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Validation of electronic data on chemotherapy and hormone therapy use in HMOs

, : Validation of electronic data on chemotherapy and hormone therapy use in HMOs. Medical Care 51(10): E67-E73

Most data regarding medical care for cancer patients in the United States comes from Surveillance, Epidemiology and End Results-linked Medicare analyses of individuals aged 65 years or older and typically excludes Medicare Advantage enrollees. To assess the accuracy of chemotherapy and hormone therapy treatment data available through the Cancer Research Network's Virtual Data Warehouse (VDW). Retrospective, longitudinal cohort study. Medical record-abstracted, tumor registry-indicated treatments (gold standard) were compared with VDW-indicated treatments derived from health maintenance organization pharmacy, electronic medical record, and claim-based data systems. Enrollees aged 18 years and older diagnosed with incident breast, colorectal, lung, or prostate cancer from 2000 through 2007. Sensitivity, specificity, and positive predictive value were computed at 6 and 12 months after cancer diagnosis. Approximately 45% of all cancer cases (total N=23,800) were aged 64 years or younger. Overall chemotherapy sensitivity/specificities across the 3 health plans for incident breast, colorectal, lung, and prostate cancer cases were 95%/90%, 95%/93%, 93%/93%, and 85%/77%, respectively. With the exception of prostate cancer cases, overall positive predictive value ranged from 86% to 89%. Small variations in chemotherapy data accuracy existed due to cancer site and data source, whereas greater variation existed in hormone therapy capture across sites. Strong concordance exists between gold standard tumor registry measures of chemotherapy receipt and Cancer Research Network VDW data. Health maintenance organization VDW data can be used for a variety of studies addressing patterns of cancer care and comparative effectiveness research that previously could only be conducted among elderly Surveillance, Epidemiology and End Results-Medicare populations.


PMID: 22531648

DOI: 10.1097/MLR.0b013e31824def85

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