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04 ‘Beyond the emergency’: novel uses of ambulance data to identify vulnerable communities and improve pre-hospital care
  1. Harriet Moore4,
  2. Mark Gussy1,
  3. Aloysius Niroshan Siriwardena2,
  4. Bartholomew Hill3,
  5. David Nelson1,
  6. Jay Emery4,
  7. Robert Spaight5
  1. 1Lincoln International Institute for Rural Health, University of Lincoln, Lincoln, UK
  2. 2School of Health and Social Care, University of Lincoln, UK
  3. 3Water WISER CDT, University of Loughborough, UK
  4. 4Department of Geography, University of Lincoln, UK
  5. 5East Midlands Ambulance Service NHS Trust, Nottingham, UK


Background Ambulance data is often used to elucidate presentation characteristics, including patient demographics and medical conditions. There is a lack of research utilising geographical methods to understand the drivers of medical emergencies. During the COVID-19 pandemic, our team has produced an evolving research portfolio demonstrating novel uses of ambulance data, including geographical data linkage to explore the impact of built environments and socio-economic conditions on the geospatial heterogeneity of acute conditions.

Methods The research utilises 999 call data collated by the East Midlands Ambulance NHS Service including dispatch records, the impressions of paramedics attending emergencies, and paramedic decisions about patient care pathways. The region is a socio-economic, demographic, and geographic microcosm of the wider UK. The dataset includes all records between January 2018 and December 2020. Studies have involved: retrospective cross-sectional observational analyses comparing physical and mental health presentations between regions, sub-groups and across time-periods; geospatial analysis, such as identifying unusual regional condition clustering, and; the development of a geospatial early warning infection-severity index for identifying vulnerable communities.

Results The mental and physical impact of the COVID-19 pandemic on regions has not been homogenous; greatest vulnerability occurs at the intersection of demographic characteristics, socio-economic condition, and geospatial position in urban and rural landscapes. Key findings include: ambulance data captures the ‘gender health paradox’; the drivers of medical emergencies vary spatially, and; our infection-severity index highlights enduring health inequalities associated with historic linkages between post-industrial communities and their coastal counterparts.

Conclusions Ambulance data could be utilised in the early days of a pandemic to identify vulnerable communities, allocate protective equipment for health care workers, and to establish interventions to prevent mortality. Beyond the emergency, our findings reinforce the urgency of the male mental health agenda, the need for community-based care in low density rural areas, and the opportunities for preventing escalation.

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