Ambulance Locations in a Tiered Emergency Medical System in a City

This paper deals with optimizing the location of ambulance stations in a two-tiered emergency medical system in an urban environment. Several variants of station distribution are calculated by different mathematical programming models and are evaluated by a detailed computer simulation model. A new modification of the modular capacitated location model is proposed. Two ways of demand modelling are applied; namely, the aggregation of the ambient population and the aggregation of permanent residents at the street level. A case study of the city of Prešov, Slovakia is used to assess the models. The performance of the current and proposed sets of locations is evaluated using real historical data on ambulance trips. Computer simulation demonstrates that the modular capacitated location model, with the ambient population demand, significantly reduces the average response time to high-priority patients (by 79 s in the city and 62 s in the district) and increases the percentage of high-priority calls responded to within 8 min (by almost 4% in the city and 5% in the district). Our findings show that a significant improvement in the availability of the service can be achieved when ambulances are not accumulated at a few stations but rather spread over the city territory.

PREHOSPITAL EMERGENCY MEDICAL SERVICES UTILIZATION FOR CRITICAL PATIENTS AND ITS DETERMINANTS IN THAILAND

This research aimed to determine the situations and factors associated with prehospital emergency medical services (EMS) utilization for critical patients in Thailand. This cross-sectional study used the data of a survey conducted by the Information Technology for Emergency Medical System (ITEMS) of the National Institute of Emergency Medicine, Thailand. The survey collected the data among 1,145 participants using a structured questionnaire. The generalized linear mixed model (GLMM) was used to identify the factors associated with prehospital EMS utilization among critical patients when controlling the effects of covariates presenting adjusted OR and 95% confidence interval. Among 1,145 critical patients, 33.71 % reported using the prehospital EMS of the emergency medical system. Factors that were associated with prehospital EMS use had a high level of knowledge on prehospital EMS (adj. OR = 6.49; 95%CI: 3.78-11.12), high level of trust in quality and safety of prehospital EMS (adj. OR = 4.72; 95%CI: 3.50-6.36), low-moderate severity of perceived illness (adj. OR= 3.71; 95%CI: 2.54-5.42), critical condition occurred at workplace/building (adj. OR=3.57; 95%CI: 2.33-5.47), at home/residential building (adj. OR = 2.21; 95%CI: 1.37-3.58), had adequate services in the area (adj. OR= 1.94; 95%CI: 1.45-2.60), finished at least secondary school (adj. OR= 1.62; 95%CI: 1.11-2.37), less than 15km distance between scene and EMS service site (adj. OR= 1.47; 95%CI: 1.10-1.98), and were very satisfied with services (adj. OR = 1.15; 95%CI: 1.08-1.22) from the reasons mentioned.

Commencing one-handed chest compressions while activating emergency medical system using a handheld mobile device in lone-rescuer basic life support: a randomised cross-over simulation study

IntroductionIn conventional basic life support (c-BLS), a lone rescuer is recommended to start chest compressions (CCs) after activating the emergency medical system. To initiate earlier CCs in lone-rescuer BLS, we designed a modified BLS (m-BLS) sequence in which the lone rescuer commences one-handed CCs while calling for help using a handheld cellular phone with the other free hand. This study aimed to compare the quality of BLS between c-BLS and m-BLS.MethodsThis was a simulation study performed with a randomised cross-over controlled trial design. A total of 108 university students were finally enrolled. After training for both c-BLS and m-BLS, participants performed a 3-minute c-BLS or m-BLS on a manikin with a SkillReporter at random cross-over order. The paired mean difference with SE between c-BLS and m-BLS was assessed using paired t-test.ResultsThe m-BLS had reduced lag time before the initiation of CCs (with a mean estimated paired difference (SE) of −35.0 (90.4) s) (p<0.001). For CC, a significant increase in compression fraction and a higher number of CCs with correct depth were observed in m-BLS (with a mean estimated paired difference (SE) of 16.2% (0.6) and 26.9% (3.3), respectively) (all p<0.001). However, no significant paired difference was observed in the hand position, compression rate and interruption time. For ventilation, the mean tidal volumes did not differ. However, the number of breaths with correct tidal volume was higher in m-BLS than in c-BLS.ConclusionIn simulated lone-rescuer BLS, the m-BLS could deliver significantly earlier CCs than the c-BLS while maintaining high-quality cardiopulmonary resuscitation.

COVID-19 Infection Epidemic in the South Pacific Island of New Caledonia and in the Greater Paris: Where Is the Highest Wave?

Introduction New-Caledonia, an island located in the South-Pacific, was the first (overseas) French country hit by the coronavirus disease-2019 (COVID-19) pandemic to come out of lockdown. The epidemic was rapidly controlled. Analyzing the impact of an epidemic only makes sense if it is compared with a zone with a similar health care system. Objective To compare epidemic evolution in New-Caledonia and Paris suburb. Methods Health care organization is similar in New-Caledonia and Seine-Saint-Denis, based on an Emergency Medical System call center. We recorded the numbers of patients managed by SAMU (Service d’Aide Médicale Urgente)-Emergency Medical System, transferred to the emergency department and managed in prehospital setting by mobile intensive care unit. We compared these parameters during the reference (February 1-23, 2020) and the COVID-19 (February 24, 2020, to April 19, 2020) periods. Primary end-point: number of days over the 95th percentile of the reference period. Results Number of patients managed was over the 95th percentile during 27 and 47 days in New-Caledonia and Seine-Saint-Denis, respectively. Number of emergency department transfers was more than the 95th percentile during 4 and 31 days, respectively. Number of mobile intensive care unit sent was over the 95th percentile during 3 and 14 days, respectively. Peaks were similar. Conclusion The duration of the critical period rather than its spread affected the health care system.