Aeromedical retrievals as a measure of potentially preventable hospitalisations and cost comparison with provision of GP-led primary health care in a remote Aboriginal community
Bibliographic record
Abstract
INTRODUCTION: Kowanyama is a very remote Aboriginal community on the Cape York Peninsula of Far North Queensland, Australia. It is among the five most disadvantaged communities in Australia, with a very high burden of disease. It has access to 2.5 days each week of fly-in, fly-out, GP-led primary health care for a population of 1200. All patients requiring higher level care undergo aeromedical retrieval to a bigger centre. A retrospective clinical audit of charts was undertaken assessing aeromedical retrievals from Kowanyama for the year 2019 to assess whether GP access might correlate with retrievals or hospital admissions for potentially preventable conditions and whether it could be cost-effective and improve outcomes to provide the benchmarked staffing of GPs. METHODS: Using a tool made by the authors for this audit, the management and reason for evacuation were assessed against Queensland Health's Primary Clinical Care Manual guidelines, whether the presence of a rural generalist GP would have prevented the need for retrieval, and assessed against accepted Australian (and Canadian) criteria for potentially preventable hospital admissions. Each retrieval was then assessed as 'preventable' or 'not preventable'. The cost of providing benchmark levels of GPs in community was compared with the cost of potentially preventable retrievals. RESULTS: In 2019, there were 89 retrievals of 73 patients. Thirty-nine percent (35) of all retrievals occurred when a doctor was on site. Of preventable retrievals, 33% (18) occurred with a doctor on site and 67% (36) occurred with no doctor on site. All retrievals with a doctor on site resulted in an admission. All immediate discharges (10% (9)) or deaths (1% (1)) were for retrievals without a doctor on site. Sixty-one percent (54) of all retrievals were potentially preventable, with the two most common conditions being pneumonia - non vaccine preventable (18% (9)) and bacterial/unspecified (14% (7)). Thirty-two percent (20) of patients accounted for 52% (46) of retrievals and of these 63% (29) were potentially preventable (compared to 61% overall). For preventable condition retrievals, the mean number of visits to the clinic compared to non-preventable condition retrievals was higher for registered nurse or Aboriginal Health Worker visits (1.24 v 0.93) and lower for doctor visits (0.22 v 0.37). The conservatively calculated costs of retrievals matched the maximum cost of providing benchmark numbers (2.6 full-time equivalents) of rural generalist doctors in a rotating model for the audited community. CONCLUSION: Greater access to GP-led primary health care may lead to fewer retrievals/hospital admissions for potentially preventable conditions. It is likely that some preventable condition retrievals might be avoided if full coverage with benchmarked numbers of rural generalist GPs in a GP-led primary health team was provided in remote communities. This may be cost-effective and improve patient outcomes, and should be further explored.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".