Trends and characteristics in pre-hospital emergency care in Beijing from 2008 to 2017

Huang, Wei; Wang, Tianbing; He, Yingdong; Zhang, Huan; Zhou, Xiao‐Hua; Liu, Hui; Zhang, Jinjun; Tian, Zhen-Biao; Jiang, Baoguo

doi:10.1097/cm9.0000000000000770

Cited by 16 publications

(16 citation statements)

References 19 publications

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“…Furthermore, during the coronavirus disease 2019 (COVID-19) pandemic, EMS activations for cardiac events and opioid use/overdose are increasing, and ambulance response times are deteriorating ( 14 , 15 ). The supply and demand of EMS represent a challenge for both the EMS and hospital-based emergency departments ( 16 , 17 ).…”

Section: Introductionmentioning

confidence: 99%

Urban–sub-urban–rural variation in the supply and demand of emergency medical services

Geng

et al. 2023

Front. Public Health

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BackgroundEmergency medical services (EMSs) are a critical component of health systems, often serving as the first point of contact for patients. Understanding EMS supply and demand is necessary to meet growing demand and improve service quality. Nevertheless, it remains unclear whether the EMS supply matches the demand after the 2016 healthcare reform in China. Our objective was to comprehensively investigate EMS supply–demand matching, particularly among urban vs. sub-urban vs. rural areas.MethodsData were extracted from the Tianjin Medical Priority Dispatch System (2017–2021). From supply and demand perspectives, EMS resources and patient characteristics were analyzed. First, we performed a descriptive analysis of characteristics, used Moran's I to explore the spatial layout, and used the Gini coefficient to evaluate the equity of EMS supply and demand. Second, we analyzed urban–sub-urban–rural variation in the characteristics of EMS supply and demand by using the chi-square test. Finally, we examined the association between the EMS health resource density index and the number of patients by using the Spearman correlation and divided supply–demand matching types into four types.ResultsIn 2021, the numbers of medical emergency stations and ambulances were 1.602 and 3.270 per 100,000 population in Tianjin, respectively. There were gradients in the health resource density index of the number of emergency stations (0.260 vs. 0.059 vs. 0.036; P = 0.000) in urban, sub-urban, and rural areas. There was no spatial autocorrelation among medical emergency stations, of which the G values by population, geographical distribution, and the health resource density index were 0.132, 0.649, and 0.473, respectively. EMS demand was the highest in urban areas, followed by sub-urban and rural areas (24.671 vs. 15.081 vs. 3.210 per 1,000 population and per year; P = 0.000). The EMS supply met the demand in most districts (r = 0.701, P = 0.003). The high supply–high demand types with stationary demand trends were distributed in urban areas; the low supply–high demand types with significant demand growth trends were distributed in sub-urban areas; and the low supply–low demand types with the highest speed of demand growth were distributed in rural areas.ConclusionEMS supply quantity and quality were promoted, and the supply met the demand after the 2016 healthcare reform in Tianjin. There was urban–sub-urban–rural variation in EMS supply and demand patterns.

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Section: Introductionmentioning

confidence: 99%

Urban–sub-urban–rural variation in the supply and demand of emergency medical services

Geng

et al. 2023

Front. Public Health

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“…These studies have also linked the EMS demand increase to the concurrent population growth. Unfortunately, over the studied period the overall Piedmont population reduced of about 1.4% suggesting that the observed increase in EMS use had to be attributed to others drivers, as the ageing of the population [ 22 , 23 ] and the increased frailty of the community-dwelling of the older people [ 24 ]. Hypothesis which, in this study, can be further supported by the increased trend of dispatches coming from long term care facilities and the higher prevalence of medical conditions and of non-urgent codes.…”

Section: Discussionmentioning

confidence: 99%

Trends and Characteristics of Emergency Medical Services in Italy: A 5-Years Population-Based Registry Analysis

Campagna¹,

Conti²,

Dimonte³

et al. 2020

Healthcare

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Background: Emergency Medical Services (EMS) plays a fundamental role in providing good quality healthcare services to citizens, as they are the first responders in distressing situations. Few studies have used available EMS data to investigate EMS call characteristics and subsequent responses. Methods: Data were extracted from the emergency registry for the period 2013–2017. This included call and rescue vehicle dispatch information. All relationships in analyses and differences in events proportion between 2013 and 2017 were tested against the Pearson’s Chi-Square with a 99% level of confidence. Results: Among the 2,120,838 emergency calls, operators dispatched at least one rescue vehicle for 1,494,855. There was an estimated overall incidence of 96 emergency calls and 75 rescue vehicles dispatched per 1000 inhabitants per year. Most calls were made by private citizens, during the daytime, and were made from home (63.8%); 31% of rescue vehicle dispatches were advanced emergency medical vehicles. The highest number of rescue vehicle dispatches ended at the emergency department (74.7%). Conclusions: Our data showed that, with some exception due to environmental differences, the highest proportion of incoming emergency calls is not acute or urgent and could be more effectively managed in other settings than in an Emergency Departments (ED). Better management of dispatch can reduce crowding and save hospital emergency departments time, personnel, and health system costs.

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“…The burden on EMSs has increased considerably in many countries [9]. For example, in the last ten years, prehospital EMS demand and emergency response times in Beijing have increased [10], and therefore, more resources and effort should be devoted to PEC. The Danish prehospital EMS care system has received major changes [11], and other national organizations have identified a need to incorporate more evidence-based medicine in PEC [12].…”

Section: Related Workmentioning

confidence: 99%

A Decision Support Method for Prehospital Emergency Care Based on Ranking the Importance of Physiological Variables

Zhang

Zhao

et al. 2020

Healthcare

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To the on-site nursing staff or field management in prehospital emergency care, it seems baffling to conduct more targeted checklist tests for a specific disease. To address this problem, we proposed a decision support method for prehospital emergency care based on ranking the importance of physiological variables. We used multiple logistic regression models to explore the effects of various physiological variables on diseases based on the area under the curve (AUC) value. We implemented the method on the intensive care database (i.e., the Medical Information Mart for Intensive Care (MIMIC-III) database) and explored the importance of 17 physiological variables for 24 diseases, both chronic and acute. We included 33,798 adult patients, using the full physiological dataset as experiment data. We ranked the importance of the physiological variables related to the diseases according to the experiments’ AUC value. We discussed which physiological variables should be considered more important in adult intensive care units (ICUs) for prehospital emergency care conditions. We also discussed the relationships among the diseases based on ranking the importance of physiological variables. We used large-scale ICU patient data to obtain a cohort of physiological variables related to specific diseases. Ranking a cohort of physiological variables is a cost-effective means of reducing morbidity and mortality under prehospital emergency care conditions.

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Trends and characteristics in pre-hospital emergency care in Beijing from 2008 to 2017

Cited by 16 publications

References 19 publications

Urban–sub-urban–rural variation in the supply and demand of emergency medical services

Urban–sub-urban–rural variation in the supply and demand of emergency medical services

Trends and Characteristics of Emergency Medical Services in Italy: A 5-Years Population-Based Registry Analysis

A Decision Support Method for Prehospital Emergency Care Based on Ranking the Importance of Physiological Variables

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