Healthcare utilization associated with obesity management in Ontario, Canada
Bibliographic record
Abstract
Summary This study aimed to describe the characteristics, healthcare resources utilized and costs incurred by adults receiving publicly funded obesity care in Ontario, Canada. People living with obesity who first visited Wharton Medical Clinic, a weight and diabetes management clinic in Ontario, between 2015 and 2018 were identified. Pseudoanonymized data were linked to administrative databases to understand healthcare utilization and costs borne by the public payer over 3 years. 6208 participants had linked data, 63.9% and 27.3% of whom remained followed one and two years after their first clinic visit, respectively. The cohort was 71.84% female with a mean (SD) age of 50.86 (13.28) years and BMI of 40.21 (7.06) kg/m 2 . Approximately 25% of participants were prescribed pharmacotherapy (liraglutide, orlistat, naltrexone/bupropion), 4% received psychological therapy and 2% had weight‐loss surgery. Common obesity‐related complications were hypertension (42.62%), musculoskeletal pain (35.20%) and dyslipidaemia (33.65%). Participants had 22.16 physician visits per person‐year in year one, mostly to general practitioners and endocrinologists, which decreased to 17.38 visits per person‐year by year three. Mean total costs (excluding privately covered prescriptions) per person‐year decreased from $5227.25 (Canadian dollars) (SE: $0.97) to $4982.88 (SE: $2.16) over the same period. Participants were mostly female and presented with obesity‐related complications. Although healthcare utilization and costs incurred by the cohort were high, both showed a decreasing trend over the follow‐up period.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".