Developing and Evaluating the Effectiveness of Interventions to Minimize the Duration of Restraint Events
PRESENTERS: Satinder Kaur, MSc(N), MEd(HPE), PhD(N), CPMHN(C); & Amina Ali, MD, DABPN, FRCPC
DATE: June 13, 2022
TIME: 9am - 12.30pm
CONTINUING EDUCATION CREDITS: 3.5 credits
COST: $125 CAD (includes 1 catered coffee break; lunch NOT included)
Best practice guidelines related to the use of restraints emphasize the least restraints approach (RNAO, 2012 and CNO (2018), and advocate for restraints to be used only for the shortest time, as a last resort when prevention, de-escalation and crisis management strategies have failed to keep the individual and others safe. The use of restraint is not consistent with the recovery model that focuses on client control, empowerment and involvement in their own care (RNAO, 2012; APNA, 2018; PSEP, 2017). Therefore, reduction of restraint events and time spent in restraints by mental health clients continues to be a high-priority focus of the organization.
This half-day workshop will outline the process of development, implementation and evaluation of a variety of evidence based interventions to minimize duration of seclusion restraints in a forensic inpatient unit. The key highlights of the process include data informed care and co-design model of development of interventions engaging frontline staff as well as clients. The discussion will include demonstration of practical application of a clinical decision support tree as well as care planning resources. The facilitators will also delve into discussion around the overall impact of the COVID-19 pandemic on care pathways at the system level, and ultimately on client care and the efforts to minimize the duration of seclusion restraints at an inpatient unit level in the forensic service.
Review the challenges of minimizing seclusion incidents on an acute Forensic inpatient unit
Discuss factors contributing to increased duration of seclusion incidents
Outline best practice interventions implemented
Demonstrate the utility of a decision support tree in clinical decision making