ArticleBMC public health2021
Spatial-time analysis of cardiovascular emergency medical requests: enlightening policy and practice.
Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Urban Environmental Determinants and Spatiotemporal Patterns of Emergency Medical Service Response to Traumatic Injuries: A Five-Year Population-Based Study.International journal of environmental research and public health · 2026Article
- Barriers and Facilitators to Smart Healthcare Adoption Among Chinese Patients with Cardiovascular Disease and Their Caregivers: A Qualitative Study.Healthcare (Basel, Switzerland) · 2025Article
- Short-Term Exposure to Fine Particulate Matter (PMGeoHealth · 2025Article
- Bayesian spatial-temporal analysis and determinants of cardiovascular diseases in Tanzania mainland.BMC medical research methodology · 2024Article
- A timeliness analysis of emergency services and cardiovascular outcomes in cardiac patients referred through prehospital emergency services between 2020 and 2023: a cross-sectional study in Iran.BMC research notes · 2024Article
- Challenges in Emergency Medical Services in Mega Cities: A Qualitative Study in Iran.Bulletin of emergency and trauma · 2024Article
- A Spatial Variation Analysis of In-Hospital Stroke Mortality Based on Integrated Pre-Hospital and Hospital Data in Mashhad, Iran.Archives of Iranian medicine · 2023Article
- One-year spatiotemporal database of Emergency Medical Service (EMS) calls in Mashhad, Iran: data on 224,355 EMS calls.BMC research notes · 2022Article
- Measuring COVID-19 vaccination coverage: an enhanced age-adjusted two-step floating catchment area model.Infectious diseases of poverty · 2021Article
- A spatial-epidemiological dataset of subjects infected by SARS-CoV-2 during the first wave of the pandemic in Mashhad, second-most populous city in Iran.BMC research notes · 2021Article
- The Role of Social Media in the Advent of COVID-19 Pandemic: Crisis Management, Mental Health Challenges and Implications.Risk management and healthcare policy · 2021Article
- Religious Affiliation, Daily Spirituals, and Private Religious Factors Promote Marital Commitment Among Married Couples: Does Religiosity Help People Amid the COVID-19 Crisis?Frontiers in psychology · 2021Article
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12 authors.
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Abstract
backgroundResponse time to cardiovascular emergency medical requests is an important indicator in reducing cardiovascular disease (CVD) -related mortality. This study aimed to visualize the spatial-time distribution of response time, scene time, and call-to-hospital time of these emergency requests. We also identified patterns of clusters of CVD-related calls.
methodsThis cross-sectional study was conducted in Mashhad, north-eastern Iran, between August 2017 and December 2019. The response time to every CVD-related emergency medical request call was computed using spatial and classical statistical analyses. The Anselin Local Moran's I was performed to identify potential clusters in the patterns of CVD-related calls, response time, call-to-hospital arrival time, and scene-to-hospital arrival time at small area level (neighborhood level) in Mashhad, Iran.
resultsThere were 84,239 CVD-related emergency request calls, 61.64% of which resulted in the transport of patients to clinical centers by EMS, while 2.62% of callers (a total of 2218 persons) died before EMS arrival. The number of CVD-related emergency calls increased by almost 7% between 2017 and 2018, and by 19% between 2017 and 2019. The peak time for calls was between 9 p.m. and 1 a.m., and the lowest number of calls were recorded between 3 a.m. and 9 a.m. Saturday was the busiest day of the week in terms of call volume. There were statistically significant clusters in the pattern of CVD-related calls in the south-eastern region of Mashhad. Further, we found a large spatial variation in scene-to-hospital arrival time and call-to-hospital arrival time in the area under study.
conclusionThe use of geographical information systems and spatial analyses in modelling and quantifying EMS response time provides a new vein of knowledge for decision makers in emergency services management. Spatial as well as temporal clustering of EMS calls were present in the study area. The reasons for clustering of unfavorable time indices for EMS response requires further exploration. This approach enables policymakers to design tailored interventions to improve response time and reduce CVD-related mortality.
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