Enablers and barriers to the implementation of primary health care interventions for Indigenous people with chronic diseases: a systematic review
Bibliographic record
Abstract
BACKGROUND: Access to appropriate, affordable, acceptable and comprehensive primary health care (PHC) is critical for improving the health of Indigenous populations. Whilst appropriate infrastructure, sufficient funding and knowledgeable health care professionals are crucial, these elements alone will not lead to the provision of appropriate care for all Indigenous people. This systematic literature review synthesised international evidence on the factors that enable or inhibit the implementation of interventions aimed at improving chronic disease care for Indigenous people. METHODS: A systematic review using Medical Literature Analysis and Retrieval System Online (MEDLINE) (PubMed platform), Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Excerpta Medica Database (EMBASE), ATSIHealth, Australian Indigenous HealthInfoNet via Informit Online and Primary Health Care Research and Information Service (PHCRIS) databases was undertaken. Studies were included if they described an intervention for one or more of six chronic conditions that was delivered in a primary health care setting in Australia, New Zealand, Canada or the United States. Attitudes, beliefs, expectations, understandings and knowledge of patients, their families, Indigenous communities, providers and policy makers were of interest. Published and unpublished qualitative and quantitative studies from 1998 to 2013 were considered. Qualitative findings were pooled using a meta-aggregative approach, and quantitative data were presented as a narrative summary. RESULTS: Twenty three studies were included. Meta-aggregation of qualitative data revealed five synthesised findings, related to issues within the design and planning phase of interventions, the chronic disease workforce, partnerships between service providers and patients, clinical care pathways and patient access to services. The available quantitative data supported the qualitative findings. Three key features of enablers and barriers emerged from the findings: (1) they are not fixed concepts but can be positively or negatively influenced, (2) the degree to which the work of an intervention can influence an enabler or barrier varies depending on their source and (3) they are inter-related whereby a change in one may effect a change in another. CONCLUSIONS: Future interventions should consider the findings of this review as it provides an evidence-base that contributes to the successful design, implementation and sustainability of chronic disease interventions in primary health care settings intended for Indigenous people.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.035 | 0.115 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".