Patient-centred care in an occupational medicine clinic
Bibliographic record
Abstract
BACKGROUND: Patient-centred care (PCC) has been associated with improved patient satisfaction outcomes in a variety of clinical settings. There is a paucity of research addressing the concept of PCC in an occupational medicine context. AIMS: To assess patient perception and compare physician and patient perceptions of patient centredness of the care at a specialty occupational medicine clinic. METHODS: An observational study design using the Patient Perception of Patient Centeredness Questionnaire (PPPC) at an ambulatory tertiary care occupational health clinic. Results were analysed using a standardized coding system. Summary scores were compared to results reported in a primary care setting. Patient and physician scores were compared to detect physician-patient differences in perceived patient centredness of care. RESULTS: Of 47 eligible patients 37 consented to participate and seven were excluded due to incomplete data. Summary scores of patient perceptions of patient centredness were similar but somewhat better than scores reported in a primary care setting. Perceived patient centredness of care was high and there was minimal discordance between patient and physician scores. CONCLUSIONS: This study demonstrated that PCC can be measured in an occupational health setting. In an ambulatory tertiary care occupational health clinic there was a high degree of patient centredness of care which may be explained by a variety of factors. Future research should consider whether similar findings exist in other occupational medicine practice settings.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".