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 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.

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.

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 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.

Abstract W P189: Characteristics of Rural Pre-Hospital Stroke Transports

Stroke ◽  
2014 ◽  
Vol 45 (suppl_1) ◽  
Author(s):  
Charles Whiteman ◽  
Debra Paulson ◽  
Rosanna Sikora ◽  
Russell Doerr ◽  
Stephen Davis ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Life Support ◽  
The United States ◽  
Rural Setting ◽  
Care Hospital ◽  
Stroke Patients ◽  
Critical Access Hospital ◽  
Suspected Stroke ◽  
Stroke Center ◽  
The Impact

Introduction: West Virginia (WV) is the second most rural state and has a stroke prevalence of 3%. According to the United States Census Bureau, 97.3% of the land is considered rural and 51.3% of the population lives in a rural area. EMS transport times in Northern WV often exceed 20 minutes in rural counties. Little data has been published about EMS response to acute stroke patients in the rural setting. Methods: This was a retrospective cohort study of EMS response and interventions for patients with chief complaint of stroke in the MedCom database providing medical command for 26 northern WV counties. Stroke encounters from January 1, 2002 to December 31, 2011 were analyzed for EMS provider capability, receiving hospital capability, and pre-hospital interventions. Results: There were 7,594 transports available for analysis. Basic Life Support (BLS) responders provided 7.0% of the care. The majority of the patients, 51.6%, were transported to an acute care hospital, 11.6% to a critical access hospital, and 36.9% to a designated stroke center. Blood glucose was determined by glucometer in 66.4% of patients with 2.0% treated for hypoglycemia. Vascular access was attempted in 92.6% of the patients and was successful in 81.5%. Cardiac monitor was applied in 92.4% of the patients and oxygen saturation was determined by pulse oximetry in 95.8%. Oxygen therapy was administered to 96.5% of the patients. Discussion: In rural northern WV, 7% of the suspected stroke patients had care by only a BLS responder. Although evaluation at a designated stroke center has been shown to increase the chance for receiving acute thrombolytic intervention, less than 40% of patients in northern WV were initially seen at a designated stroke center and 11.6% were initially seen at a critical access hospital. Consequently, even critical access hospitals need to be prepared to rapidly evaluate and treat patients with suspected ischemic stroke. Blood glucose was not checked by EMS personnel in more than 30% of all transports. Additional studies are needed to assess the impact of these pre-hospital procedures and transport destination decisions on suspected stroke patient outcomes in the rural setting.

Abstract TP248: Reduced Door-in-Door-Out Time Increases the Likelihood of Endovascular Thrombectomy for Large Vessel Occlusion Patients

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Kavit Shah ◽  
Shashvat Desai ◽  
Benjamin Morrow ◽  
Pratit Patel ◽  
Habibullah Ziayee ◽  
...  
Keyword(s):  
Internal Carotid ◽  
Large Vessel ◽  
Large Vessel Occlusion ◽  
Stroke Patients ◽  
Vessel Occlusion ◽  
Endovascular Thrombectomy ◽  
Comprehensive Stroke Center ◽  
Stroke Center ◽  
To Receive ◽  
Rapid Transfer

Introduction: Endovascular thrombectomy (EVT) is recommended for patients with large vessel occlusion (LVO) presenting within 24 hours of last seen well (LSW). Unfortunately, patients transferred from spoke hospitals to receive EVT have poorer outcomes compared to those presenting directly to the hub, underscoring the importance of rapid transfer timing - door-in-door-out (DIDO). Methods: Data were analyzed from consecutive acute ischemic stroke patients with proximal large vessel occlusions (LVO) transferred to our comprehensive stroke center for EVT. The following variable were studied: DIDO, baseline NIHSS/mRS, presentation CT ASPECTs, site of LVO, treatment, and clinical outcome. Results: Ninety patients with internal carotid or middle cerebral artery (M1) occlusion at the spoke hospital were included in the study. At the hub hospital, 75% (68) underwent emergent cerebral angiography (DSA) with intent to perform EVT. Reasons for not undergoing angiography at hub hospital included large stroke burden (59%) and improvement in NIHSS score (41%). Overall, DIDO time was 184 (130-285) minutes. Mean DIDO time was significantly lower for patients who underwent DSA at hub hospital compared to patients who did not (207 versus 272 minutes, p=0.031). 92% (12) of patients with DIDO <=120 minutes (n=13) underwent EVT compared to 73% (56) of patients with DIDO >120 minutes (n=77). Every 30-minute delay after 120 minutes lead to a 6% reduction in the likelihood of EVT. Lower DIDO time [OR-0.92 (0.9-0.96), p=0.04] and higher ASPECTS score [OR-1.4 (1.1-1.9), p=0.013] at spoke hospital are predictors of EVT at hub hospital. Conclusion: Reduced DIDO times are associated with higher likelihood of receiving EVT. DIDO should be treated on par as in-hospital time metrics and methods should be in place to optimize transfer 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 WP470: Stroke’s Pathways of Patients Transported by Advanced Life Support Ambulance: A 26 Years Registry

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Anna Ozguler ◽  
Michel Baer ◽  
Jeremie Boutet ◽  
Adrien Altar ◽  
Thomas Loeb
Keyword(s):  
Medical Service ◽  
Life Support ◽  
Age Groups ◽  
Care Facility ◽  
Advanced Life Support ◽  
Older Age ◽  
Radiology Department ◽  
Stroke Patients ◽  
Stroke Units ◽  
Paris Area

Introduction: Since mid-2000, stroke guidelines were revised and 18 stroke units (SU) settled in Paris area (France). Our Emergency Medical Service (EMS) in a catchment of 500 000 inhabitants registered all acute strokes where dispatch of an Advanced Life Support (ALS) ambulance was decided since 1993. Methods: Data were collected from an EMS registry (1993-2019). The study included patients 16 years old and over, with an acute stroke requiring an ALS ambulance. Collected data were gender, age (by quartile), time periods (1993-99, 2000-04, 2005-09, 2010-14, 2015-19) and receiving care facility: SU, neurosurgery, intensive care unit (ICU), emergency department (ED), radiology department (MRI or scanner) or left on scene (LOS dead or alive). Comparisons were performed with Chi-2 test. Results: This study included 2955 stroke patients, mean age was 70.7 years old, sex ratio was 0.93. Table 1 and graphic 1 results show the emergence of SU during mid-2000, with a decrease of ED transfers, while neurosurgery and ICU remained steady (p<10 -3 ). This decrease of ED was more important for older age groups (≥ 75 years old). Conclusion: Older age groups benefitted more from specialized pathways including ICU and SU, with less transports to ED, but never clearly from neurosurgery. Development of SU probably explains the decreased number of younger patients in neurosurgery. Literature shows that direct pathway to SU significantly improved prognosis of stroke patients. This registry of ALS transports shows its growing use in EMS dispatch, as for ST+ myocardial infarction, while transports to ED decrease. It would be interesting to compare these results with those of faster Basic Life Support transports.

Abstract P268: Community Wide Real-Time Stroke Code Capture to Better Identify Changes in Health Care Utilization During Covid-19

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Amelia Kenner Brininger ◽  
Lindsay L Olson-Mack ◽  
Lorraine Chmielowski ◽  
Kristi L Koenig ◽  
Mary A Kalafut ◽  
...  
Keyword(s):  
Acute Stroke ◽  
Real Time ◽  
Healthcare Utilization ◽  
San Diego ◽  
San Diego County ◽  
Discharge Data ◽  
Stroke Incidence ◽  
Number Of Patients ◽  
Stroke Center ◽  
The Impact

Introduction: Many healthcare systems reported a decline in stroke admissions in the early months of the COVID-19 pandemic. We used real-time hospital admission data from Stroke Receiving Centers (SRCs) across San Diego County to quantify changes in stroke patients accessing healthcare with the onset of the COVID-19 pandemic. Rather than waiting for months-delayed discharge data, real-time stroke code data was used to understand the impact on healthcare utilization which may better inform mitigation strategies to encourage accessing care for acute stroke. Methods: We analyzed the total number of patients presenting to any of the 18 San Diego County SRCs for which a stroke code was activated between January 1, 2019 and July 31, 2020; and separated the times into: pre-pandemic (PP) as January 2019 thru February 2020, early-pandemic (EP) as March and April 2020, and mid-pandemic (MP) as May-July 2020. Patients arriving via emergency medical services or private transport were included. A public messaging campaign regarding the safety of accessing care for acute stroke started in early May 2020. Results: A total of 14,028 stroke codes were initiated between January 2019 and July 2020. An average of 43.2 stroke codes were activated per stroke center per month (range=39.6 to 46.7 activations per stroke center per month) during PP, 30.6 during EP and 37.7 during MP (p=.019). Overall, 30% fewer stroke code activations occurred during EP compared to the same months in the PP (p=.012). Mid-pandemic, there were 14.6% fewer stroke code activations compared to the same months pre-pandemic (p=.095). Conclusion: Stroke code activations decreased by 30% across San Diego County SRCs in the EP period compared to the previous year. It is unclear if this is primarily due to decreased healthcare utilization at the start of the COVID-19 pandemic or if there were changes in stroke incidence. MP showed stroke code activations increased compared to EP. This may be partially due to the public messaging campaign initiated after an analysis of PP to EP stroke code activations. We will continue to analyze stroke code data to better understand the impact of public messaging campaigns and determine when activations have returned to PP levels.

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.

Sign in / Sign up

Export Citation Format

Share Document