Cost evaluation of out-of-country care for patients with eating disorders in Ontario: a population-based study
Bibliographic record
Abstract
Background: Eating disorders, specifically anorexia nervosa, bulimia nervosa and eating disorder not otherwise specified, represent a substantial burden to the health care system. Our goal was to estimate the economic burden of patients who received specialized inpatient care for an eating disorder out of country. Method: We conducted a cost-of-illness study evaluating health care costs among patients in Ontario who received specialized inpatient care for an eating disorder out of country from 2003 to 2011, from the public third-party payer perspective. Using linked administrative databases, we estimated net costs of eating disorders for 2 patient groups: those who received specialized inpatient care both out of country and in province (n = 160), and those who received specialized inpatient care out of country only (n = 126). Results: Patients approved for specialized out-of-country inpatient care were mostly girls and young women from high-income, urban neighbourhoods. Total net costs varied annually and were higher for patients treated both out of country and in province (about $11 million before 2007, $6.5 million after) than for those treated out of country alone (about $5 million and $2 million, respectively). The main cost drivers were out-of-country care and physician services. Interpretation: Costs associated with eating disorder care represent a substantial economic burden to the Ontario health care system. Given the high costs of out-of-country care, there may be opportunity to redirect these funds to increase capacity and expertise for eating disorder treatment within Ontario.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".