Concordance between administrative claims and registry data for identifying metastasis to the bone: an exploratory analysis in prostate cancer
1 Pharmaceutical Health Services Research Department, University of Maryland School of Pharmacy, 220 Arch Street, Baltimore, MD 21201, USA
2 Department of Medicine, University of Maryland School of Medicine, 655 West Baltimore Street, Baltimore, MD 21201, USA
3 Baltimore Veterans Affairs Medical Center, 655 West Baltimore Street, Baltimore, MD 21201, USA
4 Bayer Healthcare Pharmaceuticals, 6 West Belt, Wayne, NJ 07470-6806, USA
BMC Medical Research Methodology 2014, 14:1 doi:10.1186/1471-2288-14-1Published: 2 January 2014
To assess concordance between Medicare claims and Surveillance, Epidemiology, and End Results (SEER) reports of incident BM among prostate cancer (PCa) patients. The prevalence and consequences of bone metastases (BM) have been examined across tumor sites using healthcare claims data however the reliability of these claims-based BM measures has not been investigated.
This retrospective cohort study utilized linked registry and claims (SEER-Medicare) data on men diagnosed with incident stage IV M1 PCa between 2005 and 2007. The SEER-based measure of incident BM was cross-tabulated with three separate Medicare claims approaches to assess concordance. Sensitivity, specificity and positive predictive value (PPV) were calculated to assess the concordance between registry- and claims-based measures.
Based on 2,708 PCa patients in SEER-Medicare, there is low to moderate concordance between the SEER- and claims-based measures of incident BM. Across the three approaches, sensitivity ranged from 0.48 (0.456 – 0.504) to 0.598 (0.574 - 0.621), specificity ranged from 0.538 (0.507 - 0.569) to 0.620 (0.590 - 0.650) and PPV ranged from 0.679 (0.651 - 0.705) to 0.690 (0.665 - 0.715). A comparison of utilization patterns between SEER-based and claims-based measures suggested avenues for improving sensitivity.
Claims-based measures using BM ICD 9 coding may be insufficient to identify patients with incident BM diagnosis and should be validated against chart data to maximize their potential for population-based analyses.