Professor Julia Hippisley-Cox University of Nottingham.

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Cardiovascular risk in high secure environments Professor Julia Hippisley-Cox University of Nottingham

Transcript of Professor Julia Hippisley-Cox University of Nottingham.

Page 1: Professor Julia Hippisley-Cox University of Nottingham.

Cardiovascular risk in high secure environments

Professor Julia Hippisley-CoxUniversity of Nottingham

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West London Mental Health Trust Clinical staff at three hospitals R&D and MREC EMIS TPP Vision QResearch

Acknowldegments

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Compare CVD risk factor recording and CVD risk in SEMI patients in each of the 3 hospitals with SEMI patients in QResearch

Objectives

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NICE PH15 - identify & reduce risk premature mortality

NICE CG68 - identify & reduce CVD risk DRC enquiry -poor physical health of

patients with SEMI

Background

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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

Key findings DRC report:

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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

NICE guidelines (2008, CG67)

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Comparison of CVD Risk in four groups with SEMI1. Broadmoor hospital - EMIS2. Rampton hospital3. Ashworth hospital4. QResearch – community sample

R&D and MREC approval Extraction of pseudoymised patient level

data

New study 2012

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Age Chronic renal disease

Sex Diabetes

Ethnicity Hypertension

Smoking status CHD/stroke

Body mass index Medication but not recorded systematically in any of the hospitals

Lipids

Systolic blood pressure

Rheumatoid arthritis

Data items collected

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Used www.qrisk.org to assess CVD risk

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Recording of family historylower in hospital

Hospital A 9% Hospital B 3%Hospital C 4%QResearch 14%

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Variation in recording of ethnicity

Large variation

Hospital A 48% Hospital B 0%Hospital C 97%QResearch 84%

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Recording of body mass index

Generally higher and more recent in hospital patients

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Obesity levels very highOver half all hospital patients obese c.f. 29% in QResearch

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Type 2 Diabetes also very high

One in 5 hospital patients have diabetesTwice as high as community5 times as high as non-SEMI

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Diabetes by ageMarked risk with increasing age – 29% patients over 50 have diabetes

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Fasting blood glucose testingHuge variation in FBS testing but doesn’t explain high prevalence of diabetes in all hospital settings

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SBP control < 150/90Overall most patients meeting BP targets

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Cholesterol < 5 mmol/lOverall many patients meeting cholesterol targetsBetter than QResearch

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Recording 7 QOF SEMI register

Patients with QOF code for SEMI have higher risk factor recording ratese.g. 87% with QOF code have glucose recorded cf 37% without QOF code

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QResearch no SEMI

QResearch SEMI

HospitalSEMI

<10% risk 91.2 83.8 83.5

10-19.9% risk

7.1 12.2 12.0

20%+ risk 1.7 4.0 4.6

CVD risk resultsHospital patients more than twice as likely to have high CVD risk compared with community patients

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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: hospital vs community

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Recommendation 1: urgent need to commission services for

weight loss including diet, exercise & medication review

Recomendation 2: Interventions to lower diabetes riskRecommendation 3: Use of QOF SEMI codes to identify patients

and make use of computer QOF audit facilities

Summary recommendations

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Hospitals to use GP computer system for prescribing

1. Identify patients on medication for monitoring (eg lithium)

2. Identify patients not on medication who need it (eg statins)

3. use of inbuilt safety alerts in computer systems eg for drug interactions

4. Data for research into medication effects

Recommendation4

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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

Recommendations 5-8

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Report published at www.qresearch.org Any questions

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