completeness of EHR data capture. Future initiatives will focus on elements with shared definitions in clinical and research environments and efficient workflows.
Plain Language Summary
Clinical trials use electronic case report forms to report data, and data must be manually entered on these forms, which is costly and time consuming.
ICAREdata methods use structured, organized data from clinical trials that can be more easily shared instead having to enter free text into electronic health records.