TY - JOUR
T1 - Implementing Cancer Registry Data with the PCORnet Common Data Model
T2 - The Greater Plains Collaborative Experience
AU - McDowell, Bradley D.
AU - O'Rorke, Michael A.
AU - Schroeder, Mary C.
AU - Chrischilles, Elizabeth A.
AU - Spinka, Christine M.
AU - Waitman, Lemuel R.
AU - Anuforo, Kelechi
AU - Araya, Alejandro
AU - Bah, Haddyjatou
AU - Barlocker, Jackson
AU - Chandaka, Sravani
AU - Cowell, Lindsay G.
AU - Geary, Carol R.
AU - Gupta, Snehil
AU - Horne, Benjamin D.
AU - Knosp, Boyd M.
AU - Lai, Albert M.
AU - Mandhadi, Vasanthi
AU - Mohammad Mosa, Abu Saleh
AU - Reeder, Phillip
AU - Ryu, Giyung
AU - Shukwit, Brian
AU - Smith, Claire
AU - Stoddard, Alexander J.
AU - Syed, Mahanazuddin
AU - Syed, Shorabuddin
AU - Taylor, Bradley W.
AU - Vanwormer, Jeffrey J.
N1 - Publisher Copyright:
© 2024 American Society of Clinical Oncology.
PY - 2024/12/1
Y1 - 2024/12/1
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85213017141
UR - https://www.scopus.com/pages/publications/85213017141#tab=citedBy
U2 - 10.1200/CCI-24-00196
DO - 10.1200/CCI-24-00196
M3 - Article
C2 - 39689273
AN - SCOPUS:85213017141
SN - 2473-4276
VL - 8
JO - JCO clinical cancer informatics
JF - JCO clinical cancer informatics
M1 - e2400196
ER -