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Objective: To determine if there are significant differences between universities in the proclivity to choose Family and Community Medicine (FCM), given the constraints imposed by the number of choice. To test the hypothesis that the Schools of Medicine that have the FCM as a compulsory subject in the degree (3 of 27) had the highest preference for this specialty., Design: Observational study on the data file of all the individuals taking the MIR examination between 2003 and 2011., Location: Spain., Participants: All those who sat the examinations called by MIR 2003-2011., Main Measurements: Position in the ranking of each candidate, elected position (specialty and center), post code of residence, sex, nationality and university in which they studied, and post code location for the residence chosen., Results: The percentage electing FCM is highly correlated with the position in the ranking: 8% of graduates for the 'best' college, 46% for the worst. Very noticeable and consistent differences in the preparation for the MIR among the 27 medical schools. Ranking in the exam, female and foreigner, help predict the choice of FCM. The FCM compulsory curriculum from three universities does not seem to exert any influence., Conclusions: The convenient yardstick competition between the schools of medicine, FCM in their curriculum and the emphasis on the most attractive attributes of the specialty can contribute to the necessary renewal of FCM., (Copyright © 2013 Elsevier España, S.L. All rights reserved.)

Objective: To identify patient- and practice-related factors associated with potential drug interactions., Methods: A register analysis study in general practices in the county of Funen, Denmark. Prescription data were retrieved from a population-based prescription database (Odense University Pharmacoepidemiologic Database, OPED) covering prescriptions to all inhabitants in the county of Funen, Denmark. All individuals exposed to concurrent use of two or more drugs (polypharmacy) were identified. Combinations of drugs with potential interactions were registered and classified as major, moderate, or minor, depending on the severity of outcome and the quality of documentation. A two-level random coefficient logistic regression model was used to investigate factors related to potential drug interactions., Results: One-third of the population was exposed to polypharmacy, and 6% were exposed to potential drug interactions during 1 year. Patient factors associated with increased risk of potential drug interactions were high age, a high number of concurrently used drugs, and a high number of prescribers. Practice factors associated with potential drug interactions were a high percentage of elderly patients and a low percentage of female patients listed., Conclusion: Prescription data may be useful in quality-improvement programmes to identify groups of patients and practices at increased risk of drug interactions.