Introduction: This is an international study of the epidemiology of family medicine (FM) in three practice populations from the Netherlands, Malta and Serbia. Diagnostic associations between common reasons for encounter (RfEs) and episodes titles are compared and similarities and differences are described and analysed. Methodology: Participating family doctors (FDs) recorded details of all their patient contacts in an ‘episode of care (EoC)’ structure using the International Classification of Primary Care (ICPC). RfEs presented by the patient and episode titles (diagnostic labels of EoCs) were classified with ICPC. The relationships between RfEs and episode titles were studied with Bayesian methods. Results: Distributions of diagnostic odds ratios (ORs) from the three population databases are presented and compared. Conclusions: ICPC, the RfE and the EoC data model are appropriate tools to study the process of diagnosis in FM. Distributions of diagnostic associations between RfEs and episode titles in the Transition Project international populations show remarkable similarities and congruencies in the process of diagnosis from both the RfE and the episode title perspectives. The congruence of diagnostic associations between populations supports the use of such data from one population to inform diagnostic decisions in another. Differences in themagnitude of such diagnostic associations are significant, and population-specific data are therefore desirable. We propose that both an international (common) and a local (health care system specific) content of FM exist and that the empirical distributions of diagnostic associations presented in this paper are a reflection of both these effects. We also observed that the frequency of exposure to such diagnostic challenges had a strong effect on the confidence intervals of diagnostic ORs reflecting these diagnostic associations. We propose that this constitutes evidence that expertise in FM is associated with frequency of exposure to diagnostic challenges. ; Funding: The ...