Utilization of Warning Lights and Siren Based on Hospital Time-Critical Interventions

2010 ◽  
Vol 25 (4) ◽  
pp. 335-339 ◽  
Author(s):  
Andreia Marques-Baptista ◽  
Pamela Ohman-Strickland ◽  
Kimberly T. Baldino ◽  
Michael Prasto ◽  
Mark A. Merlin
Keyword(s):  
Life Support ◽  
Advanced Life Support ◽  
Time Of Day ◽  
Average Difference ◽  
Transport Time ◽  
Day Of The Week ◽  
Medical Transport ◽  
Critical Patients ◽  
Time Critical ◽  
Warning Lights

AbstractObjective:The objective of this study was to evaluate the time saved by usage of lights and siren (L&S) during emergency medical transport and measure the total number of time-critical hospital interventions gained by this time difference.Methods:A retrospective study was performed of all advanced life support (ALS) transports using lights and siren to this university emergency department during a three-week period. Consecutive times were measured for 112 transports and compared with measured transport times for a personal vehicle traveling the same day of the week and time of day without lights and siren. The time-critical hospital interventions are defined as procedures or treatments that could not be performed in the prehospital setting requiring a physician. The project assessed whether the patients received the hospital interventions within the average time saved using lights and siren transport.Results:The average difference in time with versus without L&S was -2.62 minutes (95% CI: -2.60− -2.63, paired t-test p <0.0001). The average transport time with L&S was 14.5 ±7.9 minutes (min) (1 standard deviation/minute (min), range = 1–36 min.). The average transport time without L&S was 17.1 ±8.3 min (range = 1−40 min). Of the 112 charts evaluated, five patients (4.5%) received time-critical hospital interventions. No patients received time-critical interventions within the time saved by utilizing lights and siren. Longer distances did not result in time saved with lights and siren.Conclusions:Limiting lights and siren use to the patients requiring hospital interventions will decrease the risks of injury and death, while adding the benefit of time saved in these critical patients.

Abstract TP245: Variance in Ems Run Times by Receiving Hospital for Stroke Patients in San Diego County

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Amelia Kenner-brininger ◽  
Lindsay Olson-Mack ◽  
Lorraine Calzone ◽  
Kristi L Koenig ◽  
Thomas M Hemmen
Keyword(s):  
Response Time ◽  
San Diego ◽  
Life Support ◽  
Prehospital Care ◽  
Advanced Life Support ◽  
San Diego County ◽  
Stroke Patients ◽  
Transport Time ◽  
Stroke Registry ◽  
Few Data

Background: Emergency Medical Services (EMS) play an important role as initial providers after stroke. Few data are available that capture Stroke Receiving System and EMS response and transport data. We used a stroke registry from a community of 3.3 million residents, 18 stroke receiving centers, and 19 ground transporting advanced life support EMS agencies to evaluate EMS response time, scene time, and transport times. Our aim was to inform the stroke community about duration of EMS care and guide future prehospital interventions. Methods: We included all cases from the San Diego County Stroke Registry arriving by EMS with associated computer automated dispatch (CAD) record and base hospital record (BHR) from July 2017 through December 2018. Records were linked on the EMS incident number, reviewed for accuracy. We analyzed EMS response, scene, transport and total run times (enroute to arrival) by receiving hospital. Results: Between July 2017 and December 2018 2,376 EMS patients were transported to 18 hospitals. Volume per hospital ranged from 11 to 483 patients over the study period. Mean (±SD) response time was 7.0 (±3.7) minutes, range: 5.3 to 9.3 minutes between hospitals. Mean (±SD) scene time was 13.1 (±5.2) minutes, range: 10.5 to 15.0 minutes between hospitals. Transport time averaged 13.8 (±7.7) minutes, range: 8.3 to 23.8 minutes between hospitals (IQR=8.5-17.9). The mean (±SD) total EMS run time was 33.8 (±10.8) minutes, range: 26.4 to 44.9 minutes between hospitals (IQR=26.4-39.9). Conclusion: Only minor variations in EMS response and scene times were observed across the Stroke Receiving Centers. However, transport time showed greater variation and contributed to the differences in total EMS run times. Many systems had short transport times, limiting prehospital interventions. Next steps include studying factors contributing to transport time variation to inform prehospital care and triage decisions of possible stroke patients to optimize transport times.

Racial disparities in emergency care for seizures in the United States

2021 ◽  
Vol 13 (9) ◽  
pp. 373-377
Author(s):  
Sriman Gaddam
Keyword(s):  
Relative Risk ◽  
Racial Disparities ◽  
Life Support ◽  
Statistical Significance ◽  
Advanced Life Support ◽  
The United States ◽  
Chi Square ◽  
Time Critical ◽  
To Receive ◽  
White Patients

Background: Racial disparities exist regarding emergency medical services, and advanced life support (ALS) is superior to basic life support (BLS) for patients experiencing a seizure. Aims: This study aims to identify if there are racial disparities regarding access to ALS care for patients having a seizure. Methods: This study analysed 624 011 seizure cases regarding the provision of BLS rather than ALS care per racial group. Chi-square testing was used to check statistical significance and effect size was measured using relative risk. Findings: On average, non-white patients experiencing a seizure had a 21% higher relative risk of receiving BLS care than white patients. The highest disparity concerned American Indian patients, who had a 66% higher relative risk of receiving BLS care than white patients. Conclusions: Overall, non-white patients are less likely to receive ALS when experiencing a seizure than white patients, potentially leading to worse prehospital outcomes from less access to time-critical medications.

Abstract WP295: Factors Influencing Ems Transport Time for Patients After Stroke in San Diego County

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Amelia Kenner-Brininger ◽  
Lindsay Olson-Mack ◽  
Lorraine Calzone ◽  
Kristi L Koenig ◽  
Thomas L Hemmen
Keyword(s):  
San Diego ◽  
Life Support ◽  
Advanced Life Support ◽  
San Diego County ◽  
Stroke Patients ◽  
Transport Time ◽  
Policy Makers ◽  
Stroke Diagnosis ◽  
Stroke Center ◽  
To Receive

Background: Emergency Medical Services (EMS) play an important role as initial providers to stroke patients. Data of on scene and transport times for stroke patients with unbiased populations are rare. We explored the range of times for stroke patients to receive care on scene and transport to a stroke receiving center (SRC) in a region with 3.3 million residents, 18 SRCs and 19 ground transport advanced life support EMS agencies. This will inform researchers on prehospital stroke invervention and policy makers deliberating triage and stroke center designation. Methods: We included all patients with final hospital diagnosis of AIS, ICH, SAH, or TIA transported by EMS to a San Diego County SRC between July 2017 and December 2018 with computer automated dispatch record and base hospital record. Records were linked on EMS incident number, reviewed for accuracy. We analyzed scene and transport time, weekday vs. weekend, last known normal (LKN) to EMS enroute < 6 hours (approximation of LKN to 911 call), EMS recognition of stroke, and final hospital diagnosis. Results: In total, 2,376 patients with final stroke diagnosis were transported between July 2017 and December 2018. In 1,514 (63.7%) cases, EMS recognized stroke. In these cases mean (±SD) scene time was 12.0 (±4.6) minutes and transport time 12.4 (±7.2). In stroke patients without EMS stroke recognition the mean (±SD) scene time was 14.8 (±5.7) (p=.0001) and transport time of 16.2 (±8.1) (p=.0001). Scene time (p=.002), EMS stroke recognition (p=.00001), weekend vs. weekday (p=.013), LKN to enroute < 6 hours (p=.00001) were all correlated with shorter transport time; hospital stroke diagnosis (p=.56) was not. Linear regression indicated LKN to enroute < 6 hours (p=.001) and EMS stroke recognition (p=.00001) were significant in determining shorter transport time. Conclusion: EMS transport time of stroke patients varies across our system. However, when EMS providers recognize a stroke patient, scene time decreases by nearly 3 minutes and transport time decreases by nearly 4 minutes compared with patients with stroke undetected until after hospital arrival. Additionally, patients with a shorter LKN to EMS enroute time have a shorter transport time, which may be clinically important for this time-sensitive condition.

Racial disparities in emergency care for seizures in the United States

2021 ◽  
Vol 11 (3) ◽  
pp. 62-66
Author(s):  
Sriman Gaddam
Keyword(s):  
Relative Risk ◽  
Racial Disparities ◽  
Life Support ◽  
Statistical Significance ◽  
Advanced Life Support ◽  
The United States ◽  
Chi Square ◽  
Time Critical ◽  
To Receive ◽  
White Patients

Background Racial disparities exist regarding emergency medical services, and advanced life support (ALS) is superior to basic life support (BLS) for patients experiencing a seizure. Aims This study aims to identify if there are racial disparities regarding access to ALS care for patients having a seizure. Methods This study analysed 624 011 seizure cases regarding the provision of BLS rather than ALS care per racial group. Chi-square testing was used to check statistical significance and effect size was measured using relative risk. Findings On average, non-white patients experiencing a seizure had a 21% higher relative risk of receiving BLS care than white patients. The highest disparity concerned American Indian patients, who had a 66% higher relative risk of receiving BLS care than white patients. Conclusions Overall, non-white patients are less likely to receive ALS when experiencing a seizure than white patients, potentially leading to worse prehospital outcomes from less access to time-critical medications.

scholarly journals Maximizing resource efficiency in rural prehospital emergency medical services through call frequency analysis

2013 ◽  
Vol 5 (2) ◽  
pp. 297-301
Author(s):  
Andrew Flynn
Keyword(s):  
Emergency Medical Services ◽  
Traffic Accident ◽  
Life Support ◽  
Advanced Life Support ◽  
Time Of Day ◽  
Medical Services ◽  
Red Cross ◽  
Emergency Medical ◽  
Accident Data ◽  
Prehospital Emergency

Rural prehospital emergency medical services are often lacking when compared with their urban counterparts in terms of resources and coordinated resource use: can only employ important resources, such as paramedics, during limited shifts. This project demonstrates a method for determining the most effective use of these limited resources in a rural Red Cross ambulance service in Guápiles, Costa Rica. In this community, paramedic services are only available six days a week for twelve hours. Emergency call frequency was mapped using 20 months of traffic accident data and after establishing that traffic accident frequency was statistically dependent on the time of day, polynomial models of the data were generated. The model functions were integrated and the results were tested for accuracy. Integrals were calculated, and the results were reported to the Guápiles Red Cross committee to achieve an improved service. Methods such as this can be applied to any emergency response service.KEY WORDSWorld Health Organization (WHO), Prehospital Emergency Medical Service(s) (PEMS), Traffic Accident (TA), Téchnico de Emergencias Medicas (Paramedic), Advanced Life Support (ALS)

Recommended Guidelines for Uniform Reporting of Pediatric Advanced Life Support: The Pediatric Utstein Style

Circulation ◽  
1995 ◽  
Vol 92 (7) ◽  
pp. 2006-2020 ◽  
Author(s):  
Arno Zaritsky ◽  
Vinay Nadkarni ◽  
Mary Fran Hazinski ◽  
George Foltin ◽  
Linda Quan ◽  
...  
Keyword(s):  
Life Support ◽  
Advanced Life Support ◽  
Recommended Guidelines ◽  
Utstein Style

Code Blue Events in the Neonatal and Pediatric Intensive Care Units at a Tertiary Care Children's Hospital

2020 ◽  
Author(s):  
Catherine M. Groden ◽  
Erwin T. Cabacungan ◽  
Ruby Gupta
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Life Support ◽  
Univariate Analysis ◽  
Tertiary Care ◽  
Neonatal Resuscitation ◽  
Advanced Life Support ◽  
Pediatric Intensive Care ◽  
Code Blue ◽  
Neonatal Resuscitation Program

Objective The authors aim to compare all code blue events, regardless of the need for chest compressions, in the neonatal intensive care unit (NICU) versus the pediatric intensive care unit (PICU). We hypothesize that code events in the two units differ, reflecting different disease processes. Study Design This is a retrospective analysis of 107 code events using the code narrator, which is an electronic medical record of real-time code documentation, from April 2018 to March 2019. Events were divided into two groups, NICU and PICU. Neonatal resuscitation program algorithm was used for NICU events and a pediatric advanced life-support algorithm was used for PICU events. Events and outcomes were compared using univariate analysis. The Mann–Whitney test and linear regressions were done to compare the total code duration, time from the start of code to airway insertion, and time from airway insertion to end of code event. Results In the PICU, there were almost four times more code blue events per month and more likely to involve patients with seizures and no chronic condition. NICU events more often involved ventilated patients and those under 2 months of age. The median code duration for NICU events was 2.5 times shorter than for PICU events (11.5 vs. 29 minutes), even when adjusted for patient characteristics. Survival to discharge was not different in the two groups. Conclusion Our study suggests that NICU code events as compared with PICU code events are more likely to be driven by airway problems, involve patients <2 months of age, and resolve quickly once airway is taken care of. This supports the use of a ventilation-focused neonatal resuscitation program for patients in the NICU. Key Points

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