Background:

Every year ambulance services receive over 90,000 calls to attend an out-of-hospital cardiac arrest (OHCA), of which about a third receive treatment from ambulance clinicians. Less than 10% of these cases survive to go home from hospital. This project is working with UK Ambulance Services, and uses existing information collected by the services during the course of their routine duties. It has developed a standard way of collecting information about OHCA and for finding out if a resuscitation attempt was successful. The information is used to obtain a better understanding of why survival rates vary so widely around the country. It works out which are the most effective treatments and helps ambulance services improve the quality of care for victims of OHCA.

Policy and Practice Partners:

National Association of Ambulance Service Medical Directors

Ambulance Association of Chief Executives

NHS England

Co-Funding partners:

British Heart Foundation

Resuscitation Council UK

Aims and Objectives:

The aim is to collect and summarise high-quality data to support UK initiatives to improve outcomes from out of hospital cardiac arrest. The objectives are:

1. Summarise the epidemiology, treatments, and outcomes from OHCA across the UK.

2. Produce reports to allow benchmarking and drive quality improvement.

3. Support high-quality observational studies and randomised trials to strengthen the Chain of Survival.

4. Encourage collaboration to maximise benefits from use of data submitted to OHCAO.

5. Facilitate data linkage to support a better understanding of the full patient pathway for cardiac arrest (prevention, event, recovery, rehabilitation)

Methods:

The project is a prospective observational study of all OHCAs that occur in the UK, attended by or on behalf of NHS Ambulance Services, and where resuscitation is attempted. Data, submitted by each ambulance service, includes: System characteristics, EMS dispatch characteristics, patient characteristics, EMS performance process variables. Data definitions will follow the Utstein 2014 recommendations. The main outcome variables are: Any ROSC, ROSC at hospital handover, 30-day survival & survival to hospital discharge. Descriptive statistics are used to describe patient and event characteristics. Multivariable logistic regression models are used examine the effect of prognostic factors on the outcomes. Kaplan-Meier or Cox regression models are being used to identify factors that may predict patient survival.

Main Results:

Annual Epidemiology and Outcomes (warwick.ac.uk)

Conclusions:

Ongoing Project