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      Measuring inequalities in the distribution of the Fiji Health Workforce

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          Abstract

          Background

          Despite the centrality of health personnel to the health of the population, the planning, production and management of human resources for health remains underdeveloped in many low- and middle-income countries (LMICs). In addition to the general shortage of health workers, there are significant inequalities in the distribution of health workers within LMICs. This is especially true for countries like Fiji, which face major challenges in distributing its health workforce across many inhabited islands.

          Methods

          In this study, we describe and measure health worker distributional inequalities in Fiji, using data from the 2007 Population Census, and Ministry of Health records of crude death rates and health workforce personnel. We adopt methods from the economics literature including the Lorenz Curve/Gini Coefficient and Theil Index to measure the extent and drivers of inequality in the distribution of health workers at the sub-national level in Fiji for three categories of health workers: doctors, nurses, and all health workers (doctors, nurses, dentists and health support staff). Population size and crude death rates are used as proxies for health care needs.

          Results

          There are greater inequalities in the densities of health workers at the provincial level, compared to the divisional level in Fiji – six of the 15 provinces fall short of the recommended threshold of 2.3 health workers per 1,000 people. The estimated decile ratios, Gini co-efficient and Thiel index point to inequalities at the provincial level in Fiji, mainly with respect to the distribution of doctors; however these inequalities are relatively small.

          Conclusion

          While populations with lower mortality tend to have a slightly greater share of health workers, the overall distribution of health workers on the basis of need is more equitable in Fiji than for many other LMICs. The overall shortage of health workers could be addressed by creating new cadres of health workers; employing increasing numbers of foreign doctors, including specialists; and increasing funding for health worker training, as already demonstrated by the Fiji government. Close monitoring of the equitable distribution of additional health workers in the future is critical.

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          Most cited references30

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          Measuring the health-related Sustainable Development Goals in 188 countries: a baseline analysis from the Global Burden of Disease Study 2015

          Summary Background In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015). Methods We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices. Findings In 2015, the median health-related SDG index was 59·3 (95% uncertainty interval 56·8–61·8) and varied widely by country, ranging from 85·5 (84·2–86·5) in Iceland to 20·4 (15·4–24·9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r 2=0·88) and the MDG index (r 2=0·92), whereas the non-MDG index had a weaker relation with SDI (r 2=0·79). Between 2000 and 2015, the health-related SDG index improved by a median of 7·9 (IQR 5·0–10·4), and gains on the MDG index (a median change of 10·0 [6·7–13·1]) exceeded that of the non-MDG index (a median change of 5·5 [2·1–8·9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened. Interpretation GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs. Funding Bill & Melinda Gates Foundation.
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            Human resources for health: overcoming the crisis.

            In this analysis of the global workforce, the Joint Learning Initiative-a consortium of more than 100 health leaders-proposes that mobilisation and strengthening of human resources for health, neglected yet critical, is central to combating health crises in some of the world's poorest countries and for building sustainable health systems in all countries. Nearly all countries are challenged by worker shortage, skill mix imbalance, maldistribution, negative work environment, and weak knowledge base. Especially in the poorest countries, the workforce is under assault by HIV/AIDS, out-migration, and inadequate investment. Effective country strategies should be backed by international reinforcement. Ultimately, the crisis in human resources is a shared problem requiring shared responsibility for cooperative action. Alliances for action are recommended to strengthen the performance of all existing actors while expanding space and energy for fresh actors.
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              Using Gini-style indices to evaluate the spatial patterns of health practitioners: theoretical considerations and an application based on Alberta data.

              The paper analyzes how Gini-style indices are optimally used in the evaluation of economic spatial models designed to predict where health care practitioners are likely to locate under competitive market conditions. At a conceptual level, the analysis establishes that Gini-style indices can be brought to bear on economic models, only if the ordering of geographic areas required to give Gini-coefficient values internal technical coherence also has meaning in terms of the conceptual predictions of the modelling. This, in turn, implies that Gini-indices are most likely to prove useful for fairly aggregated forms of economic analysis, involving relatively few and large geographic divisions. At an applied level, the analysis establishes that one particular geographic distribution of health practitioners is empirically dominant, and that is the distribution which involves the lowest practitioner:population ratio in rural areas, and the highest ratio in large urban areas, with the ratio for small urban areas in between. The empirical evidence also suggests that the spatial practitioner distributions are highly stable for most kinds of health personnel, making it problematic whether these distributions can be changed through normal types of public policy interventions.
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                Author and article information

                Contributors
                Virginia.Wiseman@lshtm.ac.uk
                m.lagarde@lse.ac.uk
                n.batura@ucl.ac.uk
                Sophia.lin@unsw.edu.au
                Wayne.Irava@fnu.ac.fj
                Graham.Roberts@hrda.com.au
                Journal
                Int J Equity Health
                Int J Equity Health
                International Journal for Equity in Health
                BioMed Central (London )
                1475-9276
                30 June 2017
                30 June 2017
                2017
                : 16
                : 115
                Affiliations
                [1 ]ISNI 0000 0004 0425 469X, GRID grid.8991.9, Department of Global Health and Development, , London School of Hygiene & Tropical Medicine, ; London, WC1E 7HT UK
                [2 ]ISNI 0000 0004 4902 0432, GRID grid.1005.4, School of Public Health and Community Medicine, , University of New South Wales, ; Kensington, NSW 2033 Australia
                [3 ]ISNI 0000 0001 0789 5319, GRID grid.13063.37, , London School of Economics and Political Science, ; Houghton Street, London, WC2A 2AE UK
                [4 ]ISNI 0000000121901201, GRID grid.83440.3b, , Institute for Global Health, University College London, ; Gower St, Kings Cross, London, WC1E 6BT UK
                [5 ]ISNI 0000 0004 0455 8044, GRID grid.417863.f, Centre for Health Information Policy & Systems Research, , College of Medicine Nursing and Health Sciences, Fiji National University, ; Suva, Fiji
                [6 ]Human Resources for Development Alliance, PO Box 10570, Laucala Beach Suva, Fiji
                Article
                575
                10.1186/s12939-017-0575-1
                5493125
                28666460
                a00ddfa3-a47e-4828-a4f6-6c21a84e1649
                © The Author(s). 2017

                Open AccessThis 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. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 7 February 2017
                : 5 May 2017
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Health & Social care
                health workers,equity,human resources for health,distributional inequalities

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