Patients' perceptions of the primary care characteristics in a model of interprofessional patient-centred collaboration between chiropractors and physicians.
Bibliographic record
Abstract
Background: Considerable attention has been paid to evaluating the roles and relationships of professionals participating in team-based or collaborative practice; however, less attention has been paid to exploring the patientsâ views and impact of such practice despite claims of it being patient-centred.\nObjectives: To examine the relationship between patient and provider characteristics and patientsâ ratings of measures of quality of care and integration, and to explore the patient views of care delivered in a patient-centred collaborative study involving chiropractors and physicians.\nDesign: Cross-sectional survey.\nMethod: A mixed methods sequential approach with a quantitative priority was used in data analysis. Quantitative data were collected from 2597 patients participating in a collaborative study involving chiropractors and physicians and 530 patients attending chiropractors not involved in collaborative care. All participants presented with musculoskeletal pain. The Primary Care Assessment Survey (PCAS) was modified and scores from six of its scales were used to assess attributes of quality patient-centred care between the two study groups. Qualitative transcript-based data from six purposefully selected focus groups was analyzed using an interpretivist approach. \nResults: The revised PCAS demonstrated acceptable psychometric properties. Patients in both study groups received quality, patient-centred care. Patientsâ reporting being completely satisfied and feeling improved by their care was positively associated with rating chiropractors as high performers on all scales. Survey findings were confirmed in focus groups of study patients. Patients appreciated positive interpersonal interactions, sharing in the treatment decision-making process, having a choice in provider and treatment, and the provision of holistic care. Patients perceived that collaboration between chiropractors and physicians varied, favouring those who were co-located. Patients with chronic or co-morbid conditions desired greater involvement in their care. Patients felt sharing of clinical information was more important than co-location as facilitating coordination and integration of collaborative care. \nConclusion: The study suggests that patients suffering from musculoskeletal pain benefit from interprofessional collaborative care that includes improved access to and choice of providers and treatment options, as well as enhanced interprofessional communication and coordination of care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".