Optimisation of the deployment of automated external defibrillators in public places in England.

Background: Ambulance services treat over 32,000 patients sustaining an out-of-hospital cardiac arrest annually, receiving over 90,000 calls. The definitive treatment for out-of-hospital cardiac arrest is defibrillation. Prompt treatment with an automated external defibrillator can improve survival significantly. However, their location in the community limits opportunity for their use. There is a requirement to identify the optimal location for an automated external defibrillator to improve out-of-hospital cardiac arrest coverage, to improve the chances of survival.

Methods: This was a secondary analysis of data collected by the Out-of-Hospital Cardiac Arrest Outcomes registry on historical out-of-hospital cardiac arrests, data held on the location of automated external defibrillators registered with ambulance services, and locations of points of interest. Walking distance was calculated between out-of-hospital cardiac arrests, registered automated external defibrillators and points of interest designated as potential sites for an automated external defibrillator. An out-of-hospital cardiac arrest was deemed to be covered if it occurred within 500 m of a registered automated external defibrillator or points of interest. For the optimisation analysis, mathematical models focused on the maximal covering location problem were adapted. A de novo decision-analytic model was developed for the cost-effectiveness analysis and used as a vehicle for assessing the costs and benefits (in terms of quality-adjusted life-years) of deployment strategies. A meeting of stakeholders was held to discuss and review the results of the study.

Results: Historical out-of-hospital cardiac arrests occurred in more deprived areas and automated external defibrillators were placed in more affluent areas. The median out-of-hospital cardiac arrest - automated external defibrillator distance was 638 m and 38.9% of out-of-hospital cardiac arrests occurred within 500 m of an automated external defibrillator. If an automated external defibrillator was placed in all points of interests, the proportion of out-of-hospital cardiac arrests covered varied greatly. The greatest coverage was achieved with cash machines. Coverage loss, assuming an automated external defibrillator was not available outside working hours, varied between points of interest and was greatest for schools. Dividing the country up into 1 km grids and placing an automated external defibrillator in the centre increased coverage significantly to 78.8%. The optimisation model showed that if automated external defibrillators were placed in each points-of-interest location out-of-hospital cardiac arrest coverage levels would improve above the current situation significantly, but it would not reach that of optimisation-based placement (based on grids). The coverage efficiency provided by the optimised grid points was unmatched by any points of interest in any region. An economic evaluation determined that all alternative placements were associated with higher quality-adjusted life-years and costs compared to current placement, resulting in incremental cost-effectiveness ratios over £30,000 per additional quality-adjusted life-year. The most appealing strategy was automated external defibrillator placement in halls and community centres, resulting in an additional 0.007 quality-adjusted life-year (non-parametric 95% confidence interval 0.004 to 0.011), an additional expected cost of £223 (non-parametric 95% confidence interval £148 to £330) and an incremental cost-effectiveness ratio of £32,418 per quality-adjusted life-year. The stakeholder meeting agreed that the current distribution of registered publicly accessible automated external defibrillators was suboptimal, and that there was a disparity in their location in respect of deprivation and other health inequalities.

Conclusions: We have developed a data-driven framework to support decisions about public-access automated external defibrillator locations, using optimisation and statistical models. Optimising automated external defibrillator locations can result in substantial improvement in coverage. Comparison between placement based on points of interest and current placement showed that the former improves coverage but is associated with higher costs and incremental cost-effectiveness ratio values over £30,000 per additional quality-adjusted life-year.

Study Registration: This study is registered as researchregistry5121.

Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR127368) and is published in full in Health and Social Care Delivery Research; Vol. 13, No. 5. See the NIHR Funding and Awards website for further award information.