Characteristics of Indigenous primary health care service delivery models: a systematic scoping review

Published online: 25 January 2018Background: Indigenous populations have poorer health outcomes compared to their non-Indigenous counterparts. The evolution of Indigenous primary health care services arose from mainstream health services being unable to adequately meet the needs of Indigenous communities and Indigenous peoples often being excluded and marginalised from mainstream health services. Part of the solution has been to establish Indigenous specific primary health care services, for and managed by Indigenous peoples. There are a number of reasons why Indigenous primary health care services are more likely than mainstream services to improve the health of Indigenous communities. Their success is partly due to the fact that they often provide comprehensive programs that incorporate treatment and management, prevention and health promotion, as well as addressing the social determinants of health. However, there are gaps in the evidence base including the characteristics that contribute to the success of Indigenous primary health care services in providing comprehensive primary health care. This systematic scoping review aims to identify the characteristics of Indigenous primary health care service delivery models. Method: This systematic scoping review was led by an Aboriginal researcher, using the Joanna Briggs Institute Scoping Review Methodology. All published peer-reviewed and grey literature indexed in PubMed, EBSCO CINAHL, Embase, Informit, Mednar, and Trove databases from September 1978 to May 2015 were reviewed for inclusion. Studies were included if they describe the characteristics of service delivery models implemented within an Indigenous primary health care service. Sixty-two studies met the inclusion criteria. Data were extracted and then thematically analysed to identify the characteristics of Indigenous PHC service delivery models. Results: Culture was the most prominent characteristic underpinning all of the other seven characteristics which were identified – accessible health services, community participation, continuous quality improvement, culturally appropriate and skilled workforce, flexible approach to care, holistic health care, and self-determination and empowerment. Conclusion: While the eight characteristics were clearly distinguishable within the review, the interdependence between each characteristic was also evident. These findings were used to develop a new Indigenous PHC Service Delivery Model, which clearly demonstrates some of the unique characteristics of Indigenous specific models.Stephen G. Harfield, Carol Davy, Alexa McArthur, Zachary Munn, Alex Brown and Ngiare Brow

Statistical consulting courses for undergraduates : fortune or folly?

This article presents an overview of three undergraduate-level statistical consulting courses being taught at institutions of different size (small, medium, and large). Topics that will be discussed include the evolution of these courses, thoughts on what makes such courses successful, potential pitfalls to watch for, the necessary minimal skills students should have to be successful in the courses, and thoughts on where these courses should appear in a statistics curriculum. This paper will provide an overview of the similarities and differences in the way applied consulting courses are presented within the three undergraduate programs

Statistical modeling of Southern Ocean marine diatom proxy and winter sea ice data : model comparison and developments

We compare the performance of the modern analog technique (MAT), the Imbrie and Kipp transfer function (IKTF), the generalized additive model (GAM) and weighted averaging partial least squares (WA PLS) on a southern hemisphere diatom relative abundance and winter sea ice concentration training data set. All relevant model assumptions are tested with a random 10-fold cross-validation, whilst a hold out cross-validation tested the explanatory power of each model on spatially independent validation data. We used auto correlograms on model residuals, variance partitioning, and principal coordinates analysis of neighbor matrices (PCNM) to investigate the importance of the spatial structure of our training database. A set of hierarchical logistic regression models (or Huisman–Olff–Fresco models) are used to infer the response of each diatom species along the winter sea ice gradient. Our analyses suggest that IKTF is an inappropriate sea ice estimation approach as its underlying statistical assumptions do not hold and the fit of IKTF to our data under cross-validation was poor. We conclude that MAT may be biased by spatial autocorrelation, and together with IKTF fails to provide unbiased estimates of winter sea ice. We find GAM and WA PLS are more appropriate than IKTF and MAT for the estimation of paleo winter sea ice cover throughout the Southern Ocean. However, as WA PLS is based on a unimodal species response, which is rarely exhibited by diatoms along the winter sea ice gradient, we ultimately advocate the application of GAM. GAM only uses diatoms with a statistically significant association, and ecologically based link, with sea ice. GAM outperformed all other models under cross-validation in terms of performance statistics, the fit of GAM to the training dataset and diagnostic tests for model assumptions. We also demonstrate that GAM provides a more detailed and potentially more accurate (based on a comparison with New Zealand and southeast Australian paleo climatic records) paleo winter sea ice record for the southwestern Pacific Ocean in comparison with IKTF, MAT and WA PLS.13 page(s