Geospatial Analysis of Ambulance Station Coverage of the Acute Coronary Syndrome Incidents in Semey, Kazakhstan

Geospatial Analysis of Ambulance Station Coverage of the Acute Coronary Syndrome Incidents in Semey, Kazakhstan

BACKGROUND: One of the main causes of death is cardiovascular diseases. Among cardiovascular diseases ischemic heart disease is major a cause of death. Emergency medical service and ambulance play the key role in providing timely care. AIM: This study was carried out to investigate the coverage area...

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Veröffentlicht in:Open access Macedonian journal of medical sciences 2020-09, Vol.8 (E), p.638-646
Hauptverfasser: Shaltynov, Askhat, Abiltaev, Askar, Konabekov, Bakytzhan, Jamedinova, Ulzhan, Aldyngurov, Daulet, Utegenova, Aigul, Myssayev, Ayan
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container_issue E
container_start_page 638
container_title Open access Macedonian journal of medical sciences
container_volume 8
creator Shaltynov, Askhat
Abiltaev, Askar
Konabekov, Bakytzhan
Jamedinova, Ulzhan
Aldyngurov, Daulet
Utegenova, Aigul
Myssayev, Ayan
description BACKGROUND: One of the main causes of death is cardiovascular diseases. Among cardiovascular diseases ischemic heart disease is major a cause of death. Emergency medical service and ambulance play the key role in providing timely care. AIM: This study was carried out to investigate the coverage area of calls of acute coronary syndrome (ACS) by ambulance stations in regards to the time using GIS-analyze. METHODS: This was descriptive study which contains secondary data from Semey ambulance service’s database about all 1704 ACS with and without elevation of ST segment emergency calls in Semey city (Kazakhstan) over the period from August 1, 2017 to May 30, 2018. Spatial Analyst and Network Analyst Extensions of ArcGIS 10.7 (ESRI, CA, USA) were used to define high ACS density areas and find 10, 15, and 20 min time response areas. Kernel density tool calculates a magnitude-per-unit area from point or polyline features using a kernel function to fit a smoothly tapered surface to each point or polyline. RESULTS: The distance to the patient for ambulances was from 7 to 15 km. For most calls, the response time was
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Among cardiovascular diseases ischemic heart disease is major a cause of death. Emergency medical service and ambulance play the key role in providing timely care. AIM: This study was carried out to investigate the coverage area of calls of acute coronary syndrome (ACS) by ambulance stations in regards to the time using GIS-analyze. METHODS: This was descriptive study which contains secondary data from Semey ambulance service’s database about all 1704 ACS with and without elevation of ST segment emergency calls in Semey city (Kazakhstan) over the period from August 1, 2017 to May 30, 2018. Spatial Analyst and Network Analyst Extensions of ArcGIS 10.7 (ESRI, CA, USA) were used to define high ACS density areas and find 10, 15, and 20 min time response areas. Kernel density tool calculates a magnitude-per-unit area from point or polyline features using a kernel function to fit a smoothly tapered surface to each point or polyline. RESULTS: The distance to the patient for ambulances was from 7 to 15 km. For most calls, the response time was &lt;10 min, which is the recommended national standard for emergency care. Density zones were divided into seven categories from white (from 0 to 3.4 cases/km2) to red (from 59.9 to 86.1 cases/km2). The largest high-density area of ACS cases was located in central part of the city on right-bank of the river. Furthermore, high density of ACS cases was identified in the areas of high rise buildings on the left bank of the river. CONCLUSION: GIS tools are useful tool that can be implemented in planning of emergency medical service. In our study, we determined that the service areas of ambulance stations cover the needs of patients with ACS. But nevertheless, it is necessary to plan the ambulance care to nearby regions and villages. In addition, it needs to consider the development of new areas of city and patterns of emergency calls in planning.</description><identifier>ISSN: 1857-9655</identifier><identifier>EISSN: 1857-9655</identifier><identifier>DOI: 10.3889/oamjms.2020.5160</identifier><language>eng</language><ispartof>Open access Macedonian journal of medical sciences, 2020-09, Vol.8 (E), p.638-646</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids></links><search><creatorcontrib>Shaltynov, Askhat</creatorcontrib><creatorcontrib>Abiltaev, Askar</creatorcontrib><creatorcontrib>Konabekov, Bakytzhan</creatorcontrib><creatorcontrib>Jamedinova, Ulzhan</creatorcontrib><creatorcontrib>Aldyngurov, Daulet</creatorcontrib><creatorcontrib>Utegenova, Aigul</creatorcontrib><creatorcontrib>Myssayev, Ayan</creatorcontrib><title>Geospatial Analysis of Ambulance Station Coverage of the Acute Coronary Syndrome Incidents in Semey, Kazakhstan</title><title>Open access Macedonian journal of medical sciences</title><description>BACKGROUND: One of the main causes of death is cardiovascular diseases. Among cardiovascular diseases ischemic heart disease is major a cause of death. Emergency medical service and ambulance play the key role in providing timely care. AIM: This study was carried out to investigate the coverage area of calls of acute coronary syndrome (ACS) by ambulance stations in regards to the time using GIS-analyze. METHODS: This was descriptive study which contains secondary data from Semey ambulance service’s database about all 1704 ACS with and without elevation of ST segment emergency calls in Semey city (Kazakhstan) over the period from August 1, 2017 to May 30, 2018. Spatial Analyst and Network Analyst Extensions of ArcGIS 10.7 (ESRI, CA, USA) were used to define high ACS density areas and find 10, 15, and 20 min time response areas. Kernel density tool calculates a magnitude-per-unit area from point or polyline features using a kernel function to fit a smoothly tapered surface to each point or polyline. RESULTS: The distance to the patient for ambulances was from 7 to 15 km. For most calls, the response time was &lt;10 min, which is the recommended national standard for emergency care. Density zones were divided into seven categories from white (from 0 to 3.4 cases/km2) to red (from 59.9 to 86.1 cases/km2). The largest high-density area of ACS cases was located in central part of the city on right-bank of the river. Furthermore, high density of ACS cases was identified in the areas of high rise buildings on the left bank of the river. CONCLUSION: GIS tools are useful tool that can be implemented in planning of emergency medical service. In our study, we determined that the service areas of ambulance stations cover the needs of patients with ACS. But nevertheless, it is necessary to plan the ambulance care to nearby regions and villages. 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Among cardiovascular diseases ischemic heart disease is major a cause of death. Emergency medical service and ambulance play the key role in providing timely care. AIM: This study was carried out to investigate the coverage area of calls of acute coronary syndrome (ACS) by ambulance stations in regards to the time using GIS-analyze. METHODS: This was descriptive study which contains secondary data from Semey ambulance service’s database about all 1704 ACS with and without elevation of ST segment emergency calls in Semey city (Kazakhstan) over the period from August 1, 2017 to May 30, 2018. Spatial Analyst and Network Analyst Extensions of ArcGIS 10.7 (ESRI, CA, USA) were used to define high ACS density areas and find 10, 15, and 20 min time response areas. Kernel density tool calculates a magnitude-per-unit area from point or polyline features using a kernel function to fit a smoothly tapered surface to each point or polyline. RESULTS: The distance to the patient for ambulances was from 7 to 15 km. For most calls, the response time was &lt;10 min, which is the recommended national standard for emergency care. Density zones were divided into seven categories from white (from 0 to 3.4 cases/km2) to red (from 59.9 to 86.1 cases/km2). The largest high-density area of ACS cases was located in central part of the city on right-bank of the river. Furthermore, high density of ACS cases was identified in the areas of high rise buildings on the left bank of the river. CONCLUSION: GIS tools are useful tool that can be implemented in planning of emergency medical service. In our study, we determined that the service areas of ambulance stations cover the needs of patients with ACS. But nevertheless, it is necessary to plan the ambulance care to nearby regions and villages. In addition, it needs to consider the development of new areas of city and patterns of emergency calls in planning.</abstract><doi>10.3889/oamjms.2020.5160</doi><tpages>9</tpages></addata></record>
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