Primary health care services for patients with chronic disease in Newfoundland and Labrador: a descriptive analysis
Bibliographic record
Abstract
BACKGROUND: Newfoundland and Labrador has a rapidly aging population, much of which is rural, with poor health behaviours and high rates of chronic disease. These factors contribute to a unique challenge in health care delivery. Our aim was to describe the availability of publicly funded primary health care programs and services delivered by regional health authorities across the province. METHODS: We performed a descriptive analysis using data from a cross-sectional provincial primary health care survey deployed across Newfoundland and Labrador. Survey data included location, disease-specific chronic disease prevention programming, types of routine primary care, allied health prevention and promotion, chronic disease prevention and management services, and team-based care. The mode of service delivery was identified for most programs and services. RESULTS: Surveys were returned by 153 sites (99.4% response rate). Family physician services were available at 66% of sites (95/145) and nurse practitioner services were available at 51% (74/144) of sites. Many sites offered screening for cervical (60%, 86/144), colon (42%, 59/142) and prostate cancers (43%, 60/141), in addition to various self-management and education services. Allied health services, such as clinical nutrition counselling (47%, 68/46) and occupational therapy (46%, 68/147), were available at many sites. Available health care services were most often offered by on-site staff, and few sites provided primary health care services through telehealth. Overall, rural sites offered a greater variety of services than urban sites. INTERPRETATION: Considerable variability exists in the range of primary health care services available across Newfoundland and Labrador, with limited delivery of some programs and services. Future research should examine how availability of programs and services affects health outcomes and costs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".