Probability of Survival (Ps) & Hospital Survival Rate (Ws) The Trauma Audit & Research Network (TARN)

Probability of Survival Once ISS is assigned Probability of Survival (Ps) calculated each submission

Why calculate PS? Need to assign weight to deaths and survivors. Some deaths more statistically significant than others. Case mix adjustment. Performances measurement: hospital and networks.

History of PS TARN developed first Ps model in 2004 Remodelled in 2007, 2009, 2012 4 components used in Ps since 2004: ISS Age Gender GCS

PS 12 model Age Gender ISS GCS/ intubation i PS 12 calculation $ 63.0%

What is Ps? PS% is retrospective measure of pts with same profile on TARN database. TARN database: past 4 years (Approx 200,000 cases) Ps = 63%, then 63 out of every 100 patients with that profile have previously survived. 37 out of every 100 patients have previously died.

Probability of Survival Ps is calculated using: GCS taken on arrival in ED at first receiving hospital where unavailable Pre Hospital GCS Presence of Intubation/ventilation Impute a “probable” GCS (equivalent weighting)

PS14 developments Pre-Existing Medical Conditions (PMC) added Launched December 2014 Pre-Existing Medical Conditions (PMC) added Charlson comorbidity index (CCI) adds ‘weighting’ PMC True 30 day outcome model introduced ONS (Office of National Statistics) data linkage using NHS No.

PS 14 –PMC and true 30 day outcome Launched December 2014 Age Gender ISS GCS/ intubation PMC i PS 14 calculation $ Patient PS ONS outcome linkage * *Charlson index (1984, revised).

Pre-Existing Medical Conditions PS14 Weighting groups Pre-Existing Medical Conditions Weight PMC group Bone conditions Connective tissue disorder Diabetes GU disease HIV Mental health Neurological disorders Nil Paraplegia Pulmonary disease 1-5 Alcohol Blood conditions Cancer CVA Congestive heart failure Dementia MI Other conditions Peripheral vascular disease 6-10 Metastatic cancer/Haematological malignancy Renal disease >10 Liver disease

Weightings for Age, GCS, Gender & PMC PS 14 Weightings for Age, GCS, Gender & PMC Age: 25 Gender: Male ISS: 25 GCS: 15 PMC: Nil i PS 14 calculation $ Ps: 98.7%

Weightings for Age, GCS, Gender & PMC PS 14 Weightings for Age, GCS, Gender & PMC Age: 25 Gender: Male ISS: 25 GCS: 15 PMC: Alcohol abuse i PS 14 calculation $ Ps: 97.8%

Weightings for Age, GCS, Gender & PMC PS 14 Weightings for Age, GCS, Gender & PMC Age: 25 Gender: Male ISS: 25 GCS: 15 PMC: Alcohol Abuse Liver Disease i PS 14 calculation $ Ps: 93.7%

Weightings for Age, GCS, Gender & PMC PS 14 Weightings for Age, GCS, Gender & PMC Age: 25 Gender: Male ISS: 25 GCS: 3 PMC: Alcohol Abuse Liver Disease i PS 14 calculation $ Ps: 25.3%

Weightings for Age, GCS, Gender & PMC PS 14 Weightings for Age, GCS, Gender & PMC Age: 65 Gender: Male ISS: 25 GCS: 3 PMC: Alcohol Abuse Liver Disease i PS 14 calculation $ Ps: 6.5%

Weightings for Age, GCS, Gender & PMC PS 14 Weightings for Age, GCS, Gender & PMC Age: 65 Gender: Female ISS: 25 GCS: 3 PMC: Alcohol Abuse Liver Disease i PS 14 calculation $ Ps: 7.06%

Importance of accurate injury detail PS 14 Importance of accurate injury detail Full injury detail Code Subdural haematoma bilateral & 2cm thick on both sides 140655.5 Base of skull fracture 150200.3 5 ribs fractured on left 450203.3 Full thickness Rectal laceration 543624.3 Spiral Fracture of left Shaft of Femur 853251.3 Vertical Shear fracture to pelvis with blood loss >20% 856173.5 Open Comminuted fracture to Tibial Shaft 854272.3 Accurate ISS Accurate Ps 59 49% Incomplete injury detail Code Subdural haematoma 140650.4 Base of skull fracture 150200.3 Ribs fractured on left 450210.2 Rectal laceration 543620.2 Fracture of left Shaft of Femur 853221.3 Pelvic Fracture 856151.2 Tibial Shaft Fracture 854221.2 Incomplete ISS 29

Importance of accurate injury detail Ps 14 Importance of accurate injury detail Age: 40 Gender: Male ISS: 29 GCS: 5 PMC: Nil i PS 14 calculation $ Ps: 79%

PS breakdown: 4 years Calendar data: Shown on Website Ps Bandings: Expanded for PS14 No. of patients in each band No. of expected survivors for each band Actual number of survivors Difference = Actual – Expected x 100 No. in group Adjusted Difference = Difference x fraction of pts on TARN database

Hospital Survival Rate: 4 years Calendar data +1.2 Survivors Statistically significant outcome (+0.39 to +1.97) +1.2 Survivors Not Statistically significant (-1.83 to +4.2) Total Ws shown Yearly Ws shown

Comparative Outcome Analysis (Ws) graph Compares outcomes between all submitting Hospitals 4 Comparative Outcome graphs included in Clinical Reports: 2 x Caterpillar plots (showing outcomes by Survival Rate) Outcome at 30 days or discharge (whichever is sooner) True 30 day outcome (linked to ONS data)

95% confidence intervals CATERPILLAR PLOT: Ascending Survival rate Your hospital 95% confidence intervals All hospitals

Comparative Outcome Analysis (Ws graphs) Compare Outcomes between all submitting Hospitals 4 Comparative Outcome graphs included in Clinical Reports: 2 x Caterpillar plots (showing outcomes by Survival Rate) Outcome at 30 days or discharge (whichever is sooner) True 30 day outcome (linked to ONS data) 2 x Funnel plots (showing outcomes by Precision –no. of cases)

FUNNEL PLOT: Precision (no. of cases) Your hospital All hospitals Lower Precision: Fewer cases (not as reliable) Greater Precision: More cases (more reliable)