Policies in Canada fail to address disparities in access to person-centred osteoarthritis care: a content analysis
Bibliographic record
Abstract
Abstract Background Women are disproportionately impacted by osteoarthritis (OA) but less likely than men to access OA care, particularly racialized women. One way to reduce inequities is through policies that can influence healthcare services. We examined how OA-relevant policies in Canada address equitable, person-centred OA care for women. Methods We used content analysis to extract data from English-language OA-relevant documents referred to as policies or other synonymous terms published in 2000 or later identified by searching governmental and other web sites. We used summary statistics to describe policy characteristics, person-centred care using McCormack’s six-domain framework, and mention of OA prevalence, barriers and strategies to improve equitable access to OA care among women. Results We included 14 policies developed from 2004 to 2021. None comprehensively addressed all person-centred care domains, and few addressed individual domains: enable self-management (50%), share decisions (43%), exchange information (29%), respond to emotions (14%), foster a healing relationship (0%) and manage uncertainty (0%). Even when mentioned, content offered little guidance for how to achieve person-centred OA care. Few policies acknowledged greater prevalence of OA among women (36%), older (29%) or Indigenous persons (29%) and those of lower socioeconomic status (14%); or barriers to OA care among those of lower socioeconomic status (50%), in rural areas (43%), of older age (37%) or ethno-cultural groups (21%), or women (21%). Four (29%) policies recommended strategies for improving access to OA care at the patient (self-management education material in different languages and tailored to cultural norms), clinician (healthcare professional education) and system level (evaluate OA service equity, engage lay health leaders in delivering self-management programs, and offer self-management programs in a variety of formats). Five (36%) policies recommended research on how to improve OA care for equity-seeking groups. Conclusions Canadian OA-relevant policies lack guidance to overcome disparities in access to person-centred OA care for equity-seeking groups including women. This study identified several ways to strengthen policies. Ongoing research must identify the needs and preferences of equity-seeking persons with OA, and evaluate the impact of various models of service delivery, knowledge needed to influence OA-relevant policy.
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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 | 0.019 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.016 | 0.038 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| 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".