Exploring policy driven systemic inequities leading to differential access to care among Indigenous populations with obstructive sleep apnea in Canada
Bibliographic record
Abstract
BACKGROUND: In settler societies such as Australia, Canada, New Zealand and the United States, health inequities drive lower health status and poorer health outcomes in Indigenous populations. This research unravels the dense complexity of how historical policy decisions in Canada can influence inequities in health care access in the 21(st) century through a case study on the diagnosis and treatment of obstructive sleep apnea (OSA). In Canada, historically rooted policy regimes determine current discrepancies in health care policy, and in turn, shape current health insurance coverage and physician decisions in terms of diagnosis and treatment of OSA, a clinical condition that is associated with considerable morbidity in Canada. METHODS: This qualitative study was based in Saskatchewan, a Western Canadian province which has proportionately one of the largest provincial populations of an Indigenous subpopulation (status Indians) which is the focus of this study. The study began with determining approaches to OSA care provision based on Canadian Thoracic Society guidelines for referral, diagnosis and treatment of sleep disordered breathing. Thereafter, health policy determining health benefits coverage and program differences between status Indians and other Canadians were ascertained. Finally, respirologists who specialized in sleep medicine were interviewed. All interviews were audio-recorded and the transcripts were thematically analyzed using NVIVO. RESULTS: In terms of access and provision of OSA care, different patient pathways emerged for status Indians in comparison with other Canadians. Using Saskatchewan as a case study, the preliminary evidence suggests that status Indians face significant barriers in accessing diagnostic and treatment services for OSA in a timely manner. CONCLUSIONS: In order to confirm initial findings, further investigations are required in other Canadian jurisdictions. Moreover, as other clinical conditions could share similar features of health care access and provision of health benefits coverage, this policy analysis could be replicated in other provincial and territorial health care systems across Canada, and other settler nations where there are differential health coverage arrangements for Indigenous peoples.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".