Health service use among Manitobans with alcohol use disorder: a population-based matched cohort study
Bibliographic record
Abstract
BACKGROUND: Alcohol is the drug most commonly used by Canadians, with multiple impacts on health and health service use. We examined patterns of short- and long-term health service use among people with a diagnosis of alcohol use disorder. METHODS: In this retrospective matched cohort study, we used population-based administrative data from the province of Manitoba, Canada, to identify individuals aged 12 years or older with a first indication of alcohol use disorder (index date) in the period 1990 to 2015. We matched cases (those with diagnosis of alcohol use disorder) to controls (those without this diagnosis), at a 1:5 ratio, on the basis of age, sex, geographic region and income quintile at the index date. The outcome measures were inpatient hospital admission, outpatient physician visits, emergency department visits and use of prescription medications. We modelled crude rates using generalized estimating equations with either a negative binomial or a Poisson distribution RESULTS: We identified 53 410 people with alcohol use disorder and 264 857 matched controls. All outcomes occurred at a higher rate among people with the disorder than among controls. For example, during the year of diagnosis, the rate ratio for hospital admission was 4.0 (95% confidence interval [CI] 3.9-4.2) for women and 4.5 (95% CI 4.4-4.7) for men. All rates of health service use peaked close to the index date, but remained significantly higher among people with alcohol use disorder than among controls for 20 years. Among people with alcohol use disorder, the most commonly filled prescriptions were for psycholeptics, whereas among controls, the most commonly filled prescriptions were for sex hormones (women) and antihypertensives (men). INTERPRETATION: Compared with controls, people with alcohol use disorder used significantly more health services from the time of diagnosis and over the next 20 years. This finding highlights the need for better detection and early intervention to reduce the need for acute and emergency care, as well as the need for improved management of alcohol use disorder over the longer term.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".