Quality improvement in forensic mental health: the East London forensic violence reduction collaborative.

Ward-based violence is the most significant cause of reported safety incidents at East London NHS Foundation Trust (ELFT). It impacts on patient and staff safety, well-being, clinical care and the broader hospital community in various direct and indirect ways. The contributing factors are varied and complex. Several factors differentiate the forensic setting, which has been identified as a particularly stressful work environment. Staff must constantly balance addressing therapeutic needs with robust risk management in a complex patient cohort. ELFT identified reducing inpatient physical violence on mental health wards as a major quality improvement (QI) priority. The aim was to use a QI methodology to reduce incidents of inpatient violence and aggression across two secure hospital sites by at least 30% between July 2016 and March 2018. Collaborative learning was central to this project. It sought to foster a culture of openness within the organisation around violence and to support service users and staff to work together to understand and address it. A QI methodology was applied in medium and low secure inpatient settings. A change bundle was tested for effectiveness, which included: safety huddles, safety crosses and weekly community safety discussions. Operational definitions for non-physical violence, physical violence and sexual harassment were developed and used. Reductions of 8% and 16.6% in rates of physical and non-physical violent incidents, respectively, were achieved and sustained. Compared with baseline, this equated to one less incident of physical and 17 less of non-physical violence per week averaged across seven wards. Three wards achieved at least a 30% reduction in incidents of physical violence per week. Five wards achieved at least a 30% reduction in incidents of non-physical violence per week. This collaborative brought significant improvements and a cultural shift towards openness around inpatient violence.

VR-based training and assessment in ultrasound-guided regional anesthesia: from error analysis to system design.

If VR-based medical training and assessment is to improve patient care and safety (i.e. a genuine health gain), it has to be based on clinically relevant measurement of performance. Metrics on errors are particularly useful for capturing and correcting undesired behaviors before they occur in the operating room. However, translating clinically relevant metrics and errors into meaningful system design is a challenging process. This paper discusses how an existing task and error analysis was translated into the system design of a VR-based training and assessment environment for Ultrasound Guided Regional Anesthesia (UGRA).