People with severe mental illnesses like schizophrenia are dying early from heart disease, and a new programme aims to give their GPs a simple web-based tool to predict and prevent it. The problem is stark: these patients have higher rates of smoking, diabetes, and obesity, yet are less likely to be screened for cardiovascular risk or prescribed statins. Current risk scores, designed for the general population, may not work well for them. This programme will build a new predictive model using patient data, then test a nurse-led intervention—including statin prescriptions and adherence checks—in a trial across GP practices. If successful, the research could give primary care a practical, evidence-based way to close a persistent health inequality. Instead of dying years earlier from preventable heart attacks, people with severe mental illness could receive the same standard of cardiovascular care as everyone else. The web-based tool would slot directly into NHS workflows, making it easy for practice nurses to identify high-risk patients and act.
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• Aims and objectivesWe aim to develop a Cardiovascular Disease (CVD) risk score tool, specifically for people with Severe Mental Illness (SMI). We will develop, then test, the effectiveness and cost-effectiveness of an intervention with practice nurses working to reduce CVD risk in SMI, including reviews, prescription of statins & adherence• BackgroundPeople with SMI, including schizophrenia, die early from CVD. They have increased CVD risk factors including abnormal lipids, diabetes, smoking and obesity. They make frequent contact with primary care, yet are less likely to be screened for risk factors or receive interventions such as statins.Primary care services are expected to address this health inequality and our programme will address two key areas highlighted by NICE for NHS research • Research plansDevelopment (yrs 1-2) Work Package (WP) 1: A new predictive risk score for CVD risk in SMI. We will refining existing tools for the general population which are widely used in primary care. We will use data from the THIN database on over 20,000 people with SMI over 20 years to build a model which predicts new-onset CVD. We will compare how models perform in people with and without SMI. Our final predictive model will be validated and calibrated for performance.It will be developed into a web based tool for clinical use in the NHS at year 2.WP 2: We will consolidate our previous work including qualitative work and systematic reviews to develop a nurse-led intervention to reduce CVD risk in SMI in primary care. i) We will hold 4 focus groups with service users, 4 with practice nurses/GPs and 4 with other stakeholders and experts. The corner stones of the intervention will be statin therapy, adherence and monitoring of CVD risk over one year. ii) We will update a systematic review of interventions to reduce CVD risk in SMI.iii) We will explore inequalities in CVD risk reduction (eg prescription of statins) for people with SMI in primary care using THIN data from WP1Synthesis of WP 1 and 2 findings will lead to WP3WP3: Trial (years 3-5)A cluster randomised, clinical and cost effectiveness trial, comparing the intervention to treatment as usual in 40 practices on the MRC GP Research Framework. Intervention arm nurses will work with adults with SMI who have a raised CVD risk score (from WP1) or raised lipids. They will review risk, arrange for statin prescriptions and check adherence. We have 90% power to demonstrate a 0.4 standard deviation difference in cholesterol between the two arms (n=198 each) at 1 year follow-up. This is an achievable and clinically meaningful impact.• Research teamWe have a track record of publications and grant funding in physical health and severe mental illness, research with primary care databases and delivering mental health trials. This also includes qualitative, statistical and epidemiological work and evidence synthesis. Our work has influenced NHS policy including NICE. Many applicants belong to the Mental Health Research Network research group on the physical consequences of SMI, including Rethink. Convenor: DO Our team includes NHS cliniciansExperts in risk models Cardiovascular expertsExpert service users and RethinkNHS clinical managersConsultant endocrinologistClinical and academic GPsClinical academic psychiatristsStatisticians epidemiologists & health economistsQualitative researchersTrials expertsHealth psychology• Research environmentThe host NHS Trust has a strong record of research with UCL and the co-applicants have a history of collaboration. There is a cohesive team of statistical and epidemiological experts at UCL to support the database work involved in WP1. The design and delivery of the trial will be supported by the PRIMENT CTU, several co-applicants work in the CTU and the London Research Design Service. • Anticipated outputs, outcomes and impact of research on the health and the NHSOur deliverables address two NICE priorities for people with SMI: better prediction and mana
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