Purpose: The STOPP/START criteria are increasingly used to assess prescribing quality in elderly patients at practice level. Our aim was to test computerized algorithms for applying these criteria to a medical record database. Methods: STOPP/START criteria-based computerized algorithms were defined using Anatomical-Therapeutic-Chemical (ATC) codes for medication and International Classification of Primary Care (ICPC) codes for diagnoses. The algorithms were applied to a Dutch primary care database, including patients aged ≥65 years using ≥5 chronic drugs. We tested for associations with patient characteristics that have previously shown a relationship with the original STOPP/START criteria, using multivariate logistic regression models. Results: Included were 1187 patients with a median age of 75 years. In total, 39 of the 62 STOPP and 18 of the 26 START criteria could be converted to a computerized algorithm. The main reasons for inapplicability were lack of information on the severity of a condition and insufficient covering of ICPC-codes. We confirmed a positive association between the occurrence of both the STOPP and the START criteria and the number of chronic drugs (adjusted OR ranging from 1.37, 95% CI 1.04-1.82 to 3.19, 95% CI 2.33-4.36) as well as the patient's age (adjusted OR for STOPP 1.30, 95% CI 1.01-1.67; for START 1.73, 95% CI 1.35-2.21), and also between female gender and the occurrence of STOPP criteria (adjusted OR 1.41, 95% CI 1.09-1.82). Conclusion: Sixty-five percent of the STOPP/START criteria could be applied with computerized algorithms to a medical record database with ATC-coded medication and ICPC-coded diagnoses.