Electroconvulsive Therapy Practice in the Province of Quebec: Linked Health Administrative Data Study from 1996 to 2013
Bibliographic record
Abstract
OBJECTIVE: As part of a quality improvement process, we propose a model of routinely monitoring electroconvulsive therapy (ECT) in Canadian provinces using linked health administrative databases to generate provincial periodic reports, influence policy, and standardise ECT practices. METHODS: ECT practice in Quebec was studied from 1996 to 2013, using longitudinal data from the Quebec Integrated Chronic Disease Surveillance System of the Institut National de Santé Publique du Québec, which links 5 health administrative databases. The population included all persons, aged 18 y and over, eligible for the health insurance registry, who received an ECT treatment at least once during the year. RESULTS: Among recorded cases, 75% were identified by physician claims and hospitalisation files, 19% exclusively by physician claims, and 6% by hospitalisation files. From 1996 to 2013, 8,149 persons in Quebec received ECT with an annual prevalence rate of 13 per 100,000. A decline was observed, which was more pronounced in women and in older persons. On average, each patient received 9.7 treatments of ECT annually. The proportion of acute ECT decreased whereas maintenance treatment proportions increased. A wide variation in the use of ECT was observed among regions and psychiatrists. CONCLUSION: This study demonstrates the profitable use of administrative data to monitor ECT use in Quebec, and provides a reliable method that could be replicated in other Canadian provinces. Although Quebec has one of the lowest utilisation rates reported in industrialized countries, regional disparities highlighted the need for a deeper examination of the quality and monitoring of ECT care and services.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".