背景:越来越多的证据支持向“发展自己的”招聘方式转变,培训和留住来自农村社区的卫生专业人员。为了实现这一点,有必要健全的方法,通过这些方法,大学可以准确地描述他们的地理重点区域,可以用来从他们的地区招募学生,并评估合作伙伴社区的劳动力成果。在澳大利亚,迪肯大学开展了一项由农村临床学校和大学农村卫生系资助的农村卫生多学科培训(RHMT)计划,目的是通过在维多利亚州西部和西南部提供农村临床实习来培养研究生卫生劳动力。在Deakin的医学博士课程中建立专门的农村培训流的愿望成为我们描述“农村足迹”的催化剂,这种方式可用于优先考虑当地学生的招聘以及评估专门针对该地区的研究生劳动力成果。
目标:在澳大利亚,选择农村学生依靠澳大利亚统计地理标准远程区域(ASGS-RA)或改良的莫纳什模型(MMM)为医学课程申请人分配农村背景身份,基于RHMT程序提供的标准定义。符合农村背景标准的申请人可以根据入学配额或全国各地的专用农村流优先进入任何医学院。直到最近,对毕业生劳动力成果的评估也使用了这些农村分类,但通常没有提到特定的地理区域。越来越多的国际证据支持基于地点的联系和培训的重要性,医学毕业生更有可能在他们来自或受过培训的地区工作。对于大学来说,农村学生的招聘与特定地理区域的培训更加战略性地保持一致,有必要制定准确的农村重点地区的地理定义,可以在招生过程中应用。
结论:当我们努力准确描述我们的农村活动区时,我们模拟了几个地理和其他框架的应用,包括MMM,ASGS-RA,初级医疗保健网络(PHN),地方政府区域(LGA),邮政编码和统计区。很明显,没有一个单一的地理或农村框架(1)准确地描述了我们的活动领域,(2)准确描述了我们期望的劳动力重点,(3)在录取过程中实际适用。我们最终决定使用PHN和MMM的组合来实现所需的特异性的定制方法。本报告提供了一个示例,说明如何准确描述并成功利用农村活动足迹来优先考虑地理区域的学生进行课程录取。分享了关于现有地理衡量标准的优势和局限性的经验教训。描述了精确足迹定义的应用,包括学生招募,评估一个地理区域的劳动力成果,对利益相关者关系的好处,以及更细致入微的RHMT报告的机会。
BACKGROUND: There is growing evidence supporting a shift towards \'grow your own\' approaches to recruiting, training and retaining health professionals from and for rural communities. To achieve this, there is a need for sound methodologies by which universities can describe their area of geographic focus in a precise way that can be utilised to recruit students from their region and evaluate workforce outcomes for partner communities. In Australia, Deakin University operates a Rural Health Multidisciplinary Training (RHMT) program funded Rural Clinical School and University Department of Rural Health, with the purpose of producing a graduate health workforce through the provision of rural clinical placements in western and south-western Victoria. The desire to establish a dedicated Rural Training Stream within Deakin\'s Doctor of Medicine course acted as a catalyst for us to describe our \'rural footprint\' in a way that could be used to prioritise local student recruitment as well as evaluate graduate workforce outcomes specifically for this region.
OBJECTIVE: In Australia, selection of rural students has relied on the Australian Statistical Geography Standard Remoteness Areas (ASGS-RA) or Modified Monash Model (MMM) to assign rural background status to medical course applicants, based on a standard definition provided by the RHMT program. Applicants meeting rural background criteria may be preferentially admitted to any medical school according to admission quotas or dedicated rural streams across the country. Until recently, evaluations of graduate workforce outcomes have also used these rurality classifications, but often without reference to particular geographic areas. Growing international evidence supports the importance of place-based connection and training, with medical graduates more likely to work in a region that they are from or in which they have trained. For universities to align rural student recruitment more strategically with training in specific geographic areas, there is a need to develop precise geographical definitions of areas of rural focus that can be applied during admissions processes.
CONCLUSIONS: As we strived to describe our rural activity area precisely, we modelled the application of several geographical and other frameworks, including the MMM, ASGS-RA, Primary Healthcare Networks (PHN), Local Government Areas (LGAs), postcodes and Statistical Areas. It became evident that there was no single geographical or rural framework that (1) accurately described our area of activity, (2) accurately described our desired workforce focus, (3) was practical to apply during the admissions process. We ultimately settled on a bespoke approach using a combination of the PHN and MMM to achieve the specificity required. This report provides an example of how a rural activity footprint can be accurately described and successfully employed to prioritise students from a geographical area for course admission. Lessons learned about the strengths and limitations of available geographical measures are shared. Applications of a precise footprint definition are described including student recruitment, evaluation of workforce outcomes for a geographic region, benefits to stakeholder relationships and an opportunity for more nuanced RHMT reporting.