Identifying and explaining clusters of acute physical and mental health conditions in the East Midlands of the UK and Ontario using ambulance call condition data – Satscan analysis and evaluation of health care system effectiveness (Emergency Medical Service Call Condition Cluster Study: EMSC3)

PROJECT TITLE IDENTIFYING AND EXPLAINING CLUSTERS OF ACUTE PHYSICAL AND MENTAL HEALTH CONDITIONS IN THE EAST MIDLANDS OF THE UK AND ONTARIO USING AMBULANCE CALL CONDITION DATA: SATSCAN ANALYSIS AND EVALUATION OF HEALTH CARE SYSTEM EFFECTIVENESS (EMERGENCY MEDICAL SERVICE CALL CONDITION CLUSTER STUDY: EMSC3)
Funding body School of Geography Seed Grant Funding 2019/2020 awarded to Dr Harriet Moore
Total funding  £2000
Team
  • Prof Niro Siriwardena, CaHRU, University of Lincoln
  • Dr Gina Agarwal, McMaster University, Ontario, Canada
  • Prof Frank Tanser, International Institute for Rural Health Care, University of Lincoln
  • Dr Harriet Moore, School of Human Geography, University of Lincoln
  • Rob Spaight, East Midlands Ambulance Service NHS Trust
  • Prof Mark Gussy, International Institute for Rural Health Care, University of Lincoln
  • Dr Melissa Pirrie, McMaster University, Ontario, Canada
  • Dr Ricardo Angeles, McMaster University
  • Dr. Iwona Bielska, , McMaster University
  • Brent McLeod, McMaster University & Hamilton Paramedic Service
  • Richard Ferron, Niagara EMS
  • Prof Kamlesh Khunti, Leicester Diabetes Centre, University of Leicester
  • Dr Elise Rowan, CaHRU, University of Lincoln
  • Prof Graham Law, CaHRU, University of Lincoln
Team/consortium
  • University of Lincoln, UK
  • University of Leicester, UK
  • McMaster University, Ontario, Canada
  • Hamilton Paramedic Service
  • Niagara Emergency Medical Services
Overarching aim To investigate the epidemiology of 999 ambulance attendances for ambulatory care sensitive conditions in East Midlands, UK and Ontario, Canada, by identifying spatial clusters of single and multiple common ambulance acute service-sensitive conditions (diabetes, asthma, mental health, COPD, angina and epilepsy), using call condition records from the East Midlands Ambulance Service NHS Trust, and equivalent services in Ontario involving state-of-the-art spatial analysis (with SatScan software). We aim to identify clusters of higher/lower than expected occurrence of acute conditions in relation to socioeconomic factors, such as deprivation, environmental factors, such as access to healthy assets and hazards, and built environment factors, such as social housing. In the current climate of COVID-19 pandemic, this analysis will begin with a focus on acute respiratory conditions, particularly focussing on people with underlying or multiple comorbidities (e.g. chronic heart, lung and kidney disease or diabetes) and calls for suspected COVID-19. The study is on the UK Health Research Authority list of approved COVID-19 research.
Objectives Primary objective
1. To identify unique single and co-occurring spatial clusters of most commonly occurring NHS ambulatory conditions for younger and older populations using EMAS data for acute presentations in the UK, and equivalent emergency service data for Ontario, Canada.
Secondary objectives
To conduct a comparative analysis of Emergency Medical Systems (ambulance) in the UK (East Midlands) and Canada (Ontario), including:
2. To identify spatial clusters of higher/lower than expected occurrence of single and multiple acute conditions including calls for suspected COVID-19 with consideration of socioeconomic and environmental factors.
3. To explore underlying mechanisms and factors that influence the spatial dynamics of acute presentation in younger (<18) and older (18+) people.
4. To elucidate pathways and mechanisms that explain the observed single and multimorbidity patterns by using the Social-Ecological Framework to synthesize multi-scale data, including big spatial data (e.g., EMS, deprivation and AHAHI).
5. To explore factors linked with transportation rates in children (<18) and adults (18+) for acute (initially respiratory) presentations in people with underlying or multiple at-risk factors for suspected SARS-COV2 infection (e.g. chronic heart, lung and kidney disease or diabetes).
Methods Spatial cluster analysis.
Outcomes
  • Partnerships: a key outcome will be the development of collaborative partnerships between the UK and Canada involving universities and ambulance services in the East Midlands and Ontario with a focus on rural healthcare.
  • Future funding bids: We will use this pump priming as the basis for submission for external funding to further develop research in this area on a wider scale.
Outputs Peer reviewed publications and conference presentations and recommendations for EMS service delivery.
Impact We aim to create impact by using the findings to inform future Emergency Medical Services provision and design.

 

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