Emergency Medical Services Stroke Research Articles

Prevalence and Determinants of Prehospital Impression of Stroke in Ischemic Stroke Patients.

Emergency Medical Services (EMS) clinicians are front-line in evaluating patients with stroke in the community. Their ability to correctly identify stroke influences downstream management decisions. We sought to use a large national database of prehospital clinical data to determine risk factors associated with missed EMS stroke identification. Retrospective study examining EMS evaluation of adults with Emergency Department (ED) stroke diagnosis. We leveraged the ESO Data Collaborative research dataset containing EHR data from 2019-2022 that has a subset of encounters with linked hospital diagnostic codes. Our primary outcome was the presence of an EMS diagnosis of stroke. We evaluated the association between demographic and clinical variables with EMS stroke identification using Pearson χ2 test for demographic variables and multivariable GLM for clinical variables with adjustment for demographic variables. We identified 34,504 EMS encounters for patients with ED stroke diagnosis. Of these, 11,077 (32.1%) strokes had missed EMS stroke identification and instead had an EMS impression of "Generalized Weakness" (25.9%), "Altered Level of Consciousness" (24.9%), and "Dizziness" (7.2%). Patients more likely to have missed prehospital stroke identification were of Black race (p=0.0001) and Hispanic ethnicity (p=0.0001). Clinical variables associated with higher risk of missed EMS stroke identification were suspected alcohol or drug use (RR 1.48, 95% CI 1.37-1.59), low GCS (RR 1.17, 95% CI 1.10-1.24), tachycardia (RR 1.05, 95% CI 1.01-1.09), and hypotension (RR 1.47, 95% CI 1.34-1.61). Approximately 1-in-3 patients transported by EMS did not have their stroke identified in the prehospital setting. Factors associated with lower odds of missed EMS stroke identification provide a starting point for future performance improvement initiatives.

Rural-urban differences in emergency medical services bypass routing of stroke in North Carolina.

Acute stroke is a serious, time-sensitive condition requiring immediate medical attention. Emergency medical services (EMS) routing and direct transport of acute stroke patients to stroke centers improves timely access to care. This study aimed to describe EMS stroke routing and transports by rurality in North Carolina (NC). We conducted a retrospective study using existing data on EMS transports of suspected stroke patients in NC in 2019. The primary study outcome was EMS bypass of the nearest hospital for transport to a nonnearest hospital, determined by geographic information systems (GIS) analysis. Incident addresses were geocoded to census tracts and classified as urban, suburban, or rural by Rural-Urban Commuting Area codes. We compared the frequency of bypass and estimated additional transport times by urban, suburban, and rural incident locations. Of 3666 patients, 1884 (51%) EMS transports bypassed the nearest hospital. Bypass occurred less often for rural EMS incidents (39%) compared to those in urban (57%) and suburban (63%) tracts. The estimated additional transport time for rural bypasses of nonendovascular-capable stroke centers for endovascular-capable stroke centers was a median of 25min (interquartile range 13-33). Using GIS analysis, we found nearly half of EMS transports of suspected stroke patients in NC bypassed the nearest hospital, including noncertified hospitals and stroke centers. Bypasses occurred less often in rural areas, though incurred significantly longer transport times, compared to urban areas. These findings are important for regional stroke system planning, especially for improving rural access to acute stroke care.

Abstract WP93: Providing Stroke Reports to Emergency Medical Services (EMS) Agencies Improves Data Quality in Michigan's Statewide EMS Data Repository

Intro: The Michigan Stroke Program (MiSP) monitors statewide EMS stroke care performance and data quality. Starting in 2018, quarterly performance and outcome benchmark data were shared with EMS agency partners to support prehospital quality improvement (QI) for stroke patients. Objective: To improve EMS data quality and prehospital stroke care performance. Methods: This is a retrospective before and after study of the impact of tailored QI interventions to improve EMS compliance with three prehospital stroke quality metrics selected by MiSP EMS partners: (prehospital stroke scale documentation, last known well documentation, and prehospital notification). Five MiSP EMS partners participated in the intervention which consisted of provision of quarterly performance reports generated from linked data from Michigan’s EMS Information System and the Michigan Stroke Registry. The MiSP team reviewed agency performance with EMS leadership to select the target measures for intervention and then assisted in development of a QI plan to improve agency performance. Measure compliance was compared from three months prior to and six months after data quality solutions were implemented. Results: Through data sharing and communication with EMS agencies and EMS software data vendors, common themes were identified related to poor data quality beginning in January 2020. A sample of agencies and resolutions to address these issues are displayed in the Table. Compliance with the targeted metric improved significantly at each agency at three and six months following intervention. Conclusions: Analysis of EMS data and sharing performance data directly with EMS agency partners identified correctable data quality issues negatively impacting EMS quality measures. Correcting these issues led to dramatic and sustained improvement in EMS quality metric compliance. This approach may serve as a model for improving the accuracy of EMS performance data in state-level EMS registries.

Emergency Medical Services Compliance With Prehospital Stroke Quality Metrics Is Associated With Faster Stroke Evaluation and Treatment.

Emergency medical services (EMS) is an important link in the stroke chain of recovery. Various prehospital quality metrics have been proposed for prehospital stroke care, but their individual impact is uncertain. We sought to measure associations between EMS quality metrics and downstream stroke care. This is a retrospective analysis of a cohort of EMS-transported stroke patients assembled through a linkage between Michigan's EMS and stroke registries. We used multivariable regression to quantify the independent associations between EMS quality metric compliance (dispatch within 90 seconds of 911 call, prehospital stroke screen documentation [Prehospital stroke scale], glucose check, last known well time, maintenance of scene times ≤15 minutes, hospital prenotification, and intravenous line placement) and shorter door-to-CT times (door-to-CT ≤25), accounting for EMS recognition, age, sex, race, stroke subtype, severity, and duration of symptoms. We then developed a simple EMS quality score based on metrics associated with early CT and examined its associations with hospital stroke evaluation times, treatment, and patient outcomes. Five thousand seven hundred seven EMS-transported stroke cases were linked to prehospital records from January 2018 through June 2019. In multivariable analysis, prehospital stroke scale documentation (adjusted odds ratio, 1.4 [1.2-1.6]), glucose check (1.3 [1.1-1.6]), on-scene time ≤15 minutes (1.6 [1.4-1.9]), hospital prenotification ([2.0 [1.4-2.9]), and intravenous line placement (1.8 [1.5-2.1]) were independently associated with a door-to-CT ≤25 minutes. A 5-point quality score (1 point for each element) was therefore developed. In multivariable analysis, a 1-point higher EMS quality score was associated with a shorter time from EMS contact to CT (-9.2 [-10.6 to -7.8] minutes; P<0.001) and thrombolysis (-4.3 [-6.4 to -2.2] minutes; P<0.001), and higher odds of discharge to home (adjusted odds ratio, 1.1 [1.0-1.2]; P=0.002). Five EMS actions recommended by national guidelines were associated with rapid CT imaging. A simple quality score derived from these measures was also associated with faster stroke evaluation, greater odds of reperfusion treatment, and discharge to home.

Policy implementation strategies to address rural disparities in access to care for stroke patients.

Stroke systems of care (SSOC) promote access to stroke prevention, treatment, and rehabilitation and ensure patients receive evidence-based treatment. Stroke patients living in rural areas have disproportionately less access to emergency medical services (EMS). In the United States, rural counties have a 30% higher stroke mortality rate compared to urban counties. Many states have SSOC laws supported by evidence; however, there are knowledge gaps in how states implement these state laws to strengthen SSOC. This study identifies strategies and potential challenges to implementing state policy interventions that require or encourage evidence-supported pre-hospital interventions for stroke pre-notification, triage and transport, and inter-facility transfer of patients to the most appropriate stroke facility. Researchers interviewed representatives engaged in implementing SSOC across six states. Informants (n = 34) included state public health agency staff and other public health and clinical practitioners. This study examined implementation of pre-hospital SSOCs policies in terms of (1) development roles, processes, facilitators, and barriers; (2) implementation partners, challenges, and solutions; (3) EMS system structure, protocols, communication, and supervision; and (4) program improvement, outcomes, and sustainability. Challenges included unequal resource allocation and EMS and hospital services coverage, particularly in rural settings, lack of stroke registry usage, insufficient technologies, inconsistent use of standardized tools and protocols, collaboration gaps across SSOC, and lack of EMS stroke training. Strategies included addressing scarce resources, services, and facilities; disseminating, training on, and implementing standardized statewide SSOC protocols and tools; and utilizing SSOC quality and performance improvement systems and approaches. This paper identifies several strategies that can be incorporated to enhance the implementation of evidence-based stroke policies to improve access to timely stroke care for all patient populations, particularly those experiencing disparities in rural communities.

Community Socioeconomic and Urban-Rural Disparities in Prehospital Notification of Stroke by Emergency Medical Services in North Carolina.

Notification by emergency medical services (EMS) to the destination hospital of an incoming suspected stroke patient is associated with timelier in-hospital evaluation and treatment. Current data on adherence to this evidence-based best practice are limited, however. We examined the frequency of EMS stroke prenotification in North Carolina by community socioeconomic status (SES) and rurality. Using a statewide database of EMS patient care reports, we selected 9-1-1 responses in 2019 with an EMS provider impression of stroke or documented stroke care protocol use. Eligible patients were 18 years old and older with a completed prehospital stroke screen. Incident street addresses were geocoded to North Carolina census tracts and linked to American Community Survey socioeconomic data and urban-rural commuting area codes. High, medium, and low SES tracts were defined by SES index tertiles. Tracts were classified as urban, suburban, and rural. We used multivariable logistic regression to estimate independent associations between tract-level SES and rurality with EMS prenotification, adjusting for patient age, sex, and race/ethnicity; duration of symptoms; incident day of week and time of day; 9-1-1 dispatch complaint; EMS provider primary impression; and prehospital stroke screen interpretation. The cohort of 9527 eligible incidents was mostly at least 65 years old (65%), female (55%), and non-Hispanic White (71%). EMS prenotification occurred in 2783 (29%) patients. Prenotification in low SES tracts (27%) occurred less often than in medium (30%) and high (32%) SES tracts. Rural tracts had the lowest frequency (21%) compared with suburban (28%) and urban (31%) tracts. In adjusted analyses, EMS prenotification was less likely in low SES (vs high SES; odds ratio 0.76, 95% confidence interval 0.67-0.88) and rural (vs urban; odds ratio 0.64, 95% confidence interval 0.52-0.77) tracts. Across a large, diverse population, EMS prenotification occurred in only one-third of suspected stroke patients. Furthermore, low SES and rural tracts were independently associated with a lower likelihood of prehospital notification. These findings suggest the need for education and quality improvement initiatives to increase EMS stroke prenotification, particularly in underserved communities.

Uncooperative patients suspected of acute stroke ineligible for prehospital stroke screening test by emergency medical service providers: final hospital diagnoses and characteristics.

This study investigated the hospital diagnoses and characteristics of uncooperative prehospital patients suspected of acute stroke who could not undergo a prehospital stroke screening test (PHSST). This retrospective observational study was conducted at a single academic hospital with a regional stroke center. We analyzed three scenario-based prehospital stroke screening performances using the final hospital diagnoses: (1) a conservative approach only in patients who underwent the PHSST, (2) a real-world approach that considered all uncooperative patients as screening positive, and (3) a contrapositive approach that all uncooperative patients were considered as negative. Of the 2,836 emergency medical services (EMS)-transported adult patients who met the prehospital criteria for suspicion of acute stroke, 486 (17.1%) were uncooperative, and 570 (20.1%) had a confirmed final diagnosis of acute stroke. The diagnosis in the uncooperative group did not differ from that in the cooperative group (22.0% vs. 19.7%, P=0.246). The diagnostic performances of the PHSST in the conservative approach were as follows: 79.5% sensitivity (95% confidence interval [CI], 75.5%-83.1%), 90.2% specificity (95% CI, 88.8%-91.6%), and 0.849 area under the receiver operating characteristic curve (AUC; 95% CI, 0.829-0.868). The sensitivity and specificity were 83.3% (95% CI, 80.0%-86.3%) and 75.2% (95% CI, 73.3%-76.9%), respectively, in the real-world approach and 64.6% (95% CI, 60.5%-68.5%) and 91.9% (95% CI, 90.7%-93.0%), respectively, in the contrapositive approach. No significant difference was evident in the AUC between the real-world approach and the contrapositive approach (0.792 [95% CI, 0.775-0.810] vs. 0.782 [95% CI, 0.762-0.803], P>0.05). We found overestimation (false positive) and underestimation (false negative) in the uncooperative group depending on the scenario-based EMS stroke screening policy for uncooperative prehospital patients suspected of acute stroke.

Emergency Medical Services Stroke Care Performance Variability in Michigan: Analysis of a Statewide Linked Stroke Registry.

Background Emergency medical services (EMS) compliance with recommended prehospital care for patients with acute stroke is inconsistent; however, sources of variability in compliance are not well understood. The current analysis utilizes a linkage between a statewide stroke registry and EMS information system data to explore patient and EMS agency-level contributions to variability in prehospital care. Methods and Results This is a retrospective analysis of a cohort of confirmed stroke cases transported by EMS to hospitals participating in a statewide stroke registry. Using EMS information system data, the authors quantified EMS compliance with 6 performance measures derived from national guidelines for prehospital stroke care: prehospital stroke scale performance, glucose check, stroke recognition, on-scene time ≤15 minutes, time last known well documentation, and hospital prenotification. Multilevel multivariable logistic regression analysis was then used to examine associations between patient-level demographic and clinical characteristics and EMS compliance while accounting for and quantifying the variation attributable to agency of transport and recipient hospital. Over an 18-month period, EMS and stroke registry records were linked for 5707 EMS-transported stroke cases. Compliance ranged from 24% of cases for last known well documentation to 82% for documentation of a glucose check. The other measures were documented in approximately half of cases. Older age, higher National Institutes of Health Stroke Scale, and earlier presentation were associated with more compliant prehospital care. EMS agencies accounted for more than half of the variation in EMS prehospital stroke scale documentation and last known well documentation and 27% of variation in glucose check but <10% of stroke recognition and prenotification variability. Conclusions EMS stroke care remains highly variable across different performance measures and EMS agencies. EMS agency and electronic medical record type are important sources of variability in compliance with key prehospital performance metrics for stroke.

Interactive Training of the Emergency Medical Services Improved Prehospital Stroke Recognition and Transport Time.

Background and PurposeAcute stroke treatment outcomes are predicated on reperfusion timeliness which can be improved by better prehospital stroke identification. We aimed to assess the effect of interactive emergency medical services (EMS) training on stroke recognition and prehospital care performance in a very high-risk cardiovascular risk population in Lithuania.MethodsWe conducted a single-center interrupted time-series study between March 1, 2019 and March 15, 2020. Two-hour small-group interactive stroke training sessions were organized for 166 paramedics serving our stroke network. We evaluated positive predictive value (PPV) and sensitivity for stroke including transient ischemic attack identification, onset-to-door time, and hospital-based outcomes during 6-months prior and 3.5 months after the training. The study outcomes were compared between EMS providers in urban and suburban areas.ResultsIn total, 677 suspected stroke cases and 239 stroke chameleons (median age 75 years, 54.8% women) were transported by EMS. After the training, we observed improved PPV for stroke recognition (79.8% vs. 71.8%, p = 0.017) and a trend of decreased in-hospital mortality (7.8% vs. 12.3, p = 0.070). Multivariable logistic regression models adjusted for age, gender, EMS location, and stroke subtype showed an association between EMS stroke training and improved odds of stroke identification (adjusted odds ratio [aOR] 1.6 [1.1–2.3]) and onset-to-door ≤ 90 min (aOR 1.6 [1.1–2.5]). The improvement of PPV was observed in urban EMS (84.9% vs. 71.2%, p = 0.003), but not in the suburban group (75.0% vs. 72.6%, p = 0.621).ConclusionsThe interactive EMS training was associated with a robust improvement of stroke recognition, onset to hospital transport time, and a trend of decreased in-hospital mortality. Adapted training strategies may be needed for EMS providers in suburban areas. Future studies should evaluate the long-term effects of the EMS training and identify optimal retraining intervals.

Abstract 23: Population Access To Acute Stroke Expertise In The United States

Backgound: In 2011, nearly 20% of Americans lacked timely access to alteplase-capable hospitals. We update this work by assessing access to stroke centers and emergency departments (EDs) with telestroke capacity. Our objectives are to identify all US EDs with acute stroke capabilities (i.e., in a confirmed stroke center or with telestroke capacity), and to characterize the proportion of the US population with access to an ED with either capacity. Methods: We used the 2019 National ED Inventory-USA to identify all US EDs and characterize stroke capabilities by hospital stroke center status (none, acute stroke ready hospital [ASRH], primary stroke center [PSC], thrombectomy-capable or comprehensive stroke center [TSC/CSC]) and telestroke capacity. We used 2020 US Census data for census block group population and centroid. For each block group, we used ArcGIS to assess whether an ED with stroke expertise was within a 60 minute (min) response and transport time by ground emergency medical services (EMS). To determine the transport time, we used data from actual EMS stroke transports using the 2019 National EMS Information System with median EMS dispatch, response, and scene times in access calculations. Results: Of 5,587 US EDs, 2,563 (46%) were in a stroke center (691 ASRH, 1,505 PSC, 367 TSC/CSC); of these, 55% also had telestroke capacity. Of the 3,024 (54%) that were not a confirmed stroke center, 36% had telestroke. We estimate that 91% of the US population is within 60 min of a confirmed stroke center by ground EMS and 96% is within 60 min of a confirmed stroke center or telestroke ED (Figure). The percentage of the population without access to a confirmed stroke center or telestroke ED varied by region, from 1% in the Middle Atlantic to 9% in the West Mountain. Conclusion: Relative to previous reports, an increasing proportion of the US population has access to acute stroke expertise. While geographic disparities in access remain, telestroke plays an important role in filling this gap.

Abstract TP87: Discrete-event Simulation Of The Prehospital Stage Of The Acute Ischemic Stroke

Introduction: It is critical to treat Acute Ischemic Stroke (AIS) patients quickly; however, treatment eligibility is dependent on the arrival time to the nearest stroke center by Private Vehicle (PV) or Emergency Medical Services (EMS). The duration in the prehospital stage is defined as the period from stroke onset to arrival at a non-stroke center, primary stroke center or comprehensive stroke center. This study aims to detail the prehospital stage of suspected AIS patients in order to identify opportunities for process improvements. Methods: Discrete-event simulation (DES) is a powerful decision-making tool and robust methodology for evaluating treatment processes and allows for improvements to be tested before implementing changes using real resources. A DES is developed using ARENA software to model the prehospital stage of suspected AIS patients. The process steps include two treatment pathways, PV and EMS. The pathways differ because those patients arriving via EMS allow for the activation of the code stroke protocol prior to hospital arrival. The drive times from the stroke scene to the hospital were kept constant at 40 min assuming a suburban transport. The model assumes 60% recognition of ischemic stroke using EMS stroke screening tools and large vessel occlusion screening tools and a 90% probability that the paramedics correctly screen for a potential stroke and bypass to a stroke center. The primary outcome measure is median onset-to-door time, defined as the time from onset of stroke symptoms to arrival to the hospital. The Mann-Whitney U test is used for evaluating statistical significance among the outputted median onset-to-door time for all scenarios. Results: The following process improvement scenarios were run: reducing the waiting time for EMS on average from 7 min to 5 min and reducing delays on-scene on average from 20 min to 15 min, and the median onset-to-door time reductions were from a median of 57.53 min to a median of 51.41 min (p&lt;0.0001). Conclusions: Reduction in onset to arrival times is possible by reducing waiting time for the EMS and delay on-scene of the stoke.

Abstract WP52: Emergency Medical Services Documentation Of Stroke Care In The United States

Introduction: Emergency medical services (EMS) are often the first point of medical contact for patients suffering from acute stroke. EMS must identify and triage patients appropriately for them to receive the best care. Several prehospital stroke scales exist to assist prehospital providers in identifying acute stroke in the field, but their real-world applications are poorly characterized. Understanding prehospital stroke treatment provides the opportunity to identify areas of improvement across the stroke continuum of care. Methods: We retrospectively reviewed data from the 2019 National EMS Information System (NEMSIS) dataset from the United States of America. NEMSIS contains standardized information reported by states on EMS activations. Observations included were transported by ground ambulance and had an EMS provider documented stroke assessment with a primary impression of stroke or TIA. Observations excluded interfacility transfers and were limited to activations that documented pre-notification of hospital-based stroke specialty team resources. Results: EMS providers used a variety of stroke scales in 2019. Of 30,436 observations, the Cincinnati Prehospital Stroke Scale was the most common with 17,462 uses (57.37%). The F.A.S.T. Exam came second with 3366 (11.05%) uses and the Los Angeles Prehospital Stroke Scale with 3,146 (10.33%). EMS providers recorded “Other Stroke Scale Type” 4362 (14.33%) times. EMS providers documented either a negative or inconclusive stroke score 10,390 (34.13%) times. EMS documented stroke specialty team notifications 17,391 (57.14%) of the time. EMS did not pre-notify the stroke specialty team for 13,045 (42.86%) of patients. 3,576 (27.41%) of these patients received a negative stroke scale score, 1,745 (13.38%) inconclusive and 7,724 (59.21%) positive respectively. Among cases where EMS notified a stroke specialty team 1,590 (9.14%) received a negative, 2,479 (14.25%) an inconclusive and 13,322 (76.60%) a positive stroke scale score. Conclusion: US EMS stroke care documentation has substantial variability and is ripe for standardization. This fact necessitates research to understand its causes and achieve pre-hospital stroke care optimization on a national scale.

Emergency Medical Services (EMS) Calls During COVID-19: Early Lessons Learned for Systems Planning (A Narrative Review).

BackgroundOver the course of the COVID-19 progress, reports from many locations around the world indicated major increases in EMS call volume, which imposed great pressure on EMS dispatch centers (EMSDC) globally. No studies yet have been done to examine this phenomenon.ObjectiveThis paper examines the interrelated effects of the unprecedented global increase of EMS call, the effect of the COVID-19 crisis on responding to non-COVID-19 emergencies, and the concurrent effects of having overwhelmed dispatch centers. It tries to explain the current evidence of the bottleneck of EMS calls during the early phase of the worldwide pandemic.Eligibility CriteriaWe examine the numbers of EMS calls internationally between March and June 2020, derived from published literature and news media. Only articles in English were selected, with certain keywords related to EMS calls, ambulance delay, stroke and cardiac arrest.Source of EvidenceGoogle Scholar was the main searching source.ResultsAfter applying the selection criteria, a total of 29 citations were chosen, and a pattern of knowledge resulted in the emergence of five themes: EMS calls during COVID-19, Reduced EMS operator response time, Ambulance response delays, Collateral mortality and morbidity among non-COVID-19 cases, and Total ambulance call time.ConclusionOver the course of COVID-19 progress, there was a global phenomenon of exponential increases in EMS calls, which is expected to impose a great pressure on EMS dispatch centers. Several factors contributing to the bottleneck of EMS calls are identified and explained.

Time Is Brain: Prehospital Emergency Medical Services Response Times for Suspected Stroke and Effects of Prehospital Interventions

ObjectivesTo compare prehospital time for patients with suspected stroke in Florida with the American Stroke Association (ASA) time benchmarks, and to investigate the effects of dispatch notification and stroke assessment scales on prehospital time. Patients and MethodsA retrospective analysis was performed using data from Florida’s Emergency Medical Services Tracking and Reporting System database. All patients with suspected stroke transported to a treatment center from January 1, 2018, through December 31, 2018, were analyzed. Time intervals from 911 call to hospital arrival were evaluated and compared with ASA benchmarks. ResultsIn 2018, 11,577 patients with suspected stroke were transported to a hospital (mean age, 71.5±15.7 years; 51.5% women). The median alarm-to-hospital time was 33.98 minutes (27.8 to 41.4), with a total emergency medical services (EMS) time of 32.30 minutes (26.5 to 39.478). The on-scene time was the largest time interval with a median of 13.28 minutes (10.0 to 17.4). Emergency medical services encounters met the ASA benchmarks for time in 58% to 62% of the EMS encounters in Florida (recommended 90%; P<.001). The total EMS time was reduced when a stroke notification was reported by the dispatch center (32.00 minutes vs 32.62 minutes; P=.006) or when a stroke assessment scale was used by the EMS personnel (31.88 minutes vs 32.96 minutes; P=.005). ConclusionThis study reveals a substantial opportunity for improvement in stroke care in Florida. Two prehospital EMS stroke interventions seem to reduce prehospital time for patients with suspected stroke. Adoption of these interventions might improve the stroke systems of care.

Abstract 19: Prehospital Identification of Acute Ischemic Stroke is Associated With Faster and More Frequent Thrombolysis

Background: Functional outcomes are improved when AIS patients receive faster treatment. The first medical contact for many AIS patients is with emergency medical services (EMS) providers. We hypothesize that AIS treatment is faster when EMS providers suspect stroke. Methods: We performed a retrospective analysis of the Greater Cincinnati/Northern Kentucky Stroke Study, a comprehensive study of stroke patients in a large geographical area with 1.3 million inhabitants whose demographics are representative of the United States. We compared AIS patients age ≥18 years transported by EMS in 2015 with an EMS impression of “stroke” or “weakness/numbness” to those with other EMS impressions. Primary outcome was thrombolysis rate, and secondary outcomes were times from EMS scene arrival to ED arrival, CT, and treatment and times from ED arrival to CT and treatment. Chi-square and Mann-Whitney U-tests were used to compare treatment rates and times, respectively. Logistic regression (for rates) and median regression (for times) adjusted for NIHSS, GCS, age, sex, race, and prior stroke history. Results: Among 2,486 confirmed AIS patients from 1/1/2015-12/31/2015, 868 were transported by EMS, including 595 (69%) with EMS suspected stroke. Compared to EMS non-suspected strokes, patients with EMS suspected stroke patients were more likely to receive thrombolysis (18% vs 8%; OR 2.67, 95% CI 1.63-4.47) and had faster prehospital transport (30 vs 32 min, p=0.02), ED arrival to CT (27 vs 46 min, p&lt;0.01) and thrombolysis (64 vs 83 min, p=0.03), and EMS scene arrival to thrombolysis (91 vs 118 min, p=0.03) and EVT (164 vs 250 min, p=0.03). Findings were maintained in the adjusted models except for EMS arrival to EVT (Table). Conclusions: In a large population-based study, EMS stroke identification is associated with a higher rate of and faster thrombolysis. Efforts to increase accuracy of EMS stroke identification is likely to have significant clinical impact by shortening treatment times.

Abstract P161: The Effect of Simulation Based Education on Nursing and EMS Stroke Care

Background: Treatment options for acute ischemic stroke (AIS) now include mechanical thrombectomy. As a result, primary stroke centers (PSC) must quickly identify large vessel occlusion (LVO) patients, treat them with alteplase when appropriate and transfer them to a comprehensive stroke center (CSC) for potential mechanical thrombectomy. Given the need for expedited care in the emergency department, collaboration with emergency medical services (EMS) in the pre-hospital setting and timely administration of alteplase prior to transfer to the CSC have been identified as practice gaps. Purpose: To examine the effect of an educational stroke simulation session on the knowledge and confidence level of registered nurses (RN) and EMS providers who care for patients with acute stroke receiving alteplase. Methods: Simulations were 60 min, in groups of 4-5 RNs and 1-2 EMS providers, and focused on neurological assessment, administration of alteplase, and rapid transfer when a LVO is suspected and/or identified. Participants completed a pre and post simulation survey assessing confidence levels of nurse role actions and knowledge of stroke care (Table 1). A paired samples t-test examined differences in confidence levels and total percent of correctly answered questions on the survey, pre versus post simulation. A McNemar test examined differences in the proportion of participants that correctly answered each question on the test pre versus post simulation. Results: Following the stroke simulation, the confidence levels of nurses increased for all nurse role actions (all P s&lt;0.01; Table 1) and there was an increase in the number of correct answers for 3 of the 6 test questions (all P s&lt;0.05; Table 1), as well as the total percent of correctly answered test questions ( P &lt;0.001). Conclusions: Simulation based education can be an effective training tool for improving the knowledge and confidence of nursing and EMS providers in the management of AIS.

Accuracy and Implications of Hemorrhagic Stroke Recognition by Emergency Medical Services

Background Hemorrhagic stroke is a medical emergency that requires rapid identification and treatment. Despite playing a critical role in the emergency response to hemorrhagic stroke patients, a minimal amount is known about the quality of emergency medical services (EMS) care for this condition. The objectives of this study were to quantify EMS hemorrhagic stroke recognition, identify predictors of accurate EMS recognition, and examine associations between EMS recognition, quality of prehospital care, and patient outcomes. Methods: Consecutive EMS-transported hemorrhagic strokes were identified from medical records at 4 primary stroke centers. Data regarding prehospital care were abstracted from EMS records and linked to in-hospital data. Clinical predictors of accurate EMS recognition were examined using logistic regression. EMS performance measure compliance and hospital outcomes were also compared among EMS recognized and unrecognized hemorrhagic strokes. Results: Over 24 months, EMS-transported 188 hemorrhagic stroke patients; 108 (57.4%) were recognized by EMS. Recognized cases had higher rates of stroke scale documentation (84.3% vs. 20.0%, p < 0.001); multivariable logistic regression confirmed a strong independent relationship between stroke scale documentation and recognition (adjusted OR 15.1 [5.6 to 40.7]). Recognized cases also had shorter on-scene times (15.5 vs. 21 min, p < 0.001) and door-to-computed tomography (DTCT) acquisition times (20 vs. 47 min, p < 0.001). Conclusions: Among EMS-transported hemorrhagic stroke cases, stroke screen documentation was strongly associated with EMS stroke recognition, which was in turn associated with higher quality of EMS care and faster computed tomography (CT) scans upon emergency department arrival.

The accuracy of the FAST stroke assessment in identifying stroke at initial ambulance call into a South African private emergency call centre.

Stroke is a potentially life-threatening, time-dependent event, and one of the leading causes of mortality and lasting morbidity in South Africa (SA). It is of vital importance that Emergency Medical Services (EMS) call-takers accurately recognise stroke symptoms and prioritise time as well as adequate care. EMS call-takers are the first link in stroke care and improving call-taker recognition of stroke signs and symptoms can drastically improve patient outcome. The Newcastle Face Arm Speech Time (FAST) test is a mnemonic aimed at improving diagnostic accuracy of stroke. To assess the use of the FAST test at a call-taker level to raise early suspicion of stroke and appropriately allocate resources to increase awareness of time and decrease delays on scene. A retrospective diagnostic study to determine the accuracy of the FAST mnemonic at identifying stroke when applied at EMS call-taker level. The outcome of the FAST assessment was compared with EMS stroke diagnosis for cases of a private SA EMS over a three-month period (N=146). Using FAST, call-takers were able to identify stroke with a sensitivity of 87.5% and a specificity of 17.4% (positive predictive value 34%, negative predictive value 74%). This yielded an overall accuracy of 40.41%. FAST is a useful screening tool for identifying stroke at call-taker level. FAST has acceptable sensitivity when used as a screening tool; however, specificity and diagnostic effectiveness are lacking. Further studies should be considered to determine call-taker as well as general public knowledge of stroke risk factors and presentation. Stroke is one of the leading causes of death and lasting morbidity in South Africa (SA) and is increasing in incidence. Early recognition of stroke at initial emergency call may expedite treatment, thus improving outcomes. This study demonstrates that the application of the FAST assessment at emergency contact centre level in SA, might be useful at identifying stroke early. Future research should investigate barriers to its use.

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

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 &lt; 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 &lt; 6 hours (p=.00001) were all correlated with shorter transport time; hospital stroke diagnosis (p=.56) was not. Linear regression indicated LKN to enroute &lt; 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.

Correction to: Brief Educational Intervention Improves Emergency Medical Services Stroke Recognition.

HomeStrokeVol. 50, No. 10Correction to: Brief Educational Intervention Improves Emergency Medical Services Stroke Recognition Free AccessCorrectionPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessCorrectionPDF/EPUBCorrection to: Brief Educational Intervention Improves Emergency Medical Services Stroke Recognition Originally published23 Sep 2019https://doi.org/10.1161/STR.0000000000000208Stroke. 2019;50:e313This article corrects the followingBrief Educational Intervention Improves Emergency Medical Services Stroke RecognitionIn the article by Oostema et al, “Brief Educational Intervention Improves Emergency Medical Services Stroke Recognition,” which published online ahead of print March 28, 2019, and appeared in the May 2019 issue of the journal (Stroke. 2019;50:1193–1200. doi: 10.1161/STROKEAHA.118.023885), a correction is needed.The affiliation for J. Adam Oostema, MD, should be:J. Adam Oostema, MD, Department of Emergency Medicine, Spectrum Health and Michigan State University College of Human Medicine, Secchia Center, 15 Michigan NE Grand Rapids, MI 49503. Email [email protected]edu.These corrections have been made to the current online version of the article, which is available at https://www.ahajournals.org/doi/10.1161/STROKEAHA.118.023885. Previous Back to top Next FiguresReferencesRelatedDetailsCited By Liu J, He J, Zhang C and Tang M (2022) Clinical Significance and Value of Serum Homocysteine and Urine 11 Dehydrothromboxane B2 Combined with Transferrin-Specific Peptide in the Diagnosis of Cerebral Apoplexy, Computational and Mathematical Methods in Medicine, 10.1155/2022/6130413, 2022, (1-9), Online publication date: 17-May-2022. Related articlesBrief Educational Intervention Improves Emergency Medical Services Stroke RecognitionJ. Adam Oostema, et al. Stroke. 2019;50:1193-1200 October 2019Vol 50, Issue 10 Advertisement Article InformationMetrics © 2019 American Heart Association, Inc.https://doi.org/10.1161/STR.0000000000000208PMID: 31545694 Originally publishedSeptember 23, 2019 PDF download Advertisement