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Feasibility of structuring electronic health record data to facilitate real-world data research: ICAREdata methods applied to multicenter cancer clinical trials.
George, Suzanne; Campbell, Nancy; Hillman, Shauna L; Harlos, Elizabeth S; Stein, David W J; Chan, Miranda Y; Chow, Selina L; Elrahi, Cassandra L; Quina, Andre C; Kokolus, Maeve C; Casagni, Michelle D; Weiss, Matthias; Anderson, Daniel M; Stadler, Walter M; Hoff, Olivia C; Rivera, Donna R; Kluetz, Paul G; Mandrekar, Sumithra J; Piantadosi, Steven.
Afiliación
  • George S; Dana-Farber/Harvard Cancer Center, Boston, Massachusetts, USA.
  • Campbell N; Data Innovation Lab LLC, Alliance for Clinical Trials in Oncology, Boston, Massachusetts, USA.
  • Hillman SL; Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, Minnesota, USA.
  • Harlos ES; Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, Minnesota, USA.
  • Stein DWJ; The MITRE Corporation, Bedford, Massachusetts, USA.
  • Chan MY; The MITRE Corporation, Bedford, Massachusetts, USA.
  • Chow SL; Alliance for Clinical Trials in Oncology, Chicago, Illinois, USA.
  • Elrahi CL; Data Innovation Lab LLC, Alliance for Clinical Trials in Oncology, Boston, Massachusetts, USA.
  • Quina AC; The MITRE Corporation, Bedford, Massachusetts, USA.
  • Kokolus MC; The MITRE Corporation, Bedford, Massachusetts, USA.
  • Casagni MD; The MITRE Corporation, Tampa, Florida, USA.
  • Weiss M; ThedaCare Regional Cancer Center, Appleton, Wisconsin, USA.
  • Anderson DM; Metro-Minnesota Community Oncology Research Consortium, St Louis Park, Minnesota, USA.
  • Stadler WM; University of Chicago Comprehensive Cancer Center, Chicago, Illinois, USA.
  • Hoff OC; Metro-Minnesota Community Oncology Research Consortium, St Louis Park, Minnesota, USA.
  • Rivera DR; Oncology Center of Excellence, US Food and Drug Administration, Silver Spring, Maryland, USA.
  • Kluetz PG; Oncology Center of Excellence, US Food and Drug Administration, Silver Spring, Maryland, USA.
  • Mandrekar SJ; Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, Minnesota, USA.
  • Piantadosi S; Brigham and Women's Hospital, Boston, Massachusetts, USA.
Cancer ; 2024 Aug 28.
Article en En | MEDLINE | ID: mdl-39192753
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.
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Cancer Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Cancer Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos