Predictors of remote practice location in the first seven cohorts of James Cook University MBBS graduates
Citation: Woolley T, Sen Gupta T, Bellei M. Predictors of remote practice location in the first seven cohorts of James Cook University MBBS graduates. Rural and Remote Health (Internet) 2017; 17: 3992. Available: http://www.rrh.org.au/articles/subviewnew.asp?ArticleID=3992 (Accessed 24 October 2017). DOI: https://doi.org/10.22605/RRH3992
Introduction: This article describes factors predicting James Cook University (JCU) medical graduates undertaking at least 1 year of remote practice. The cross-sectional design involved point-in-time (2015) analysis of the JCU medical school’s ongoing longitudinal graduate tracking database. Participants were the first seven cohorts of graduates from the JCU medical school who had completed at least their postgraduate year (PGY) 4 in Australia (n=529); that is, PGY 4 to PGY 10 graduates.Key words: Australia, medical, practice, predictors, workforce.
Methods: Multiple logistic regression and Classification and Regression Tree (CART) analysis of medical graduate application data (age, gender, hometown, interview score, ethnicity), undergraduate data (scholarships awarded, clinical school location) and postgraduation data (internship location, specialty training) was performed. Analysis identified independent predictors of having practised for at least 1 year in a ‘remote’ Australian town (Australian Standard Geographic Classification Remoteness Area 4–5).
Results: Forty-seven (9%) of JCU Bachelor of Medicine and Bachelor of Surgery graduates in the first seven cohorts had practised for at least 1 year in a remote location between PGY 4 and 10. Practice in a ‘remote’ town was predicted by undertaking rural generalist training (p<0.001; prevalence odds ratio (POR)=17.0), being awarded an ‘above average’ interview score at medical school selection (p=0.006; POR=5.1), attending the Darwin clinical school in years 5–6 (p=0.005; POR=4.7), being female (p=0.016, POR=3.6) and undertaking an outer-regional or remotely based internship (p=0.006; POR=3.5). CART analysis identified Indigenous graduates as another key subgroup of remote practice graduates.
Conclusions: This study provides the first Australian evidence that likelihood of remote medical practice is enhanced by investment in a ‘remote pipeline’ – medical education via clinical schools and internships in rural/remote locations, with a later option of a rural generalist pathway. The proportion of medical graduates working in remote practice may also be increased by preferentially selecting Indigenous Australian applicants and applicants who score highly for communication, teamwork, self-reliance and motivation for rural and remote practice.
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