What effect do point of care fees have on childhood consultations in general practice?
Bibliographic record
Abstract
BACKGROUND: General practice (GP) has historically been central to the prevention and treatment of childhood illnesses. In Ireland, this role has recently expanded with the introduction of free GP care for children aged under six years in 2015. The Republic of Ireland has the only health system in the European Union which does not offer universal coverage for primary care. This study aims to analyse general practice records to investigate the effect of point of care consultation fees on childhood attendances. METHODS: GPs affiliated to the medical school (n = 72) were invited to participate. 100 children aged 1 to 14 years were randomly sampled from each. Data was collected on service utilisation in the previous 12 months, specifically: age, gender, eligibility for free care and whether they had consulted their GP in the 12 month period. RESULTS: Sixty-four practices participated, producing data on 6007 eligible children. The median age of children was seven years; 3688(62%) were 'fee-paying'. GMS patients aged under six years had a median of three consultations/year, with a quarter attending six times a year or more, while fee paying patients had a median of two consultations/year with a quarter attending four times a year or more. CONCLUSIONS: Children eligible for free care attend more often with a subgroup attending very frequently. This study provides important information on the possible impact of fees on healthcare utilisation for countries considering co-payment.
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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 | 0.008 | 0.102 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".