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Objective: This study aimed to examine changes in the demographics and regions of work of Australian doctors over a period of 9 years. Methods: A retrospective study of Australian Health Practitioner Regulation Agency (AHPRA) registration data was performed. Data were sourced from the Health Workforce Dataset Online Data Tool which was derived from annual registration data from AHPRA for 2013–2022. The demographic factors analysed were gender, age, and origin of qualification. Regions of work were defined using the Modified Monash (MM) model. Results: The number of registered doctors increased from 82,408 in 2013 to 111,908 in 2022 but mean hours worked per week decreased from 41 to 39 leading up to 2020. Trends in age and origin of qualification remained stable, but the proportion of female workers increased from 38.5% in 2013 to 44.5% in 2022. While female hours per week (~37) were consistent from 2013 to 2020, male hours per week decreased from 43 to 41. The number of registrations and total full-time equivalent (FTE) outcomes increased consistently in metropolitan (MM1) and rural (MM2–5) regions but did not increase for remote and very remote (MM6–7) regions. Conclusion: The Australian medical workforce both grew and changed between 2013 and 2022. An overall decrease in mean hours worked appears to be driven by a decline in hours worked by male workers and the increased proportion of female workers. While increased gender parity and a decrease in hours worked per week were positive outcomes, a lack of growth in the medical workforce was noted in remote and very remote regions of Australia. What is known about the topic? Changes in the medical workforce over time are likely to impact health service delivery. What does this paper add? This paper examined changes in the gender, age, origin of qualification, and the region of work of Australia's medical workforce from 2013 to 2022. What are the implications for practitioners? An increase in gender parity and a decrease in the mean hours worked suggests improvements in workforce participation and sustainability, but lack of growth in medical workforce was noted in remote and very remote regions of Australia. [ABSTRACT FROM AUTHOR]

Introduction: The shortfall in medical workers in rural and remote Australia has led to health discrepancies in these regions. The University of Wollongong's medical program was designed to encourage graduates to work in these regions to address this shortfall. Objective: To compare rural and regional locations of work and choices of speciality between University of Wollongong's graduates and graduates from all Australian universities. Design: We conducted a longitudinal analysis on data available from the Medical Schools Outcome database, with graduate exit surveys linked to registrations of location and speciality. Rural and remote locations were identified as MM2‐7 regions using the Modified Monash Model. In total, 716 graduates from the University of Wollongong and 26 915 graduates from all Australian medical schools completed the MSOD exit survey in 2010‐2021 and registered with the Australian Health Practitioner Regulation Agency in 2022. The main outcome was the relative likelihood (relative risk) of cohorts working in rural and regional areas and of cohorts choosing general practice as their speciality. Findings: University of Wollongong's medical graduates were 1.51 times or 51% more likely to work in regional or rural areas (RR 1.51, 95% CI 1.34 to 1.71, p < 0.0001). Respondents who were 10 or more years post graduation were 1.57 times or 57% more likely to specialise in general practice than all other Australian medical graduates (RR 1.57 95% CI: 1.40 to 1.79, p < 0.0001). Discussion: The University of Wollongong's medical school is producing graduates to meet Australia's rural health workforce needs. This may be due to a higher intake of rural students, and a higher percentage of students taking rural placements. Conclusions: Rural health workforce needs can be addressed through rural‐focussed education strategies. [ABSTRACT FROM AUTHOR]

Introduction: Addressing the imbalance of the health workforce between metropolitan and rural areas requires a clear understanding of trends in choices of work location of health care staff. Objective: Here, we provide an automated and highly reproducible protocol to examine the location of health care workers over multiple years using medical graduates as a case study. Design: Data linkage cohort study. The study cohort examined was University of Wollongong Medical graduates from 2010 to 2021 who were registered to practice in Australia. The main outcome measure was graduate location of practice in Modified Monash regsions MM1 or MM2–7 across multiple postgraduate years. This protocol used R Markdown. Findings: An automated and reproducible protocol was used to analyse choices of work location for the University of Wollongong's medical graduates. Over 90% of graduates were registered with AHPRA. Around 25%–30% of graduates were found to work in MM2–7 regions across their careers, exceeding the national average. Discussion: The protocol presented allows for a fast and reproducible analysis of work location by region for health care workers. This will allow comparisons of outcomes between universities or health professions. [ABSTRACT FROM AUTHOR]

Introduction: Many strategies have been implemented to address the shortage of medical practitioners in rural areas. One such strategy, the Rural Clinical School Program supporting 18 rural clinical schools (RCSs), represents a substantial financial investment by the Australian Government. This is the first collaborative RCS study summarising the rural work outcomes of multiple RCSs. The aim of this study was to combine data from all RCSs' 2011 graduating classes to determine the association between rural location of practice in 2017 and (i) extended rural clinical placement during medical school (at least 12 months training in a rural area) and (ii) having a rural background. Methods: All medical schools funded under the RCS Program were contacted by email about participation in this study. Deidentified data were supplied for domestic students about their gender, origin (rural background defined as having lived in an Australian Standard Geographic Classification-Remoteness Area (ASGC-RA) 2–5 area for at least 5 years since beginning primary school) and participation in extended rural clinical placement (attended an RCS for at least 1 year of their clinical training). The postcode of their practice location according to the publicly available Australian Health Practitioner Regulation Agency (AHPRA) register was collected (February to August 2017) and classified into rural and metropolitan areas using the ASGC 2006 and the more recent Modified Monash Model (MMM). The main outcome measure was whether graduates were working in a ‘rural’ area (ASGC categories RA2–5 or MMM categories 3–7) or ‘metropolitan’ area. Pearson’s χ test was used to detect differences in gender, rural background and extended placement at an RCS between rural and metropolitan practice locations. Binary logistic regression was used to determine odds of rural practice and 95% confidence intervals (CIs) were calculated. Results: Although data were received from 14 universities, two universities had not started collecting origin data at this point so were excluded from the analysis. The proportion of students with a rural background had a range of 12.3–76.6% and the proportion who had participated in extended RCS placement had a range of 13.7–74.6%. Almost 17% (16.6%) had a principal practice postcode in a rural area (according to ASGC), range 5.8–55.6%, and 8.3% had a principal practice postcode in rural areas (according to MMM 3–7), range 4.5–29.9%. After controlling for rural background, it was found that students who attended an RCS were 1.5 times more likely to be in rural practice (95%CI 1.2–2.1, p=0.004) using ASGC criteria. Using the MMM 3–7 criteria, students who participated in extended RCS placement were 2.6 times as likely to be practising in a rural location (95%CI 1.8–3.8, p<0.001) after controlling for rural background. Regardless of geographic classification system (ASGC, MMM) used for location of practice and of student background (metropolitan or rural), those students with an extended RCS had an increased chance of working rurally. Conclusion: Based on the combined data from three-quarters (12/16) of the Australian medical schools who had a graduating class in 2011, this suggests that the RCS initiative as a whole is having a significant positive effect on the regional medical workforce at 5 years post-graduation. [ABSTRACT FROM AUTHOR]

Objective: This study aims to determine the associations between specialty type and practice location at postgraduate year 10 (PGY10), matched with PGY5 and PGY8 work locations, and earlier rural exposure/experience., Design and Setting: A cohort study of medicine graduates from nine Australian universities., Participants: 1220 domestic medicine graduates from the class of 2011., Outcome Measures: Practice location recorded by the Australian Health Practitioner Regulation Agency in PGY10; matched graduate movement between PGYs 5, 8 and 10 as classified by the Modified Monash Model, stratified by specialty type (predominantly grouped as general practitioner (GP) or non-GP)., Results: At PGY10, two-thirds (820/1220) had achieved fellowship. GPs were 2.8 times more likely to be in non-metropolitan practice (28% vs 12%; 95% CI 2.0 to 4.0, p<0.001) than graduates with non-GP (all other) specialist qualifications. More than 70% (71.4%) of GPs who were in non-metropolitan practice in PGY5 remained there in both PGY8 and PGY10 versus 29.0% of non-GP specialists and 36.4% of non-fellowed graduates (p<0.001). The proportion of fellowed graduates observed in non-metropolitan practice was 14.9% at PGY5, 16.1% at PGY8 and 19.0% at PGY10, with this growth predominantly from non-GP specialists moving into non-metropolitan locations, following completion of metropolitan-based vocational training., Conclusions: There are strong differences in practice location patterns between specialty types, with few non-GP specialists remaining in non-metropolitan practice between PGY5 and PGY10. Our study reinforces the importance of rural training pathways to longer-term work location outcomes and the need to expand specialist vocational training which supports more rural training opportunities for trainees outside general practice., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: This study was undertaken to improve assessment practice on OSCEs through collaboration across geographically dispersed medical schools in Australia., Methods: A total of eleven OSCE stations were co-developed by four medical schools and used in summative 2011 and 2012 examinations for the assessment of clinical performance in the early clinical and exit OSCEs in each school's medical course. Partial Credit Rasch Model was used to evaluate the psychometric properties of the shared OSCE data. Evaluation of the quality assurance reports was used to determine the beneficial impact of the collaborative benchmarking exercise on learning and teaching outcomes., Results: The data for each examination demonstrated sufficient fit to the Rasch model with infit mean square values ranging from 0.88 to 0.99. Person separation (1.25-1.63) indices indicated good reliability. Evaluation of perceived benefits showed that the benchmarking process was successful as it highlighted common curriculum areas requiring specific focus and provided comparable data on the quality of teaching at the participating medical schools., Conclusion: This research demonstrates the validity of the psychometric data and benefits of evaluating clinical competence across medical schools without the enforcement of a prescriptive national curriculum or assessment.