Hematologic malignancies: an opportunity to fill a gap in cancer surveillance.

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.

The value of billing data from oncology practice to supplement treatment information for cancer surveillance.

BACKGROUND: Cancer treatment information is often underreported in cancer registries due to the shift in cancer care to ambulatory settings. Incomplete treatment information for central registries limits the usefulness of these data for understanding disparities in outcomes. The objective of this study was to evaluate the added value and validity of medical billing data to supplement treatment for incident cases within a central cancer registry. METHODS: Billing data using standardized structure and nomenclature as submitted by all practices was evaluated using an automated software (MDoffice, MDO) process that captures and processes these data and submits the information in a standardized format. A validation of the billing reported treatment was performed using data from 3 community oncology practices. RESULTS: The accuracy of treatment data captured was 100 percent for both chemotherapy and radiation therapy among the 313 cases validated. Chemotherapy (36 percent and 5 percent respectively for solid tumors and hematologic cancers) and radiation therapy (46 percent and 20 percent respectively for solid tumors and hematologic cancers) information was added to 738 known incident cases using billing data. CONCLUSION: Automated reporting based on billing data from community specialty providers is likely to markedly enhance the completeness of treatment data among known cancer cases as these community providers render significant amounts of treatment for cancer patients.