Accessible and continuous primary care may help reduce rates of emergency department use. An international survey in 34 countries
Bibliographic record
Abstract
BACKGROUND: Part of the visits to emergency departments (EDs) is related to complaints that may well be treated in primary care. OBJECTIVES: (i) To investigate how the likelihood of attending an ED is related to accessibility and continuity of primary care. (ii) To investigate the reasons for patients to visit EDs in different countries. METHODS: Data were collected within the EU Seventh Framework project Quality and Costs in Primary Care (QUALICOPC) in 31 European countries, Australia, New Zealand and Canada. The data were collected between 2011 and 2013 and contain survey data from 60991 patients and 7005 GPs, within 7005 general practices. OUTCOME MEASURE: whether the patient visited the ED in the previous year (yes/no). Multilevel logistic regression analyses were carried out to analyse the data. RESULTS: Some 29.4% had visited the ED in the past year. Between countries, the percentages varied between 18% and 40%. ED visits show a significant and negative relation with better accessibility of primary care. Patients with a regular doctor who knows them personally were less likely to attend EDs. Only one-third of all patients who visited an ED indicated that the main reason for this was that their complaint could not be treated by a GP. CONCLUSIONS: Good accessibility and continuity of primary care may well reduce ED use. In some countries, it may be worthwhile to invest in more continuous relationships between patients and GPs or to eliminate factors that hamper people to use primary care (e.g. for costs or travelling).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".