Understanding disparities in primary care patient experience
Bibliographic record
Abstract
OBJECTIVE: To understand disparities in primary care patient experience. DESIGN: A serial cross-sectional study was conducted to understand disparities in patient experience at 2 time points (2014 and 2016). Disparities related to age, gender, neighbourhood income, and self-rated health were explored using 3 analytic approaches: stratification, logistic regression, and relative comparison across multiple demographic variables. SETTING: A multisite family health team in Toronto, Ont. PARTICIPANTS: Patients in the family medicine practice who completed e-mail surveys in 2014 (n = 1171, 19% response rate) and 2016 (n = 1823, 15% response rate). MAIN OUTCOME MEASURES: Patient-reported access (timely access when sick, access after hours) and patient-centredness (opportunity to ask questions, involvement in care decisions, enough time with provider). RESULTS: Performance for all measures improved between 2014 and 2016, with the greatest absolute improvement seen in access after hours (61% in 2014; 75% in 2016). Patients residing in low-income neighbourhoods reported worse patient experiences than those in high-income neighbourhoods did, as did patients with poor versus excellent self-rated health, even after adjustment for other variables. For example, in 2016, 60% of patients residing in low-income neighbourhoods reported timely access when sick versus 70% in high-income neighbourhoods (adjusted odds ratio of 0.67, 95% CI 0.47 to 0.95); 60% of patients with poor or fair self-rated health reported timely access when sick versus 72% with excellent self-rated health (adjusted odds ratio of 0.54, 95% CI 0.35 to 0.84). Comparing across demographic groups, patients with excellent self-rated health and poor or fair self-rated health reported the best and worst experiences, respectively, for all measures. In 2016, the average disparity between subgroups was largest for access after hours. CONCLUSION: In this setting, patient experience was worse for patients in lower-income neighbourhoods and those with poor or fair self-rated health. Access after hours demonstrated the greatest overall absolute improvement but also the greatest widening of disparities.
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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 | 0.017 |
| 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 | 0.001 | 0.002 |
| Open science | 0.000 | 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".