How common is multiple general practice attendance in Australia?
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Australians can seek general practice care from multiple general practitioners (GPs) in multiple locations. This provides high levels of patient choice but may reduce continuity of care. The aim of this study was to estimate the prevalence of attendance at multiple general practices in Australia, and identify patient characteristics associated with multiple practice attendances. METHOD: A cross-sectional survey of 2477 Australian adults was conducted online in July 2013. Respondents reported whether they had attended more than one general practice in the past year, and whether they had a usual general practice and GP. Demographic information, health service use and practice characteristics were also obtained from the survey. RESULTS: Over one-quarter of the sample reported attending more than one practice in the previous year. Multiple practice attendance is less common with increasing age, and less likely for survey respondents from regional Australia, compared with respondents from metropolitan areas. Multiple practice attenders are just as likely as single practice attenders to have a usual GP. DISCUSSION: A significant proportion of general practice care is delivered away from usual practices. This may have implications for health policy, in terms of continuity and quality of primary care.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".