Patient trade-offs between continuity and access in primary care interprofessional teaching clinics in Canada: a cross-sectional survey using discrete choice experiment
Bibliographic record
Abstract
OBJECTIVE: Timely access to care and continuity with a specific provider are important determinants of patient satisfaction when booking appointments in primary care settings. Advanced access booking systems restrict the majority of providers' appointment spots for same-day appointments and keep the number of prebooked appointments to a minimum. In the teaching clinic environment, continuity with the same provider can be a challenge. This study examines trade-offs that patients may consider during appointment bookings for six different clinical scenarios across a number of key access and continuity attributes using a discrete choice experiment (DCE) method. DESIGN: Cross-sectional survey. SETTING: Two urban family medicine teaching clinics in Canada. PARTICIPANTS: Convenience sample of 430 patients of family medicine clinics aged 18 and older. INTERVENTION: Discrete choice conjoint experiment survey. PRIMARY OUTCOME MEASURES: Patient preferences on six attributes: appointment booking method, appointment wait time, time spent in the waiting room, appointment time convenience, familiarity with healthcare provider and position of healthcare provider. Data were analysed by hierarchical Bayes analysis to determine estimates of part-worth utilities for each respondent. RESULTS: Patients rated appointment wait time as the most highly valued attribute, followed by position of provider, then familiarity with the provider. Patients showed a significant preference (p<0.02) for their own physician for booking of routine annual check-ups and other logical preferences across attributes overall and by clinical scenario. CONCLUSIONS: Patients preferred timely access to their primary care team over other attributes in the majority of health state scenarios tested, especially urgent issues, however they were willing to wait for a check-up. These results support the notion that advanced access booking systems which leave the majority of appointment spots for same day access and still leave a few for continuity (check-up) bookings, align well with trends in patient preferences.
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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 | 0.005 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".