Primary health care utilization for alcohol-attributed diseases in British Columbia Canada 2001–2011
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to determine whether general practitioner visits for alcohol-attributed diseases increased in a decade when several regulatory changes were made to the distribution and price of alcohol in British Columbia Canada. METHODS: General practitioner consultations for alcohol-attributed diseases were examined using data from British Columbia's Medical Services Plan database. Negative binomial regression was used to measure the significance of yearly variations using incidence rate ratios by disease type per year. RESULTS: From 2001 to 2011, 690,401 visits were made to general practitioners by 198,623 persons with alcohol-attributed diseases. Most visits (86.2%) were for alcohol dependency syndrome (N = 595,371). General practitioner visits for alcohol-attributed diseases increased significantly (p < .001) by 53.3% from 14,882 cases in 2001 to 22,823 cases in 2011. While the number of cases increased from 2001-2011, the frequency of visits to general practitioners significantly decreased from 3.9 in 2001 to 2.7 visits per case in 2011 (F = 428.1, p < .001). CONCLUSION: From 2001 to 2011 there were significant increases in the number of persons presenting to general practitioners with alcohol-attributed diseases in British Columbia. The results of this study demonstrate the need to provide enhanced support to general practitioners in the treatment of patients with substance use disorders given the increasing number of primary health care patients with alcohol-attributed diseases.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".