Determining the distance patterns in the movements of future doctors in UK between 2002 and 2015: a retrospective cohort study - Jonathan M Read; Colin Melville; Luigi Sedda; Daniel Thomas Smith; Lucy Hitchings; Ben Fleet (BMJ Open, 2024)
Objective To determine and identify distance patterns in the movements of medical students and junior doctors between their training locations.Design A retrospective cohort study of UK medical students from 2002 to 2015 (UKMED data).Setting All UK medical schools, foundations and specialty training organisation.Participants All UK medical students from 2002 to 2015, for a total of 97 932 participants.Outcome measures Individual movements and number of movements by county of students from family home to medical school training, from medical school to foundation training and from foundation to specialty training.Methods Leslie matrix, principal components analysis, Gini coefficient, χ2 test, generalised linear models and variable selection methods were employed to explore the different facets of students’ and junior doctors’ movements from the family home to medical school and for the full pathway (from family home to specialty training).Results The majority of the movements between the different stages of the full pathway were restricted to a distance of up to 50 km; although the proportion of movements changed from year-to-year, with longer movements during 2007–2008. At the individual level, ethnicity, socioeconomic class of the parent(s) and the deprivation score of the family home region were found to be the most important factors associated with the length of the movements from the family home to medical school. Similar results were found when movements were aggregated at the county level, with the addition of factors such as gender and qualification at entry (to medical school) being statistically associated with the number of new entrant students moving between counties.Conclusion Our findings show that while future doctors do not move far from their family home or training location, this pattern is not homogeneous over time. Distances are influenced by demographics, socioeconomic status and deprivation. These results may contribute in designing interventions aimed at solving the chronic problems of maldistribution and underdoctoring in the UK.