https://www.selleckchem.com/products/ly364947.html
Restraint and seclusion in an inpatient child and adolescent psychiatric population adversely affects the overall value and safety of care. Due to adverse events, negative outcomes, and associated costs, inpatient psychiatric hospitals must strive to reduce and ultimately eliminate restraint and seclusion with innovative, data-driven approaches. To identify patterns of client characteristics that are associated with restraint and seclusion in an inpatient child and adolescent psychiatric population. A machine learning application of fa
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