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.

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.

Abstract TP256: Ems Run Times by Weekday vs. Weekend 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 ◽  
Response Times ◽  
San Diego County ◽  
Hospital Treatment ◽  
Transport Time ◽  
Hospital Arrival ◽  
Stroke Registry ◽  
Clinically Significant ◽  
Initial Responder

Background: Emergency Medical Services (EMS) is important as the initial responder, very little data examines EMS response and transport to hospital diagnosis. Understanding differences between weekday and weekend is informative for resource and staff planning. Using a countywide registry, we evaluated differences in EMS response times on weekdays and weekends and in-hospital treatment. Methods: We included EMS San Diego County Stroke Registry cases with a computer automated dispatch (CAD) and base hospital record (BHR) from July 2017 through December 2018; linked on EMS incident number. We analyzed EMS response, scene and transport time by weekday and weekend for all cases and cases with last known normal (LKN) to EMS enroute time < 6 hours. Hospital arrival to tPA and to embolectomy therapy (EVT) time was analyzed for this subgroup. Weekend was defined as Friday 1800 through Monday 0600. Results: Of 2,376 cases, 726 (30.6%) arrived during weekends. Weekend mean (±SD) response time was 6.7 (±3.4) minutes (min); 7.1 min (±3.9) on weekdays. Mean weekend scene time was 12.8 (±5.1) min, 13.2 (±5.3) min on weekdays (p=.18). Transport time was 13.2 (±7.6) min on weekends, 14.1 (±7.8) min on weekdays (p=.01). There were 1,190 cases with LKN to EMS enroute time < 6 hours, 379 arrived on weekends (31.8%). Mean (±SD) response time was 6.6 (±3.4) min on weekends, 7.2 (±3.9) min on weekdays; weekend scene time 12.1 (±4.5) min, weekday scene time 12.2 (±4.9); weekend transport time 12.2 (±6.6) min, weekday transport time 12.7 (±7.4) min. Of this group, 378 received tPA, 126 (33.3%) on the weekend. Mean (±SD) weekend arrival to tPA was 53.6 (±22.2) min; 56.0 (±32.1) min on weekdays (p=.39). 100 cases received EVT, 39 on a weekend. Mean (±SD) weekend arrival to EVT was 2.1 (±0.6) hours; weekdays 1.9 (±0.8) hours (p=.13). Conclusion: One in three patients arrived at the hospital on weekends. EMS response time and scene time did not differ, while transport time on the weekend was shorter, although this may not be clinically significant. This may be attributed to traffic volume and patterns during these times. However, among patients with shorter LKN time and patients receiving tPA no difference in EMS times was seen. Overall acute stroke transfer times did not differ across weekends and weekdays.

Impact of the San Diego County Firestorm on Emergency Medical Services

2006 ◽  
Vol 21 (5) ◽  
pp. 353-358 ◽  
Author(s):  
Gary M. Vilke ◽  
Alan M. Smith ◽  
Barbara M. Stepanski ◽  
Leslie Upledger Ray ◽  
Patricia A. Murrin ◽  
...  
Keyword(s):  
Emergency Medical Services ◽  
San Diego ◽  
Life Support ◽  
Advanced Life Support ◽  
San Diego County ◽  
Medical Services ◽  
Eye Injuries ◽  
Emergency Medical ◽  
The Impact ◽  
Respiratory Complaints

AbstractBackground:In October 2003, San Diego County, California, USA, experienced the worst firestormin recent history. During the firestorm, public health leaders implemented multiple initiatives to reduce its impact on community health using health updates and news briefings. This study assessed the impact of patients with fire-related complaints on the emergency medical services (EMS) system during and after the firestorm.Methods:A retrospective review of a prehospital database was performed for all patients who were evaluated by advanced life support (ALS) ambulance personnel after calling the 9-1-1 emergency phone system for direct, fire related complaints from 19 October 2003 through 30 November 2003 in San Diego County. The study location has an urban, suburban, rural, and remote resident population of approximately three million and covers 4,300 square miles (2,050 km2). The prehospital patient database was searched for all patients with a complaint that was related directly to the fires. Charts were abstracted for data, including demographics, medical issues, treatments, and disposition status.Results:During the firestorm, fire consumed >380,000 acres (>938,980 hectares), including 2,454 residences and 785 outbuildings, and resulted in a total of 16 fatalities. Advanced life support providers evaluated 138 patients for fire related complaints. The majority of calls were for acute respiratory complaints. Other complaints included burns, trauma associated with evacuation or firefighting, eye injuries, and dehydration. A total of 78% of the injuries were mild. Twenty percent of the victims were firefighters, most with respiratory complaints, eye injuries, or injuries related to trauma. A total of 76% of the patients were transported to the hospital, while 10% signed out against medical advice.Conclusion:Although the firestorm had the potential to significantly impact EMS, pre-emptive actions resulted in minimal impact to emergency departments and the prehospital system. However, during the event, therewere a number of lessons learned that can be used in future events.

Abstract WP252: The Effect and Associated Factors of Dispatcher Recognition of Stroke: A Multicenter Observational Cohort Study

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Ming-Ju Hsieh ◽  
Jen-Tang Sun ◽  
Wen-Chu Chiang ◽  
Kuo-Liong Chien ◽  
Matthew Huei-Ming Ma
Keyword(s):  
Life Support ◽  
Prehospital Care ◽  
Advanced Life Support ◽  
Patient Characteristics ◽  
Stroke Care ◽  
Tape Recording ◽  
Stroke Patients ◽  
Factors Associated ◽  
Prehospital Management ◽  
Observational Cohort

Introduction: Stroke patients recognized by dispatchers have an increased chance of receiving prehospital care with advanced life support and arrive at hospital earlier. There is limited research on factors associated with dispatcher recognition of stroke. This study aimed to: (1) understand the details of the dispatcher-caller communication among the calls for stroke patients, (2) identify factors associated with stroke recognition by dispatchers, and (3) evaluate the association between stroke recognition by dispatchers and stroke management. Methods: We conducted a multicenter retrospective study involving patients with stroke or transient ischemic stroke transported by the emergency medical service, and arriving at 9 hospitals in Taipei within 3 hours of symptom onset from January 1, 2013 to February 28, 2014. Patients were excluded if tape-recording data or prehospital management information were not available. Data of the enrolled patients were reviewed, including the tape recording of the dispatcher-caller communication, the type of dispatch determination, and patient characteristics. We used stroke dispatch determination as the surrogate for stroke recognition by dispatchers. Multivariable logistic regression was used to identify the factors associated with stroke dispatch determination. Results: A total of 507 patients were included. In approximately 50% of cases, callers were close family members. Ninety-one patients (17.9%) had stroke dispatch determination. After adjustment, stroke reported spontaneously, any one symptom included in the Cincinnati Prehospital Stroke Scale reported spontaneously, and dispatcher adherence to the protocol, were associated with stroke dispatch determination independently. Stroke dispatch determination was associated with receiving pre-arrival notification, shorter door-to-computed tomography time, and thrombolytic therapy. Conclusions: The sensitivity of recognizing stroke patients by dispatchers is suboptimal. Dispatchers should spend more time identifying stroke patients from those with frequently reported problems, by following the dispatch protocol. Recognition of stroke by dispatchers was associated with improved stroke care.

Pediatric Prehospital Care in Urban and Rural Areas

PEDIATRICS ◽  
1991 ◽  
Vol 88 (4) ◽  
pp. 681-690 ◽  
Author(s):  
James S. Seidel ◽  
Deborah Parkman Henderson ◽  
Patrick Ward ◽  
Barbara Wray Wayland ◽  
Beverly Ness
Keyword(s):  
Emergency Medical Services ◽  
Rural Areas ◽  
Urban Areas ◽  
Pediatric Patients ◽  
Life Support ◽  
Prehospital Care ◽  
Advanced Life Support ◽  
Medical Services ◽  
Care Providers ◽  
Emergency Medical

There are limited data concerning pediatric prehospital care, although pediatric prehospital calls constitute 10% of emergency medical services activity. Data from 10 493 prehospital care reports in 11 counties of California (four emergency medical services systems in rural and urban areas) were collected and analyzed. Comparison of urban and rural data found few significant differences in parameters analyzed. Use of the emergency medical services system by pediatric patients increased with age, but 12.5% of all calls were for children younger than 2 years. Calls for medical problems were most common for patients younger than 5 years of age; trauma was a more common complaint in rural areas (64%, P = .0001). Frequency of vital sign assessment differed by region, as did hospital contact (P &lt; .0001). Complete assessment of young pediatric patients, with a full set of vital signs and neurologic assessment, was rarely performed. Advanced life support providers were often on the scene, but advanced life support treatments and procedures were infrequently used. This study suggests the need for additional data on which to base emergency medical services system design and some directions for education of prehospital care providers.

scholarly journals A Workplace-Based Observation Strategy to Assess Prehospital Care Delivery by Public Ambulances in Ukraine

2019 ◽  
Vol 34 (s1) ◽  
pp. s179-s180
Author(s):  
Stanislav Gaievskyi ◽  
Oleksandr Linchevskyy ◽  
Colin Meghoo
Keyword(s):  
Life Support ◽  
Care Delivery ◽  
Prehospital Care ◽  
Advanced Life Support ◽  
Cost Effective ◽  
Financial Resources ◽  
Successful Implementation ◽  
Patient Privacy ◽  
Patient Encounter ◽  
Treatment Protocols

Introduction:Current methods to evaluate the delivery of urgent prehospital care often rely on inadequate surrogate measures or unreliable self-reported data. A workplace-based strategy may be feasible to assess the delivery of prehospital care by ambulances in selected populations.Aim:To perform a nationwide assessment of the psychomotor performance of public ambulance workers in Ukraine, we created a plan of workplace-based observation. We conducted a post-hoc analysis of this strategy to assess feasibility, strengths, and limitations for future use in assessing prehospital ambulance performance.Methods:With support from the Ministry of Health, we sent teams of trained observers to 30 ambulance substations across Ukraine. Using data collection tools on mobile devices, these observers accompanied Advanced Life Support ambulances on urgent calls for periods of 72 hours. We evaluated this program for collecting patient encounter data against the investment of time, personnel, and financial resources.Results:Over a two-month period, we directly observed 524 patient encounters by public ambulances responding to urgent calls at 30 ambulance substations across Ukraine. We employed 6 observers and 2 administrators over this time period. Collecting our observations required 2,160 person-hours at the ambulance substations. The total distance traveled to these sites was 11,375 kilometers. Project costs amounted to 37,000 USD, equating to 71 USD per observed patient encounter.Discussion:Workplace-based assessments are a cost-effective strategy to collect data on the delivery of prehospital care in select populations. This data can be useful for identifying the current state of EMS care delivered and evaluating compliance with established treatment protocols. Successful implementation depends on effective planning and coordination with a commitment of time, personnel, and financial resources. Issues of patient privacy, legal permission, and observer training must be considered.

scholarly journals The influence of advanced life support response time on patient outcomes after out-of-hospital cardiac arrest in Taipei

Resuscitation ◽  
2019 ◽  
Vol 142 ◽  
pp. e101
Author(s):  
Ying-Chih Ko ◽  
Jen-Tang Sun ◽  
Wen-Chu Chiang ◽  
Yu-Chun Chien ◽  
Yao-Cheng Wang ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Response Time ◽  
Patient Outcomes ◽  
Life Support ◽  
Advanced Life Support ◽  
Hospital Cardiac Arrest

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.

Prehospital Care and In-hospital Mortality of Trauma Patients in Iran

2014 ◽  
Vol 29 (5) ◽  
pp. 473-477 ◽  
Author(s):  
Mohammad Paravar ◽  
Mehrdad Hosseinpour ◽  
Mahdi Mohammadzadeh ◽  
Azade Sadat Mirzadeh
Keyword(s):  
Hospital Mortality ◽  
Trauma Center ◽  
Injury Severity ◽  
Life Support ◽  
Prehospital Care ◽  
Advanced Trauma Life Support ◽  
Trauma Patients ◽  
Publication Type ◽  
Transport Time ◽  
Severe Injuries

AbstractIntroductionThe aim of this study was to determine the effect of prehospital time and advanced trauma life support interventions for trauma patients transported to an Iranian Trauma Center.MethodsThis study was a retrospective study of trauma victims presenting to a trauma center in central Iran by Emergency Medical Services (EMS) and hospitalized more than 24 hours. Demographic and injury characteristics were obtained, including accident location, damaged organs, injury mechanism, injury severity score, prehospital times (response, scene, and transport), interventions and in-hospital outcome.ResultsTwo thousand patients were studied with an average age of 36.3 (SD = 20.8) years; 83.1% were male. One hundred twenty patients (6.1%) died during hospitalization. The mean response time, at scene time and transport time were 6.6 (SD = 3), 11.1 (SD = 5.2) and 12.8 (SD = 9.4), respectively. There was a significant association of longer transport time to worse outcome (P = .02). There was a trend for patients with transport times >10 minutes to die (OR: 0.8; 95% CI, 0.1-6.59). Advanced Life Support (ALS) interventions were applied for patients with severe injuries (Revised Trauma Score ⩽7) and ALS intervention was associated with more time on scene. There was a positive association of survival with ALS interventions applied in suburban areas (P = .001).ConclusionIn-hospital trauma mortality was more common for patients with severe injuries and long prehospital transport times. While more severely injured patients received ALS interventions and died, these interventions were associated with positive survival trends when conducted in suburban and out-of-city road locations with long transport times.HosseinpourM, ParavarM, MohammadzadehM, MirzadehAS. Prehospital care and in-hospital mortality of trauma patients in Iran. Prehosp Disaster Med. 2014;29(5):1-5.

Abstract P651: Should I Stay or Go: Seeking Stroke Care During Covid-19

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Kathyrn J Libby ◽  
Linda Couts ◽  
Paige Schoenheit-Scott ◽  
Lindsay L Olson-Mack ◽  
Amelia Kenner Brininger ◽  
...  
Keyword(s):  
San Diego ◽  
Arrival Time ◽  
Stroke Care ◽  
Time Frame ◽  
San Diego County ◽  
Stroke Patients ◽  
Discharge Data ◽  
Hospital Arrival ◽  
The Impact ◽  
At Home

Introduction: On March 16, 2020 San Diego County implemented a stay at home order in response to COVID-19 pandemic; followed by the state of California instituting a shelter in place order. Locally, San Diego County’s stroke receiving centers (SRC) determined a 30% drop in stroke code activations between March-April 2020 compared to the same time in 2019 indicating a possible delay in seeking care. Utilizing discharge data, we sought to understand the impact of the stay at home order on the timeliness of seeking care. Hypothesis: We hypothesized an increase in last known normal (LKN) to hospital arrival time and a decrease in alteplase (tPA) and endovascular therapy (EVT) treatment rates between March 16-June 30 2020 compared to March 16-June 30 2019. Methods: AIS patients presenting to one of 16 SRC in San Diego County between March 16-June 30 in 2019 and 2020, discharged from the hospital or treated in the ED and transferred to another facility were included. Patients arriving as transfers from another facility were excluded. Results: In 2019, of 1,342 AIS cases LKN time was recorded for 85.6% of cases; of 1,092 cases in 2020 86.4% of cases had a LKN. Average LKN to arrival was 20.5 hours in 2019 and 32.4 hours in 2020 (p = .001, 95% CI [4.79, 18.93]). In 2019, 209 (15.6%) received tPA and 91 (6.8%) had EVT. In 2020, 144 (13.2%) received tPA and 75 (6.9%) had EVT. Odds that a case in 2019 received tPA was 1.21 times that of cases in 2020 (p=.09). Odds that a case in 2019 had EVT was .99 times that of cases in 2020 (p=.93). Conclusion: Ischemic stroke patients arriving between March 16-June 30, 2020 had a longer LKN to arrival time compared to the same time frame in 2019. The longer time to arrival may have been due to patients waiting longer to seek care, as anecdotal information from patients eluded to. The odds of receiving tPA or EVT treatment in 2020 compared to 2019 were not statistically significant. This may be due to patients experiencing acute symptoms accessing healthcare at the same rate in 2020 as 2019. Analysis of percent of patients arriving within 4 hours of LKN and average NIHSS are important next steps to determine this. Regardless, during a time of community crisis, it is important to broadcast community messaging focusing on the importance of seeking emergency care for stroke-like symptoms.

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