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Health workforce supply and geographical maldistribution are amongst the most important issues affecting the provision of accessible primary health care services and improving the equity of health outcomes for populations living in rural and remote areas throughout the world. It is crucial that policymakers attempting to redress these issues have accurate and timely information so that workforce planning and policy-making is well-informed. In particular, it is critical that policy interventions effectively optimise the turnover and retention of the existing rural and remote primary health care workforce, as these are frequently a scarce and valuable resource. The aim of this research, therefore, is to understand the patterns, determinants and metrics of rural and remote Australian primary health care workforce turnover and retention, with a view to developing appropriate indicators and benchmarks to support rural and remote health service workforce retention and inform rural and remote health workforce policy-making. The research of this thesis takes a quantitative approach to investigate rural health workforce turnover and retention. Firstly, five metrics, well suited for measuring turnover and retention in rural and remote Australian contexts, are identified. These include simple metrics, such as turnover rates and retention rates, as well as metrics requiring more advanced analytical capabilities, such as survival probabilities and proportional hazards ratios. These metrics, particularly those calculated using survival analysis, are applied to five different Australian rural and remote primary health care workforce datasets to explore how rural primary health care workforce retention differs according to profession, geographical location, population size and a range of other financial and economic, professional and organisational, educational and regulatory, and personal and family factors. The empirical findings are then used to derive tentative benchmarks for length of stay of primary health care professionals that differ according to profession and geographic location. This research reveals substantial and significant differences in rural and remote Australian primary health care workforce retention according to profession and geographical location and population size. Doctors and allied health professionals have approximately 1.80 times the risk of leaving a rural or remote health service at any point in time compared with nurses and Aboriginal health workers. Substantial differences in retention are evident within the allied health professions. Podiatrists, for example, are more than twice as likely to leave compared to occupational therapists (Hazard Ratio 2.13). The risk of rural and remote GPs leaving small communities (population size<5,000) also increases with increasing geographical remoteness (Outer regional Hazard Ratio 1.33; Remote Hazard Ratio 2.65, compared to Inner regional GPs). Additionally, the research of this thesis reveals that a range of professional and organisational variables are strongly associated with rural primary health care workforce retention. These include practice ownership, hospital appointments and undertaking advanced procedural activities (for GPs) and grade of employment (for Allied Health Professionals). Income source, health workers' age group, country of primary training and regulatory restrictions on practice location are each strongly associated with retention. The research also proposes tentative benchmarks for the retention of rural Australian primary health care workers that differ according to profession and geographical location. The median survival of rural NSW GPs is predicted according to geographical location and population size, coastal location, country of primary medical degree, and certain workload characteristics. Aside from better understanding rural and remote PHC workforce retention patterns and determinants, the research of this thesis has extensive and broad-ranging policy implications. At the most fundamental level, the use and demonstration of how best to measure retention in the rural and remote PHC context is critical for informing future research, for future evaluation and monitoring of retention interventions, and for the collection and management of workforce data. Importantly, the new empirical knowledge generated by this research has also highlighted the need to modify national workforce retention policy to take both geographical location (remoteness) and population size into account when targeting retention incentives, as was recommended by the 2013 "Review of Australian Government Health Workforce Programs". Further, the findings suggest that strengthening and expanding rural generalist pathways providing advanced procedural training and up-skilling of rural and remote GPs may support their long-term retention, as may the funding and support of rural and remote hospital infrastructure. Retention of Allied Health Professionals in rural and remote communities can be supported by developing specific rural and remote career pathways. Finally, coercive recruitment mechanisms can be expected to be associated with higher retention whilst the coercion is in place, but a substantially increased risk of leaving once the period of coercion ends. Mitigating the risk that PHC workers fulfilling return-of-service obligations may exacerbate retention of rural and remote PHC workforce in the longer term is likely to require careful matching of individuals to the location in which they fulfil their obligations and ongoing investment in vocational training and professional support programs.

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How accurate are political opinion polls in multiparty elections? Many countries have proportional representation systems with low vote thresholds for parliamentary representation. Germany has such a system, as do Israel, Poland, the Netherlands, New Zealand, Norway, Portugal, the Republic of Macedonia, Romania, and South Africa. Minor parties are a viable voting choice in these countries, resulting in multiparty elections. Despite this, there is little work on polling accuracy for multiparty elections. Political polling usually has three purposes: to forecast the outcome of an election; to understand voter behavior; and to inform campaign strategy (Hillygus, 2011). In multiparty elections, these imperatives remain, but with complications. The forecasting problem includes whether small parties will gain representation at all. Party supporters may engage in strategic voting to strengthen coalition partners (Meffert & Gschwend, 2011). If a party lies below the proportional representation threshold, supporters may change their vote to avoid wasting their ballot (Holtz-Bacha, 2012). Campaign strategy may take account of postelection coalitions; strategic voting may be encouraged to help a coalition partner above the threshold. Alternatively, campaigning against a minor party may drive it below the threshold, forcing it out of parliament, allowing successful parties to hold more seats. Therefore, to extend work on poll accuracy to multiparty elections, both empirical comparisons and methodological innovations are required. As an empirical base, the present work uses data from New Zealand, a developed western democracy that last held a general election in November 2011. New Zealand has a system of mixed member proportional representation with a threshold of 5% of the vote, resulting in multiparty elections. The present study demonstrates that New Zealand polls have comparable accuracy to those of other developed countries, making it a suitable context for the study of multiparty elections. It then extends formal accuracy analysis to minor parties, including very small parties. Finally, it develops a new method, using odds, to translate poll outcomes into forecasts that a party will cross the proportional representation threshold. Adapted from the source document.

Background: Doctor shortages in remote areas of Indonesia are amongst challenges to provide equitable healthcare access. Understanding factors associated with doctors' work location is essential to overcome geographic maldistribution. Focused analyses of doctors' early-career years can provide evidence to strengthen home-grown remote workforce development. Method: This is a cross-sectional study of early-career (post-internship years 1–5) Indonesian doctors, involving an online self-administered survey on demographic characteristics, and; locations of upbringing, medical clerkship (placement during medical school), internship, and current work. Multivariate logistic regression was used to test factors associated with current work in remote districts. Results: Of 3,176 doctors actively working as clinicians, 8.9% were practicing in remote districts. Compared with their non-remote counterparts, doctors working in remote districts were more likely to be male (OR 1.5,CI 1.1–2.1) or unmarried (OR 1.9,CI 1.3–3.0), have spent more than half of their childhood in a remote district (OR 19.9,CI 12.3–32.3), have completed a remote clerkship (OR 2.2,CI 1.1–4.4) or internship (OR 2.0,CI 1.3–3.0), currently participate in rural incentive programs (OR 18.6,CI 12.8–26.8) or have previously participated in these (OR 2.0,CI 1.3–3.0), be a government employee (OR 3.2,CI 2.1–4.9), or have worked rurally or remotely post-internship but prior to current position (OR 1.9,CI 1.2–3.0). Conclusion: Our results indicate that building the Indonesian medical workforce in remote regions could be facilitated by investing in strategies to select medical students with a remote background, delivering more remote clerkships during the medical course, deploying more doctors in remote internships and providing financial incentives. Additional considerations include expanding government employment opportunities in rural areas to achieve a more equitable geographic distribution of doctors in Indonesia.

BACKGROUND: Choosing the appropriate definition of rural area is critical to ensuring health resources are carefully targeted to support the communities needing them most. This study aimed at reviewing various definitions and demonstrating how the application of different rural area definitions implies geographic doctor distribution to inform the development of a more fit-for-purpose rural area definition for health workforce research and policies. METHODS: We reviewed policy documents and literature to identify the rural area definitions in Indonesian health research and policies. First, we used the health policy triangle to critically summarize the contexts, contents, actors and process of developing the rural area definitions. Then, we compared each definition's strengths and weaknesses according to the norms of appropriate rural area definitions (i.e. explicit, meaningful, replicable, quantifiable and objective, derived from high-quality data and not frequently changed; had on-the-ground validity and clear boundaries). Finally, we validated the application of each definition to describe geographic distribution of doctors by estimating doctor-to-population ratios and the Theil-L decomposition indices using each definition as the unit of analysis. RESULTS: Three definitions were identified, all applied at different levels of geographic areas: "urban/rural" villages (Central Bureau of Statistics [CBS] definition), "remote/non-remote" health facilities (Ministry of Health [MoH] definition) and "less/more developed" districts (presidential/regulated definition). The CBS and presidential definitions are objective and derived from nationwide standardized calculations on high-quality data, whereas the MoH definition is more subjective, as it allows local government to self-nominate the facilities to be classified as remote. The CBS and presidential definition criteria considered key population determinants for doctor availability, such as population density and economic capacity, as well as geographic accessibility. ...

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. ; Background Improving the health of rural populations requires developing a medical workforce with the right skills and a willingness to work in rural areas. A novel strategy for achieving this aim is to align medical training distribution with community need. This research describes an approach for planning and monitoring the distribution of general practice (GP) training posts to meet health needs across a dispersed geographic catchment. Methods An assessment of the location of GP registrars in a large catchment of rural North West Queensland (across 11 sub-regions) in 2017 was made using national workforce supply, rurality and other indicators. These included (1): Index of Access –spatial accessibility (2); 10-year District of Workforce Shortage (DWS) (3); MMM (Modified Monash Model) rurality (4); SEIFA (Socio-Economic Indicator For Areas) (5); Indigenous population and (6) Population size. Distribution was determined relative to GP workforce supply measures and population health needs in each health sub-region of the catchment. An expert panel verified the approach and reliability of findings and discussed the results to inform planning. Results 378 registrars and 582 supervisors were well-distributed in two sub-regions; in contrast the distribution was below expected levels in three others. Almost a quarter of registrars (24%) were located in the poorest access areas (Index of Access) compared with 15% of the population located in these areas. Relative to the population size, registrars were proportionally over-represented in the most rural towns, those consistently rated as DWS or those with the poorest SEIFA value and highest Indigenous proportion. Conclusions Current regional distribution was good, but individual town-level data further enabled the training provider to discuss the nuance of where and why more registrars (or supervisors) may be needed. The approach described enables distributed workforce planning and monitoring applicable in a range of contexts, with increased sensitivity for registrar distribution planning where most needed, supporting useful discussions about the potential causes and solutions. This evidence-based approach also enables training organisations to engage with local communities, health services and government to address the sustainable development of the long-term GP workforce in these towns.

OBJECTIVES: To evaluate the relationship between markers of staff employment stability and use of short-term healthcare workers with markers of quality of care. A secondary objective was to identify clinic-specific factors which may counter hypothesised reduced quality of care associated with lower stability, higher turnover or higher use of short-term staff. DESIGN: Retrospective cohort study (Northern Territory (NT) Department of Health Primary Care Information Systems). SETTING: All 48 government primary healthcare clinics in remote communities in NT, Australia (2011–2015). PARTICIPANTS: 25 413 patients drawn from participating clinics during the study period. OUTCOME MEASURES: Associations between independent variables (resident remote area nurse and Aboriginal Health Practitioner turnover rates, stability rates and the proportional use of agency nurses) and indicators of health service quality in child and maternal health, chronic disease management and preventive health activity were tested using linear regression, adjusting for community and clinic size. Latent class modelling was used to investigate between-clinic heterogeneity. RESULTS: The proportion of resident Aboriginal clients receiving high-quality care as measured by various quality indicators varied considerably across indicators and clinics. Higher quality care was more likely to be received for management of chronic diseases such as diabetes and least likely to be received for general/preventive adult health checks. Many indicators had target goals of 0.80 which were mostly not achieved. The evidence for associations between decreased stability measures or increased use of agency nurses and reduced achievement of quality indicators was not supported as hypothesised. For the majority of associations, the overall effect sizes were small (close to zero) and failed to reach statistical significance. Where statistically significant associations were found, they were generally in the hypothesised direction. CONCLUSIONS: Overall, minimal evidence of ...