Reducing Physical Restraint Use in the Medical Behavioral Unit
Bibliographic record
Abstract
OBJECTIVES: Children with behavioral health conditions often experience agitation when admitted to children's hospitals. Physical restraint should be used only as a last resort for patient agitation because it endangers the physical and psychological safety of patients and employees. At the medical behavioral unit (MBU) in our children's hospital, we aimed to decrease the weekly rate of physical restraint events per 100 MBU patient-days, independent of patient race, ethnicity, or language, from a baseline mean of 14.0 to <10 within 12 months. METHODS: Using quality improvement methodology, a multidisciplinary team designed, tested, and implemented interventions including a series of daily deescalation huddles led by a charge behavioral health clinician that facilitated individualized planning for MBU patients with the highest behavioral acuity. We tracked the weekly number of physical restraint events per 100 MBU patient-days as a primary outcome measure, weekly physical restraint event duration as a secondary outcome measure, and MBU employee injuries as a balancing measure. RESULTS: Our cohort included 527 consecutive patients hospitalized in the MBU between January 2021 and January 2023. Our 2021 baseline mean of 14.0 weekly physical restraint events per 100 MBU patient-days decreased to 10.0 during our 2022 intervention period from January through July and 4.1 in August, which was sustained through December. Weekly physical restraint event duration also decreased from 112 to 67 minutes without a change in employee injuries. CONCLUSIONS: Multidisciplinary huddles that facilitated daily deescalation planning safely reduced the frequency and duration of physical restraint events in the MBU.
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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 | 0.001 |
| 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 | 0.001 |
| 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".