Academic family health teams: Part 2: patient perceptions of access.
Bibliographic record
Abstract
OBJECTIVE: To explore patients' perceptions of primary care (PC) in the early development of academic family health teams (aFHTs)--interprofessional PC teams delivering care where family medicine and other health professional learners are trained--focusing on patients' perceptions of access and patients' satisfaction with services. DESIGN: Self-administered survey. SETTING: Six aFHTs in Ontario. PARTICIPANTS: Adult patients attending appointments and administrators at each of the aFHTs. MAIN OUTCOME MEASURES: Answers to questions about access from the Primary Care Assessment Tool Adult Expanded Version, the Primary Care Assessment Survey, and research team questions. RESULTS: The response rate was 47.3% (1026 of 2167). The mean (SD) Primary Care Assessment Tool first-contact accessibility score was 2.28 (0.36) out of 4, with 96.5% of patients rating access less than 3, which was the minimum expected level of care. Two-thirds (66.6%) indicated someone from their aFHTs would definitely or probably see them the same day if they were sick, 56.8% could definitely or probably get advice quickly by telephone, and 14.5% indicated it was definitely or probably difficult to be seen by their primary health care provider (HCP). Additionally, 46.9% indicated they would like to get medical advice by e-mail. For a routine or follow-up visit, 73.4% would be willing to see another aFHT physician if their regular provider were unavailable, while only 48.3% would see a nonphysician HCP. If sick, 88.2% would see another aFHT physician and 55.2% would see a nonphysician HCP. Most (75.3%) were satisfied with access to their regular HCP. CONCLUSION: Although patients are generally satisfied with care, there is room for improvement in access. Strategies are needed to enhance access to care, including addressing appropriate roles and scopes of practice for nonphysician HCPs. The accessibility challenges for aFHTs will likely affect new family physicians and other HCPs training in these practices and their approach to future practice.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".