Short-stay crisis units for mental health patients on crisis care pathways: systematic review and meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
Background Internationally, an increasing proportion of emergency department visits are mental health related. Concurrently, psychiatric wards are often occupied above capacity. Healthcare providers have introduced short-stay, hospital-based crisis units offering a therapeutic space for stabilisation, assessment and appropriate referral. Research lags behind roll-out, and a review of the evidence is urgently needed to inform policy and further introduction of similar units. Aims This systematic review aims to evaluate the effectiveness of short-stay, hospital-based mental health crisis units. Method We searched EMBASE, Medline, CINAHL and PsycINFO up to March 2021. All designs incorporating a control or comparison group were eligible for inclusion, and all effect estimates with a comparison group were extracted and combined meta-analytically where appropriate. We assessed study risk of bias with Risk of Bias in Non-Randomized Studies – of Interventions and Risk of Bias in Randomized Trials. Results Data from twelve studies across six countries (Australia, Belgium, Canada, The Netherlands, UK and USA) and 67 505 participants were included. Data indicated that units delivered benefits on many outcomes. Units could reduce psychiatric holds (42% after intervention compared with 49.8% before intervention; difference = 7.8%; P < 0.0001) and increase out-patient follow-up care (χ 2 = 37.42, d.f. = 1; P < 0.001). Meta-analysis indicated a significant reduction in length of emergency department stay (by 164.24 min; 95% CI −261.24 to −67.23 min; P < 0.001) and number of in-patient admissions (odds ratio 0.55, 95% CI 0.43–0.68; P < 0.001). Conclusions Short-stay mental health crisis units are effective for reducing emergency department wait times and in-patient admissions. Further research should investigate the impact of units on patient experience, and clinical and social outcomes.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it