Evaluating SEER-Medicare Linked Database Completeness for Oral and Pharyngeal Cancer

• Activity Number: 209
• Type: Contributed
• Date/Time: Monday, July 30, 2007 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Jonathan Mahnken and John Keighley*+ and Matthew Mayo
• Companies: The University of Kansas Medical Center and The University of Kansas Medical Center and The University of Kansas Medical Center
• Keywords: secondary data analysis ; health outcomes research ; Poisson Regression

Abstract

Oral and pharyngeal (OP) cancer is a persistent oral health problem. Baseline and trend data to measure progress are lacking. Our long-term goal is to create an algorithm using Medicare claims to identify OP cancer cases among those 65+. The goal of this project was to assess the completeness of the SEER-Medicare linked database (SEER-Med). We compared IRs from the "gold-standard" SEER public use database (SEER) to those from SEER-Med using Poisson regression, adjusted for age, sex, race, and ethnicity (and interactions with data source). The IR (95% CI) for OP cancer (/100,000 person-years) using SEER-Med was 31.2 (30.6-31.8), and from SEER was 43.0 (42.3-43.7). Thus, about 1/4 of the cases were missing from SEER-Med (IRR: 0.73; 0.71-0.74). Significant interactions indicated completeness varied by race (p< 0.0001) and ethnicity (p< 0.0001).