Metformin for the Prevention of Antipsychotic-Induced Weight Gain: Guideline Development and Consensus Validation.

Background: Overweight and obesity are highly prevalent in people with severe mental illness (SMI). Antipsychotic-induced weight gain (AIWG) is one of the most commonly reported and distressing side effects of treatment and people living with SMI place a high value on the avoidance of this side effect. Metformin is the most effective pharmacological intervention studied for the prevention of AIWG yet clear guidelines are lacking and evidence has not translated into practice.

Remote consultations in mental health: collaborative evaluation applying learning health systems thinking.

Aims And Method: A collaborative evaluation of remote consultations in mental health services was undertaken by mental health service providers, experts by experience, academic institutions and a Health Innovation Network in south London, UK. 'Learning healthcare systems' thinking was applied. Workstream 1 reviewed international published evidence; workstream 2 synthesised findings from three health provider surveys of the perceptions and experiences of staff, patients and carers; and workstream 3 comprised an electronic survey on local projects.

Evaluating a volunteer 'Health Champions' intervention supporting people with severe mental illness to manage their physical health: feasibility hybrid randomised controlled trial.

Background: People with severe mental illness (SMI) have worse physical health than the general population. There is evidence that support from volunteers can help the mental health of people with SMI, but little evidence regarding the support they can give for physical health.

Aims: To evaluate the feasibility of an intervention where volunteer 'Health Champions' support people with SMI in managing their physical health.

Implementation of an Electronic Clinical Decision Support System for the Early Recognition and Management of Dysglycemia in an Inpatient Mental Health Setting Using CogStack: Protocol for a Pilot Hybrid Type 3 Effectiveness-Implementation Randomized Controlled Cluster Trial.

Background: Severe mental illnesses (SMIs), including schizophrenia, bipolar affective disorder, and major depressive disorder, are associated with an increased risk of physical health comorbidities and premature mortality from conditions including cardiovascular disease and diabetes. Digital technologies such as electronic clinical decision support systems (eCDSSs) could play a crucial role in improving the clinician-led management of conditions such as dysglycemia (deranged blood sugar levels) and associated conditions such as diabetes in people with a diagnosis of SMI in mental health settings.

Objective: We have developed a real-time eCDSS using CogStack, an information retrieval and extraction platform, to automatically alert clinicians with National Health Service Trust-approved, guideline-based recommendations for dysglycemia monitoring and management in secondary mental health care.