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Cancer data from population-based cancer registries under-report cancer cases, especially for cancers primarily diagnosed and treated in outpatient clinical settings, away from hospital-based cancer registrars. Previously, we developed alternative methods of cancer case capture including a claims-based method, which identified a large proportion of cancer cases missed by traditional population-based cancer registries. In this study, we adapted a claims-based method for statewide implementation of cancer surveillance in Florida. Between 2010 and 2017 the claims-based method identified 143,083 cancer abstracts, of which 42% were new and 58% were previously registered. The claims-based method led to the creation of 53,419 new cancer cases in the state cancer registry, which made up 9.3% of all cancer cases registered between 2010 and 2017. The types of cancers identified by the claims-based method were typical of the kinds primarily diagnosed and treated in outpatient oncology clinic settings, such as hematological malignancies, prostate cancer, melanoma, breast cancer, and bladder cancer. These cases were added to the Florida cancer registry and may produce an artefactual increase in cancer incidence, which is believed to be closer to the actual burden of cancer in the state.

Background: Reporting of hematologic malignancies is an increasingly important focus for cancer surveillance. As trends in cancer care are shifting to the outpatient setting, hospital-based data collection methods used for cancer surveillance will result in under-reporting of these cancers. This study describes the testing and validation of an automated system for capturing and reporting cancers from community oncology providers., Methods: The system was evaluated in 5 oncology practices in two states processing claims data for a 4- or 8-month interval. Resulting cancers were matched with the state registries. A random sample of nonmatched cases was reabstracted to measure the accuracy of the claims data for reporting of hematologic malignancies., Results: The overall match rate for the 1,935 hematologic malignancies reported during the study period was 58.2 % (range, 37.4 % for CLL to 71.2 % for Hodgkin's Lymphoma). The overall accuracy rate for billing-reported hematologic malignancies was 95 %. Accuracy among cases that did not match with the cancer registry was 88 %. The estimated number of missed cases for the five participating practices ranged from 0.8 leukemia cases/oncologist/year to 3.4 CLL cases/oncologist/year. The estimated total number of missed cases in the five participating practices was 292 with an interquartile range of 263-323., Conclusion: As cancer diagnosis and treatment continue migration into ambulatory physician practice settings unreported hematopoietic cases will become increasingly problematic. Leveraging the standardized electronic billing data for automated reporting of cancer cases from physician practices may be an efficient method to reduce this gap in cancer surveillance reporting.