The epidemiological study of basal cell carcinomas (BCCs) is difficult because BCCs lack distinct disease codes and are excluded from most cancer registries. To develop and validate a large BCC registry based on electronically assigned Systematized Nomenclature of Medicine (SNOMED) codes and text-string searches of electronic pathology reports from Kaiser Permanente Northern California. Potential BCCs were identified from electronic pathology reports (n=39,026) in 2005 and were reviewed by a dermatologist who assigned case/non-case status (gold-standard). A subset of the records (n=9,428) was independently reviewed by a second dermatologist to ascertain reliability of case assignment. In addition, a subset of excluded electronic pathology reports from 2005 (n=2,700) was reviewed to determine whether inclusion criteria had missed potential BCCs. We calculated the positive predictive value (PPV) of 3 different algorithms for identifying BCCs from electronic pathology data. BCC-specific SNOMED codes had the highest PPV for identifying BCCs, 0.992 (95 percent CI: 0.991-0.993). Inter-rater reliability for case assignment was high (kappa=0.92, 95 percent CI: 0.91-0.93). Standardized incidence rates were consistent with previously published rates in the United States. We created and validated a large BCC registry to serve as a unique resource for studying BCCs.