A taxonomy of patient experiences of access and continuity at team-based primary healthcare clinics
Bibliographic record
Abstract
Abstract Background Access to primary healthcare services is a core lever for reducing health inequalities. Population groups living with certain individual social characteristics are disproportionately more likely to experience barriers accessing care. This study identified profiles of access and continuity experiences of patients registered at team-based primary healthcare clinics and explored the associations of these profiles with individual and organizational characteristics. Methods A cross-sectional e-survey was conducted between September 2022 and April 2023. All registered adult patients with an email address at 104 team-based primary healthcare clinics in Quebec were invited to participate. Latent class analysis was used to identify patient profiles based on nine components of access to care and continuity experiences. Multinomial logistic regression models were fit to analyze each profile’s association with ten characteristics related to individual sociodemographics and two related to clinic area and size. Results Based on 87,155 patient experiences, four profiles were identified. "Easy access and continuity" (42% of respondents) was characterized by ease in almost all access and continuity components. Three profiles were characterized by diverging access and/or continuity difficulties. "Challenging booking" (32%) was characterized by patients having to try several times to obtain an appointment at their clinic. "Challenging continuity" (9%) was characterized by patients having to repeat information that should have been in their file. "Access and continuity barriers" (16%) was characterized by difficulties with all access and continuity components. Female gender and poor perceived health significantly increased the risk of belonging to the three profiles associated with difficulties by 1.5. Being a recently arrived immigrant (p = 0.036), having less than a high school education (p = 0.002) and being registered at a large clinic (p < 0.001) were associated with experiencing booking difficulties. Having at least one chronic condition (p = 0.004) or poor perceived mental health (p = 0.048) were associated with experiencing continuity difficulties. Conclusions These results highlight individual social characteristics associated with increased risk of experiencing particular access and/or continuity difficulties. Personalized strategies are recommended, such as facilitating appointment booking for recently arrived immigrants and patients with low education, integrating interprofessional collaboration practices for patients with chronic conditions and improving care coordination and communication for patients with mental health needs.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".