BackgroundMental health professionals increasingly carry out risk assessments to prevent future violence by their patients. However, there are problems with accuracy and these assessments do not always translate into successful risk management.ObjectivesOur aim was to improve the accuracy of assessment and identify risk factors that are causal to be targeted by clinicians to ensure good risk management. Our objectives were to investigate key risks at the population level, construct new static and dynamic instruments, test validity and construct new models of risk management using Bayesian networks.Methods and resultsWe utilised existing data sets from two national and commissioned a survey to identify risk factors at the population level. We confirmed that certain mental health factors previously thought to convey risk were important in future assessments and excluded others from subsequent parts of the study. Using a first-episode psychosis cohort, we constructed a risk assessment instrument for men and women and showed important sex differences in pathways to violence. We included a 1-year follow-up of patients discharged from medium secure services and validated a previously developed risk assessment guide, the Medium Security Recidivism Assessment Guide (MSRAG). We found that it is essential to combine ratings from static instruments such as the MSRAG with dynamic risk factors. Static levels of risk have important modifying effects on dynamic risk factors for their effects on violence and we further demonstrated this using a sample of released prisoners to construct risk assessment instruments for violence, robbery, drugs and acquisitive convictions. We constructed a preliminary instrument including dynamic risk measures and validated this in a second large data set of released prisoners. Finally, we incorporated findings from the follow-up of psychiatric patients discharged from medium secure services and two samples of released prisoners to construct Bayesian models to guide clinicians in risk management.ConclusionsRisk factors for violence identified at the population level, including paranoid delusions and anxiety disorder, should be integrated in risk assessments together with established high-risk psychiatric morbidity such as substance misuse and antisocial personality disorder. The incorporation of dynamic factors resulted in improved accuracy, especially when combined in assessments using actuarial measures to obtain levels of risk using static factors. It is important to continue developing dynamic risk and protective measures with the aim of identifying factors that are causally related to violence. Only causal factors should be targeted in violence prevention interventions. Bayesian networks show considerable promise in developing software for clinicians to identify targets for intervention in the field. The Bayesian models developed in this programme are at the prototypical stage and require further programmer development into applications for use on tablets. These should be further tested in the field and then compared with structured professional judgement in a randomised controlled trial in terms of their effectiveness in preventing future violence.FundingThe National Institute for Health Research Programme Grants for Applied Research programme.

The Rasch model (RM) is the only model where "'specific objectivity"' is a defining property of the model. This property is necessary for constructing scales in line with the fundamental principles of measurement.

Costs of headache are high, and increase with severity of symptoms. The annual cost to the country for those referred to specialists is estimated at £835 million.

Objective To estimate and compare the economic costs of mental health‐related discrimination in the domains of health care, relationships and participation in leisure activities in England between 2011 and 2014. Method A subsample of the Viewpoint survey was interviewed using the Costs of Discrimination Assessment Questionnaire in 2011 and 2014. Information on the impact of discrimination on healthcare use, help seeking from family and friends and participation in leisure activities was recorded. Pattern of contacts, costs and predictor of costs were examined. Results Our findings showed higher costs of health service use for individuals who reported experiences of discrimination in healthcare settings in 2011 compared with those who did not (mean difference £625, P‐value 0.019). Individuals who reported experiences of discrimination in relationships in 2014 had higher healthcare costs than those who did not (mean difference £418, P ‐value 0.034). There was some evidence of a reduction in overall levels of healthcare use, leisure activities and support from families over time. Discrimination did not significantly affect help seeking from family/friends or leisure activities. Conclusion There is some evidence that discrimination is related to increased healthcare costs. A prospective study is needed to better understand the consequences of these effects.

Background: Severe hypoglycemic events (SHEs) in patients with diabetes are associated with substantial health care costs in the United States (US). Injectable glucagon (IG) is currently available for treatment of severe hypoglycemia but is associated with frequent handling errors. Nasal glucagon (NG) is a novel, easier-to-use treatment that is more often administered successfully. The economic impact of this usability advantage was explored in cost-offset and budget impact analyses for the US setting. Methods: A health economic model was developed to estimate mean costs per SHE for which treatment was attempted using NG or IG, which differed only in the probability of treatment success, based on a published usability study. The budget impact of NG was projected over 2 years for patients with type 1 diabetes (T1D) and type 2 diabetes treated with basal-bolus insulin (T2D-BB). Epidemiologic and cost data were sourced from the literature and/or fee schedules. Results: Mean costs were $992 lower if NG was used compared with IG per SHE for which a user attempted treatment. NG was estimated to reduce SHE-related spending by $1.1 million and $230 000 over 2 years in 10 000 patients each with T1D and T2D-BB, respectively. Reduced spending resulted from reduced professional emergency services utilization as successful treatment was more likely with NG. Conclusions: The usability advantage of NG over IG was projected to reduce SHE-related treatment costs in the US setting. NG has the potential to improve hypoglycemia emergency care and reduce SHE-related treatment costs.