Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Aug 26:8:149-155.
doi: 10.2147/POR.S140579. eCollection 2017.

A validation of clinical data captured from a novel Cancer Care Quality Program directly integrated with administrative claims data

David M Kern  1 , John J Barron  1 , Bingcao Wu  1 , Alex Ganetsky  2 , Vincent J Willey  1 , Ralph A Quimbo  1 , Michael J Fisch  3 , Joseph Singer  1 , Ann Nguyen  4 , Ronac Mamtani  5
Affiliations

A validation of clinical data captured from a novel Cancer Care Quality Program directly integrated with administrative claims data

David M Kern et al. Pragmat Obs Res. .

Abstract

Background: Data from a Cancer Care Quality Program are directly integrated with administrative claims data to provide a level of clinical detail not available in claims-based studies, and referred to as the HealthCore Integrated Research Environment (HIRE)-Oncology data. This study evaluated the validity of the HIRE-Oncology data compared with medical records of breast, lung, and colorectal cancer patients.

Methods: Data elements included cancer type, stage, histology (lung only), and biomarkers. A sample of 300 breast, 200 lung, and 200 colorectal cancer patients within the HIRE-Oncology data were identified for medical record review. Statistical measures of validity (agreement, positive predictive value [PPV], negative predictive value [NPV], sensitivity, specificity) were used to compare clinical information between data sources, with medical record data considered the gold standard.

Results: All 300 breast cancer records reviewed were confirmed breast cancer, while 197 lung and 197 colorectal records were confirmed (PPV =0.99 for each). The agreement of disease stage was 85% for breast, 90% for lung, and 94% for colorectal cancer. The agreement of lung cancer histology (small cell vs non-small cell) was 97%. Agreement of progesterone receptor, estrogen receptor, and human epidermal growth factor receptor 2 status biomarkers in breast cancer was 92%, 97%, and 92%, respectively; epidermal growth factor receptor and anaplastic lymphoma kinase agreement in lung was 97% and 92%, respectively; and agreement of KRAS status in colorectal cancer was 95%. Measures of PPV, NPV, sensitivity, and specificity showed similarly strong evidence of validity.

Conclusion: Good agreement between the HIRE-Oncology data and medical records supports the validity of these data for research.

Keywords: administrative claims; breast cancer; colorectal cancer; lung cancer; oncology; validation.

PubMed Disclaimer

Conflict of interest statement

Disclosure Authors DMK, JJB, VJW, RAQ, and JS are employees of HealthCore, Inc, a subsidiary of Anthem, Inc. BW was an employee of HealthCore, Inc at the time of the study. AN is an employee of Anthem, Inc. MJF is an employee of AIM Specialty Health. RM was supported by the National Institutes of Health (NIH) / National Cancer Institute (NIC) grant K23CA187185. The authors report no other conflicts of interest in this work.

References

    1. Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol. 2005;58(4):323–337. - PubMed
    1. van Walraven C, Bennett C, Forster AJ. Administrative database research infrequently used validated diagnostic or procedural codes. J Clin Epidemiol. 2011;64(10):1054–1059. - PubMed
    1. Johnson EK, Nelson CP. Utility and pitfalls in the use of administrative databases for outcomes assessment. J Urol. 2013;190(1):17–18. - PMC - PubMed
    1. Quan H, Li B, Saunders LD, et al. Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database. Health Serv Res. 2008;43(4):1424–1441. - PMC - PubMed
    1. Khokhar B, Jette N, Metcalfe A, et al. Systematic review of validated case definitions for diabetes in ICD-9-coded and ICD-10-coded data in adult populations. BMJ Open. 2016;6(8):e009952. - PMC - PubMed