Evaluating mental disorders and physician-based mental health services for patients enrolled in opioid agonists treatment across Ontario, Canada
Bibliographic record
Abstract
The overall purpose of this thesis was to explore the relationship between physician-based mental health services and all-cause mortality, emergency department visits and, hospitalizations among patients receiving opioid agonist treatment (OAT) in different regions of Ontario. I conducted a retrospective cohort study using secondary health administrative data from ICES. Specifically, I used the Ontario Health Insurance Plan (OHIP) and the Ontario Drug Benefit Plan (ODB) databases to identify patients. Eligible patients were 15 years of age and over and were receiving OAT from January 1, 2011, and December 31, 2015. I conducted quantitative analyses using logistic regression and propensity score matching methods to test the relationship between concurrent physician-based mental health services and OAT and health service outcomes. Five core findings were brought together in this thesis: (a) having a diagnosis of one or more mental disorders while in OAT was associated with a higher likelihood of mortality and a more complex profile of health service utilization when compared to patients in OAT who had not been diagnosed with mental disorders; (b) active engagement in OAT was associated with a reduced likelihood of all-cause mortality, emergency department visits, and hospitalizations compared to patients who had been but were not actively engaged in OAT; (c) receiving mental health services from physicians (i.e., psychiatrists, primary care or both) while actively enrolled in OAT was associated with a reduction in the likelihood of all-cause mortality compared to patients not receiving mental health services while in OAT; (d) physician-based mental health services (from psychiatrists, primary care or both) while enrolled in OAT was associated with frequent ED visits and hospitalizations; and (e) fewer patients accessed mental health services while enrolled in OAT in northern and rural Ontario compared to southern and urban regions of the province.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".