Quantifying institutional-level length of stay variation among hospitalizations for schizophrenia in Ontario between 2014–2021
Bibliographic record
Abstract
Variations in the length and intensity of care delivery from person to person are to be expected, however, such variation can also result from institutional-level factors that may not be directly related to a patient's needs. The objective of this study is to provide a descriptive analysis quantifying the variation in the length of stay (LOS) that is attributable to institutional- and patient-level factors for Ontarians hospitalized with schizophrenia between 2014 and 2021. A retrospective cohort study was conducted using Ontario medical records from >100,000 adult inpatients who had been admitted to an Ontario hospital with a primary diagnosis of schizophrenia between fiscal years 2014 and 2021. The proportion of variation in inpatient LOS that was attributable to institutional-level factors was assessed using log-linear mixed-effects models. Large community, teaching, and specialty mental health hospitals were each modelled separately. These results are presented alongside descriptive analyses for additional context. Average LOS in large community hospitals (mean = 24.2 days, SD = 62.51 days) was lower than specialty mental health hospitals (mean = 85.4 days, SD = 262.9 days) and teaching hospitals (mean = 42.8 days, SD = 137.4 days). The highest proportion of institutional-level variation was seen in large community hospitals (29.3%), with specialty mental health hospitals (19.3%) and teaching hospitals (19.7%) reporting similar proportions of institutional-level variation. This analysis has identified differences in the proportion of inpatient LOS variation attributable to institutional-level factors between types of hospital. A larger percentage of institutional-level variation was seen in large community hospitals however, all hospital types exhibited institutional-level variation. These differences likely result from a combination of governmental and hospital-level factors, which may present an opportunity for policy and clinical interventions. Future research can assess the potential for evidence-based interventions such as bundled care pathways and supportive housing programs in addressing these factors.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".