LEPH Conference 2018 James Nunn Linking police collision data and hospital trauma patient data. Enabling comparison of culpable drivers from serious injury non-fatal collisions with those who cause fatal injuries. LEPH Conference 2018 James Nunn Loughborough University Design School, Transport Research Group

Background There had been steady decline in fatal casualties until 2010. Since then the numbers have plateaued. Fatalities. Reported road casualties in Great Britain: 2017 annual report, Department for Transport, 2018

Background The number of casualties with serious injuries has also stopped declining. New methods of intervention or how to apply interventions may be required to induce a new downwards trend. Serious injuries. Reported road casualties in Great Britain: 2017 annual report, Department for Transport, 2018

Aim Identification of the people causing serious (MAIS3+) injuries in road traffic collisions. (AIS - Abbreviated Injury Scale, MAIS – Maximum AIS for a casualty. International system of trauma grading administered by the Association for the Advancement of Automotive Medicine) Most interventions are based on population stats and do not capture the perpetrators. Police injury severity classification does not use AIS and is for the serious category is subjective and broad – quadriplegic to a broken little finger MAIS3+ is the standard adopted by the European Commission to allow international comparison

Study 1 Project objective Link police collision data and hospital trauma patient data. Identify the serious injury (MAIS3+) subset. Identify all motor vehicle drivers involved in serious injury (MAIS3+) collisions. First of 3 Studies MAIS3+ is the European standard for severe/serious injury.

Methods - Data Sets for Linking Cambridgeshire Police collisions data (STATS19) 2012- 2017 No common identifier East of England Trauma Audit and Research Network Data (TARN) 2012- 2017 Four common variables (Age, sex, incident date, first string of postcode) – formatted – no missing data 10498 collisions 23741 subjects 1907 individual trauma patients STATS19 Department for Transport – Police recorded - 174 variables – STATS20 Fatal 158 Collisions – 174 Casualties; 1593 serious – 1823 casualties; 8745 slight – 12104 casualties East of England six counties; Bedfordshire, Hertfordshire, Essex, Cambridgeshire, Suffolk and Norfolk TARN 43 variables TARN does not contain all MAIS3+ injuries for East of England – Entry Criteria 72 hrs inpatient – ITU/HDU any stay TARN already filtered for Collisions

Validated Results (MAIS3+) Methods and Results - Data Linking 1. Deterministic linkage (all four variables must match) 2. Probabilistic linkage (allows variation in age ± 5 years) Deterministically linked records removed Full collision data retrieved Results 295 linked records 257 MAIS3+ linked records Results 31 linked records 22 MAIS3+ linked records Validated Results (MAIS3+) 268 linked records 243 collisions 416 motor vehicle drivers Validated 95.8% true- matches All records retrieved Deterministically linked randomly selected 10% (n=26) of the MAIS3+ records Probabilistically all records 95.8% of the deterministically linked records were true matches. 58.6% of the probabilistically linked records were true matches Validated 58.6% true- matches

Study 2 Project objective Undertake culpability scoring on the motor vehicle drivers from the serious injury (MAIS3+) subset. Identify all culpable motor vehicle drivers involved in serious injury (MAIS3+) collisions. First of 3 Studies MAIS3+ is the European standard for severe/serious injury.

Methods and Results – Culpability Scoring STATS19 full collision data Map STATS19 data to Robertson and Drummer (1994) criteria Robertson and Drummer (1994) culpability scoring tool Results 263 (63.2%) culpable drivers 31 (7.5%) contributory drivers 118 (28.4%) non-culpable drivers 4 (1.0%) could not be scored Apply scoring tool criteria to STATS19 data for validated matches to score individual motor vehicle drivers Robertson and Drummer 1994 chosen as it has a proven track record in the literature and is less subjective than previous scoring tools such a Terhune 1983 Explain principle – Culpable until mitigation applied, if sufficient mitigation achieved, culpability removed Mapping examples -

Next stage Culpability score using alternative tool (Brubacher, Chan and Asbridge (2012) for comparison Culpability score motor vehicle drivers from fatal collisions for comparison Study 3: Geodemographic profile the culpable drivers from MAIS3+ collisions using their home post codes. Target interventions. Initial analysis – the culpability is comparable between the two scoring tools, some minor differences relating primarily to single vehicle/ pedestrian collisions Fatal collisions showed a slightly lowere level of culpability

Email: J.Nunn@lboro.ac.uk Any Questions Email: J.Nunn@lboro.ac.uk Acknowledgements Co-authors Jo Barnes, Andrew Morris, Emily Petherick. Loughborough University, Epinal Way, Loughborough, LE11 3TU, UK Roderick Mackenzie. Cambridge University Hospitals, Addenbrookes Hospital, Hills Road, Cambridge, CB2 0QQ, UK. Roderick.mackenzie@addenbrookes.nhs.uk Matt Staton. Cambridgeshire County Council, Shire Hall, Castle Hill, Cambridge, CB3 0AP, UK Matt.Staton@cambridgeshire.gov.uk Thanks to Cambridgeshire County Council, Cambridgeshire Constabulary and Cambridge University Hospital for providing the data and facilitating the process and the Road Safety Trust for funding the project