Access to episodic primary care: a cross-sectional comparison of walk-in clinics and urgent primary care centers in British Columbia
Bibliographic record
Abstract
AIM: This study aimed to identify publicly reported access characteristics for episodic primary care in BC and provided a clinic-level comparison between walk-in clinics and UPCCs. BACKGROUND: Walk-in clinics are non-hospital-based primary care facilities that are designed to operate without appointments and provide increased healthcare access with extended hours. Urgent and Primary Care Centres (UPCCs) were introduced to British Columbia (BC) in 2018 as an additional primary care resource that provided urgent, but not emergent care during extended hours. METHODS: This cross-sectional study used publicly available data from all walk-in clinics and UPCCs in BC. A structured data collection form was used to record access characteristics from clinic websites, including business hours, weekend availability, attachment to a longitudinal family practice, and provision of virtual services. FINDINGS: In total, 268 clinics were included in the analysis (243 walk-in clinics, 25 UPCCs). Of those, 225 walk-in clinics (92.6%) and two UPCCs (8.0%) were attached to a longitudinal family practice. Only 153 (63%) walk-in clinics offered weekend services, compared to 24 (96%) of UPCCs. Walk-in clinics offered the majority (8,968.6/ 78.4%) of their service hours between 08:00 and 17:00, Monday to Friday. UPCCs offered the majority (889.3/ 53.7%) of their service hours after 17:00. CONCLUSION: Most walk-in clinics were associated with a longitudinal family practice and provided the majority of clinic services during typical business hours. More research that includes patient characteristics and care outcomes, analyzed at the clinic level, may be useful to support the optimization of episodic primary healthcare delivery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".