Strategic PAD positioning: a scoping review

Out-of-hospital cardiac arrest (OHCA) is a major contributor to overall morbidity and mortality. Survival depends on several factors, including rhythm shockability and timely defibrillation; for the latter, the availability of Public Access Defibrillators (PADs) is crucial. Across countries, PADs can be a limited resource, necessitating strategic placement to ensure optimal accessibility and effective utilization. The objective of this scoping review was to analyse existing experience with PAD positioning and to identify potential for the geospatial optimisation of PAD positioning.

An electronic search of PubMed and Scopus databases was performed to identify studies on PAD positioning. We included peer-reviewed articles as well as graduate and undergraduate theses, and excluded conference abstracts, books, and book chapters. Only English-language publications were considered. A Risk of Bias analysis was conducted and reported using Mixed Method Appraisal Tool. We adhered to PRISMA-ScR guidelines. Using the PCC framework, the Population was the general public, the Concept was PAD optimization, and the Context ranged from buildings to nations. Data charting was done manually. We quantitatively synthesized findings from included studies based on extracted data and Synthesis Without Meta-Analysis guidelines.

We included 43 works, mostly from North America. We found substantial diversity in study methodologies, outcome measures and results reporting. Within buildings, PADs are recommended to be positioned centrally or in elevators. Outside, places with high-footfall were preferred. Optimisation models most often employed the Maximal Covering Location Problem. Most studies based their models on the locations of existing and candidate PADs, alongside historical or simulated OHCA occurrences, and tried to minimise that distance.

In this scoping review of studies optimising PAD network deployment, we found that PAD network optimisation is feasible and improves coverage of historical OHCA locations. Data-driven positioning strategies should incorporate historical OHCA locations, population health indicators, and socioeconomic variables to identify high-risk zones effectively and inform appropriate PAD density. Future studies should adopt prospective and real-world design, while adhering to guidelines for reporting results.