Determinants of ambulance response time: A study in Sabah, Malaysia

Chin, Su Na; Cheah, Phee Kheng; Arifin, Muhamad Yaakub; Wong, Boh Leng; Omar, Zaturrawiah Ali; Yassin, Fouziah Md; Gabda, Darmesah

doi:10.1063/1.4980987

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…The traffic condition is a well-known factor in most of the studies on delayed response time [5][6][7] . Heavy traffic condition observed in this study such as congested road during peak hour and lack of cooperation from public affected the speed of ambulance travel and caused the delay in response time.…”

Section: Discussionmentioning

confidence: 99%

“…Since 1979, Emergency Medical Services (EMS) in the United States had adopted 8 minutes ambulance response time as international standard because of higher survival rates in patients with cardiac arrest who received earlier advanced life support (ALS) 1 . Many international and local studies had been conducted to improve ambulance response time as it has been accepted as one of the indicators for stratifying the quality of prehospital care in terms of service and patient's satisfaction [3][4][5][6][7][8][9] .…”

Section: Introductionmentioning

confidence: 99%

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Factors Contributing to Delayed Ambulance Response Time Using Ambulance Vehicle Locator and Global Integrating System (Avl- Gis) at Hospital Universiti Sains Malaysia

Asri

Yazid

Hamzah

et al. 2021

MJPHM

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This study aims to determine ambulance response time in KubangKerian district, Kelantan, Malaysia using Ambulance Vehicle Locator and Global Integrating System (AVL-GIS) device and the factors associated with delayed response time. This was a 6-months prospective, cross-sectional study conducted at Emergency and Trauma Department, Hospital Universiti Sains Malaysia (HUSM) in Kubang Kerian, Kelantan, Malaysia. The possible factors identified to have caused delayed ambulance response time from previous literature were included in this study. All prehospital cases from September 2017 until February 2018 attended to by AVL- GIS installed ambulances were included in this study. Data were obtained from the standardized prehospital Proforma forms and extracted from AVL-GIS using iGPS software. Simple and multiple logistic regression tests were used to determine the factors associated to delayed response time. From 505 cases, 75% found to be delayed case meanwhile 25% is non delayed case as defined in study protocol. Further analysis on delayed cases show that call duration, caller type, traffic condition, travelling time and team allocation time were associated with delayed ambulance response time. Evaluation of each component contributing to delayed ambulance response time is needed for intervention to improve prehospital care in the future.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Factors Contributing to Delayed Ambulance Response Time Using Ambulance Vehicle Locator and Global Integrating System (Avl- Gis) at Hospital Universiti Sains Malaysia

Asri

Yazid

Hamzah

et al. 2021

MJPHM

View full text Add to dashboard Cite

show abstract

“…Many factors may affect the response time, such as the type of ambulances, geographic differences, socio-demographic patterns, public awareness, traffic conditions, weather, and location of the incident. [22][23][24][25] Based on the results of a qualitative study that was conducted among Urmia personnel to identifying factors affecting pre-hospital time intervals, the most important obstacles related to pre-hospital intervals were the involvement of untrained people and urban infrastructure that delayed arriving at the crash scene or during hospital transportation. It is also emphasized that heavy work shifts, shortages in the emergency system, and a low number of personnel at dispatch centers can delay the response to calls.…”

Section: Response Intervalmentioning

confidence: 99%

Comparison of pre-hospital emergency services time intervals in patients with heart attack in Arak, Iran

et al. 2021

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Background: After cardiac arrest, the possibility of death or irreversible complications will highly increase in the absence of cardiac resuscitation within 4 to 6 minutes. Accordingly, measuring the pre-hospital services time intervals is important for better management of emergency medical services delivery. The purpose of this study then was to investigate pre-hospital time intervals for patients with heart attack in Arak city, based on locations and time variables.Methods: This is a retrospective descriptive cross-sectional study, which was conducted at the Arak Emergency Medical Services (EMS) during 2017-2018. Data were analyzed by SPSS version 13. Results:The total number of heart attack patients registered in Arak emergency medical services was 2,659 of which 51% of patients were males. Six percent of patients were under 25 and about 49 percent were between 46 and 65 years old. The average of activation, response,

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Statistical modeling of emergency medical services’ response and rescue times to road traffic crashes in the Kingdom of Saudi Arabia

Al-Zabidi¹,

Almannaa²,

Elhenawy³

et al. 2022

Case Studies on Transport Policy

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Determinants of ambulance response time: A study in Sabah, Malaysia

Cited by 5 publications

References 15 publications

Factors Contributing to Delayed Ambulance Response Time Using Ambulance Vehicle Locator and Global Integrating System (Avl- Gis) at Hospital Universiti Sains Malaysia

Factors Contributing to Delayed Ambulance Response Time Using Ambulance Vehicle Locator and Global Integrating System (Avl- Gis) at Hospital Universiti Sains Malaysia

Comparison of pre-hospital emergency services time intervals in patients with heart attack in Arak, Iran

Statistical modeling of emergency medical services’ response and rescue times to road traffic crashes in the Kingdom of Saudi Arabia

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