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. 2022 Mar:6:e2100149.
doi: 10.1200/CCI.21.00149.

Cancer Registry Data Linkage of Electronic Health Record Data From ASCO's CancerLinQ: Evaluation of Advantages, Limitations, and Lessons Learned

Affiliations

Cancer Registry Data Linkage of Electronic Health Record Data From ASCO's CancerLinQ: Evaluation of Advantages, Limitations, and Lessons Learned

Mary E Charlton et al. JCO Clin Cancer Inform. 2022 Mar.

Abstract

Purpose: To evaluate the completeness of information for research and quality assessment through a linkage between cancer registry data and electronic health record (EHR) data refined by ASCO's health technology platform CancerLinQ.

Methods: A probabilistic data linkage between Iowa Cancer Registry (ICR) and an Iowa oncology clinic through CancerLinQ data was conducted for cases diagnosed between 2009 and 2018. Demographic, cancer, and treatment variables were compared between data sources for the same patients, all of whom were diagnosed with one primary cancer. Treatment data and compliance with quality measures were compared among those with breast or prostate cancer; SEER-Medicare data served as a comparison. Variables captured only in CancerLinQ data (smoking, pain, and height/weight) were evaluated for completeness.

Results: There were 6,175 patients whose data were linked between ICR and CancerLinQ data sets. Of those, 4,291 (70%) were diagnosed with one primary cancer and were included in analyses. Demographic variables were comparable between data sets. Proportions of people receiving hormone therapy (30% v 26%, P < .0001) or immunotherapy (22% v 12%, P < .0001) were significantly higher in CancerLinQ data compared with ICR data. ICR data contained more complete TNM stage, human epidermal growth factor receptor 2 testing, and Gleason score information. Compliance with quality measures was generally highest in SEER-Medicare data followed by the combined ICR-CancerLinQ data. CancerLinQ data contained smoking, pain, and height/weight information within one month of diagnosis for 88%, 52%, and 76% of patients, respectively.

Conclusion: Linking CancerLinQ EHR data with cancer registry data led to more complete data for each source respectively, as registry data provides definitive diagnosis and more complete stage information and laboratory results, whereas EHR data provide more detailed treatment data and additional variables not captured by registries.

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Conflict of interest statement

George KomatsoulisEmployment: Zephyr AILeadership: Zephyr AIStock and Other Ownership Interests: Zephyr AINo other potential conflicts of interest were reported.

Figures

FIG 1.
FIG 1.
Comparison of treatment regimens within 12 months of diagnosis between CancerLinQ, ICR,a and SEER-Medicareb data among those with (A) breast or (B) prostate cancers who were enrolled in Medicare between 2009 and 2015. CLQ, CancerLinQ; HMO, Health Maintenance Organization; ICR, Iowa Cancer Registry.aDue to changing coding guidelines, only 2013-2015 data was included for ICR.bThose included in the SEER-Medicare population were required to have Parts A, B, and D coverage without HMO enrollment in the year following diagnosis.

References

    1. Potter D, Brothers R, Kolacevski A, et al. : Development of CancerLinQ, a health information learning platform from multiple electronic health record systems to support improved quality of care. JCO Clin Cancer Inform 4:929-937, 2020 - PMC - PubMed
    1. Chiang AC: Why the quality oncology practice initiative matters: It's not just about cost. Am Soc Clin Oncol Ed Book 35:e102-107, 2016 - PubMed
    1. Enewold L, Parsons H, Zhao L, et al. : Updated overview of the SEER-Medicare data: Enhanced content and applications. JNCI Monogr 2020:3-13, 2020 - PMC - PubMed
    1. National Cancer Institute : Match*Pro Software. https://surveillance.cancer.gov/matchpro/download
    1. National Library of Medicine : SNOMED CT. https://www.nlm.nih.gov/healthit/snomedct/index.html - PubMed

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