Adult psychiatric inpatient admissions and length of stay before and during the COVID-19 pandemic in a large urban hospital setting in Vancouver, British Columbia
Bibliographic record
Abstract
Introduction: During the COVID-19 pandemic individuals with mental illnesses faced challenges accessing psychiatric care. Our study aimed to describe patient characteristics and compare admissions and length of stay (LOS) for psychiatric-related hospitalizations before and during the COVID-19 pandemic. Methods: We conducted a retrospective analysis using health administrative data comparing individuals with an acute psychiatric admission between two time periods: 1st March 2019 to 31st December 2019 (pre-COVID) and 1st March 2020 to 31st December 2020 (during-COVID). Multivariable negative binomial regression was used to model the association between most responsible diagnosis type and the two-time periods to hospital LOS, reporting the Rate Ratio (RR) as the measure of effect. Results: The cohort comprised 939 individuals who were predominately male (60.3%) with a severe mental illness (schizophrenia or mood-affective disorder) (72.7%) and a median age of 38 (IQR: 28.0, 52.0) years. In the multivariable analysis, anxiety disorders (RR: 0.63, CI: 0.4, 0.99) and personality disorders (RR: 0.52, CI: 0.32, 0.85) were significantly associated with a shorter LOS when compared to individuals without those disorders. Additionally, when compared to hospital admissions for non-substance related disorders the LOS for patients with substance-related disorders were significantly shorter during the COVID period (RR: 0.45, CI: 0.30, 0.67) and pre-COVID period (RR: 0.31, CI: 0.21, 0.46). Conclusions: We observed a significant difference in the type and length of admissions for various psychiatric disorders during the COVID-19 period. These findings can support systems of care in adapting to utilization changes during pandemics or other global health events.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".