Why Community Health Systems Have Not Flourished in High Income Countries: What the Australian Experience Tells Us
Bibliographic record
Abstract
BACKGROUND: Despite the value of community health systems, they have not flourished in high income countries and there are no system-wide examples in high income countries where community health is regarded as the mainstream model. Those that do exist in Australia, Canada, the United States and the United Kingdom provide examples of comprehensive primary healthcare (PHC) but are marginal to bio-medical primary medical care. The aim of this paper is to examine the factors that account for the absence of strong community health systems in high income countries, using Australia as an example. METHODS: Data are drawn from two Australian PHC studies led by the authors. One examined seven case studies of community health services over a five-year period which saw considerable health system change. The second examined regional PHC organisations. We conducted new analysis using the 'three I's' framework (interests, institutions, ideas) to examine why community health systems have not flourished in high-income countries. RESULTS: The elements of the community health services that provide insights on how they could become the basis of an effective community health system are: a focus on equity and accessibility, effective community participation/control; multidisciplinary teamwork; and strategies from care to health promotion. Key barriers identified were: when general practitioners (GPs) were seen to lead rather than be part of a team; funding models that encourage curative services rather than disease prevention and health promotion; and professional and medical dominance so that community voices are drowned out. CONCLUSION: Our study of the community health system in Australia indicates that instituting such a system in high income countries will require systematic ideological, political and institutional change to shift the overarching government policy environment, and health sector policies and practices towards a social model of health which allows community control, and multidisciplinary service provision.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".