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VTE prevention: Real-world outcome data

VTE prevention: Real-world outcome data. Domenico Pagano Consultant Cardiothoracic Surgeon Clinical Director Quality & Outcomes Research Unit University Hospital Birmingham, UK. ‘VTE PREVENTION NHS SHOWCASE’ 16th September 2013 . Quality and Outcomes Research Unit

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VTE prevention: Real-world outcome data

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  1. VTE prevention: Real-world outcome data Domenico Pagano Consultant Cardiothoracic Surgeon Clinical Director Quality & Outcomes Research Unit University Hospital Birmingham, UK ‘VTE PREVENTION NHS SHOWCASE’ 16th September 2013

  2. Quality and Outcomes Research Unit University Hospital Birmingham Primary Care and Population Health University College London, UK

  3. Death from PE 80% autopsy rate 9% PE Clinical diagnosis wrong in 84% of cases What is the incidence in 2013? Karwinski & Svendsen J Clin Path 1989

  4. VTE-PE Deaths in Europe Awareness Prevention Prevention 59% 34% 7% A T Cohen et al VITAE Study, Thrombosis and Haemostasis 2007; 98:756-764

  5. Evidence based medicine1970’s • Trials post surgical thromboprophylaxis • Heparin, aspirin, dextrans Power to detect reduction fatal PE 0.8% - 0.4% 20,000

  6. Commissioning for Quality and Innovation (CQUIN) 2010-2011 • AIM: Reduce avoidable death, disability and chronic ill health from venous-thromboembolism (VTE) • METHOD: >90% of all patients admitted to hospital should have VTE risk assessment • DRIVER: Up to £ 500,000 withheld from large acute trusts who do not achieve target

  7. Patient pathway: From risk assessment to outcome CQUIN Outcome of interest Intervention (socks, pharmacological) VTE risk assessment Reduced VTE (fatal, non fatal) Outcome for payment Patient and staff awareness of VTE Increased non fatal VTE, reduced fatal VTE

  8. Aim of our study • Assess whether achieving the CQUIN target had impact on: • VTE Mortality • VTE non fatal hospital readmissions

  9. Study Population163 hospital trusts; July 2010-March 2012 • Principal analysis: • All hospital admission > 3 days • Supportive analyses: • Admissions < 4 days • Day cases • Clinical sub-groups

  10. Data source HES ONS UNIFY2 163 Acute Trusts Admissions between: July 2010-March 2012 Death certificate data Hospital level VTE-assessment data

  11. Rate of VTE assessment in England

  12. Monthly assessment rate by trust

  13. Summary DataJuly 2010- March 2012 VTE Risk Assessment 17,528.316 80.60% Admissions > 3 days 4,141,041 23.62% VTE-Related Readmissions 8,578 0.21% VTE In-Hospital deaths 4,334 0.10% VTE In-Hospital deaths ( Primary) 1,318 0.03% VTE deaths within 90 days 1,651 0.04% VTE deaths within 90 days (Primary) 895 0.02%

  14. Primary VTE deaths over time In-Hospital Deaths Post-discharge Deaths

  15. Statistical Analyses • Non linear mixed models • Poisson / Mixed error • Log Link Function • Radial Smoother Spline function for time (random effects) • Random Intercepts (Trusts) • Including count of events of interest by trust / month as response variable • Offset is loge(n) where n is the number of relevant admissions • Fixed effect time is centred scale for month (across 21 months included) • Fixed effect is whether the trust has achieved quality standards in the relevant month (binary) Enabling estimation of the change in risk associated with achieving screening target

  16. End-point definitions • Primary VTE Death: VTE in Position 1 death certificate • VTE Related Death: VTE position 1-3 death certificate • In-Hospital and 90 days post-discharge • Total: in-hospital + 90 days post-discharge • Non-Fatal Readmissions * VTE ICD-10 codes from the NHS-Outcome Framework 2013/14

  17. Patients >3 days hospital stay Relative Risk (95% CI; p: n = events) VTE related Readmissions • 1.04 (0.97, 1.11; p=0.301: n=8578) VTE related deaths at 90 days • 0.91 (0.79, 1.05; p=0.196: n=1651) * Primary VTE Deaths at 90 days • 0.81 (0.67, 0.97; p=0.026: n=895) VTE related inhospital deaths • 0.92 (0.84, 1.00; p=0.057: n=4334) Primary VTE related inhospital deaths • 0.86 (0.74, 1.01; p=0.061: n=1318) * Total VTE related deaths • 0.92 (0.85, 0.99; p=0.033: n=5985) * Total Primary VTE related deaths • 0.85 (0.75, 0.96; p=0.011: n=2213) 0.5 1 2 Reduction with Programme Increase with Programme

  18. Patients < 4 days hospital stay (excluding day cases) Relative Risk (95% CI; p: n = events) VTE related deaths at 90 days 0.74 (0.61, 0.90; p=0.003: n=874) Primary VTE Deaths at 90 days 0.61 (0.48, 0.79; p=0.0002: n=512) 0.2 0.5 1 Reduction with Programme

  19. Day cases

  20. Relative Risk Reduction for DeathNon-surgical admissions P=0.001 P=0.006 P=0.04 % Risk Reduction

  21. Hip Fracture CCS Grouping Relative Risk (95% CI; p: n = events) VTE related Readmissions 1.04 (0.82, 1.32; p=0.765: n=494) VTE related deaths at 90 days 0.77 (0.52, 1.14; p=0.191: n=164) Primary VTE Deaths at 90 days 0.69 (0.38, 1.25; p=0.220: n=68) VTE related inhospital deaths 1.05 (0.68, 1.62; p=0.83: n=141) Primary VTE related inhospital deaths 0.86 (0.20, 3.63; p=0.839: n=14) Total VTE related deaths 0.89 (0.66, 1.20; p=0.429: n=305) Total Primary VTE related deaths 0.71 (0.41, 1.25; p=0.232: n=82) 0.2 0.5 1 2 5 Reduction with Programme Increase with Programme

  22. Nervous System CCS Grouping Relative Risk (95% CI; p: n = events) VTE related Readmissions 1.34 (1.08, 1.67; p=0.009: n=556) VTE related deaths at 90 days 0.73 (0.47, 1.14; p=0.163: n=123) Primary VTE Deaths at 90 days 0.46 (0.24, 0.90; p=0.023: n=60) VTE related inhospital deaths 0.68 (0.52, 0.88; p=0.004: n=389) Primary VTE related inhospital deaths 0.70 (0.40, 1.21; p=0.202: n=92) Total VTE related deaths 0.72 (0.57, 0.91; p=0.0054: n=512) Total Primary VTE related deaths 0.61 (0.40, 0.94; p=0.025: n=152) 0.2 0.5 1 2 Reduction with Programme Increase with Programme

  23. Estimation lives savedBased on 2011 if all hospitals achieved 90% screening rate 430

  24. Conclusions • There is evidence to support an impact of the National VTE CQUIN in reducing hospital associated VTE mortality but not VTE readmissions. • The effect is also seen in patients with duration of admission <4 days. • Further subgroup analysis is required to refine which patient groups are benefiting and which patient groups should be considered for additional interventions.

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