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Implementing Cancer Registry Data with the PCORnet Common Data Model: The Greater Plains Collaborative Experience

  • Bradley D. McDowell
  • , Michael A. O'Rorke
  • , Mary C. Schroeder
  • , Elizabeth A. Chrischilles
  • , Christine M. Spinka
  • , Lemuel R. Waitman
  • , Kelechi Anuforo
  • , Alejandro Araya
  • , Haddyjatou Bah
  • , Jackson Barlocker
  • , Sravani Chandaka
  • , Lindsay G. Cowell
  • , Carol R. Geary
  • , Snehil Gupta
  • , Benjamin D. Horne
  • , Boyd M. Knosp
  • , Albert M. Lai
  • , Vasanthi Mandhadi
  • , Abu Saleh Mohammad Mosa
  • , Phillip Reeder
  • Giyung Ryu, Brian Shukwit, Claire Smith, Alexander J. Stoddard, Mahanazuddin Syed, Shorabuddin Syed, Bradley W. Taylor, Jeffrey J. Vanwormer

Producción científica: Articlerevisión exhaustiva

Resumen

PURPOSEElectronic health records (EHRs) comprise a rich source of real-world data for cancer studies, but they often lack critical structured data elements such as diagnosis date and disease stage. Fortunately, such concepts are available from hospital cancer registries. We describe experiences from integrating cancer registry data with EHR and billing data in an interoperable data model across a multisite clinical research network.METHODSAfter sites implemented cancer registry data into a tumor table compatible with the PCORnet Common Data Model (CDM), distributed queries were performed to assess quality issues. After remediation of quality issues, another query produced descriptive frequencies of cancer types and demographic characteristics. This included linked BMI. We also report two current use cases of the new resource.RESULTSEleven sites implemented the tumor table, yielding a resource with data for 572,902 tumors. Institutional and technical barriers were surmounted to accomplish this. Variations in racial and ethnic distributions across the sites were observed; the percent of tumors among Black patients ranged from <1% to 15% across sites, and the percent of tumors among Hispanic patients ranged from 1% to 46% across sites. Current use cases include a pragmatic prospective cohort study of a rare cancer and a retrospective cohort study leveraging body size and chemotherapy dosing.CONCLUSIONIntegrating cancer registry data with the PCORnet CDM across multiple institutions creates a powerful resource for cancer studies. It provides a wider array of structured, cancer-relevant concepts, and it allows investigators to examine variability in those concepts across many treatment environments. Having the CDM tumor table in place enhances the impact of the network's effectiveness for real-world cancer research.

Idioma originalEnglish (US)
Número de artículoe2400196
PublicaciónJCO clinical cancer informatics
Volumen8
DOI
EstadoPublished - dic 1 2024

ASJC Scopus subject areas

  • Oncology
  • Health Informatics
  • Cancer Research

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