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This study, led by Professor Julia Hippisley-Cox from the University of Nottingham, evaluates cardiovascular disease (CVD) risk factors in patients with severe mental illness (SEMI) across three hospitals. It compares data from SEMI patients to those in the QResearch database. Key findings indicate higher rates of coronary heart disease, obesity, and diabetes among SEMI patients, with significant disparities in the recording and management of CVD risk factors between hospital settings and the general population. Recommendations highlight the urgent need for targeted interventions to reduce these risks.
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Cardiovascular risk in high secure environments Professor Julia Hippisley-Cox University of Nottingham
Acknowldegments • West London Mental Health Trust • Clinical staff at three hospitals • R&D and MREC • EMIS • TPP • Vision • QResearch
Objectives • Compare CVD risk factor recording and CVD risk in SEMI patients in each of the 3 hospitals with SEMI patients in QResearch
Background • NICE PH15 - identify & reduce risk premature mortality • NICE CG68 - identify & reduce CVD risk • DRC enquiry -poor physical health of patients with SEMI
Key findings DRC report: Community patients with SEMI • Higher risk of CHD • Higher levels risk factors • smoking • obesity • diabetes • Less likely to be offered interventions • Less likely to report symptoms • Less likely to take prescribed medicines • Less likely to reach targets for lipids
NICE guidelines (2008, CG67) • Lipid modification guidelines • Identify patients at increased CVD risk • Quantify increased risk using QRISK2 or similar • Modify risk factors • weight loss • Blood pressure control • Lipid control • Smoking cessation
New study 2012 • Comparison of CVD Risk in four groups with SEMI • Broadmoor hospital - EMIS • Rampton hospital • Ashworth hospital • QResearch – community sample • R&D and MREC approval • Extraction of pseudoymised patient level data
Recording of family history lower in hospital Hospital A 9% Hospital B 3% Hospital C 4% QResearch 14%
Variation in recording of ethnicity Large variation Hospital A 48% Hospital B 0% Hospital C 97% QResearch 84%
Recording of body mass index Generally higher and more recent in hospital patients
Obesity levels very high Over half all hospital patients obese c.f. 29% in QResearch
Type 2 Diabetes also very high One in 5 hospital patients have diabetes Twice as high as community 5 times as high as non-SEMI
Diabetes by age Marked risk with increasing age – 29% patients over 50 have diabetes
Fasting blood glucose testing Huge variation in FBS testing but doesn’t explain high prevalence of diabetes in all hospital settings
SBP control < 150/90 Overall most patients meeting BP targets
Cholesterol < 5 mmol/l Overall many patients meeting cholesterol targets Better than QResearch
Recording 7 QOF SEMI register Patients with QOF code for SEMI have higher risk factor recording rates e.g. 87% with QOF code have glucose recorded cf 37% without QOF code
CVD risk results Hospital patients more than twice as likely to have high CVD risk compared with community patients
Summary: hospital vs community • Some good examples of recording • Some variation between the three hospital • Twice the CVD risk c.f. general population • More than half have obesity • One in five have diabetes • Diabetes twice as high as SEMI in community • Diabetes five times as high as general population
Summary recommendations Recommendation 1: • urgent need to commission services for weight loss including diet, exercise & medication review Recomendation 2: • Interventions to lower diabetes risk Recommendation 3: • Use of QOF SEMI codes to identify patients and make use of computer QOF audit facilities
Recommendation4 • Hospitals to use GP computer system for prescribing • Identify patients on medication for monitoring (eg lithium) • Identify patients not on medication who need it (eg statins) • use of inbuilt safety alerts in computer systems eg for drug interactions • Data for research into medication effects
Recommendations 5-8 • Use of computer templates to improve recording of family history • All patients to have ethnicity recorded • Update records for smoking status • Identify patients with high glucose values but without diagnosis of diabetes recorded
Thank you for listening • Report published at www.qresearch.org • Any questions