Emergency Medical Services Transport Time Research Articles

Evaluation of the implementation of evidence-based pediatric asthma exacerbation treatments in a regional consortium of emergency medical Services Agencies

Objective Asthma exacerbations are a frequent reason for pediatric emergency medical services (EMS) encounters. The objective of this study was to examine the implementation of evidence-based treatments for pediatric asthma in a regional consortium of EMS agencies. Methods This retrospective study applied the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) implementation framework to data from an EMS agency consortium in the Cincinnati, Ohio region. The study analyzed one year before an oral systemic corticosteroid (OCS) option was added to the agencies’ protocol, and five years after the protocol change. We constructed logistic regression models for the primary outcome of Reach, defined as the proportion of pediatric asthma patients who received a systemic corticosteroid. We modeled Maintenance (Reach measured monthly over time) using time series models. Results A total of 713 patients were included, 133 pre- and 580 post-protocol change. In terms of Reach, 3% (n = 4) of eligible patients received a systemic corticosteroid pre-OCS versus 20% (n = 116) post-OCS. Multivariable modeling of Reach revealed the study period, EMS transport time, months since implementation of OCS, and number of bronchodilators administered by EMS as significant covariates for the administration of a systemic corticosteroid. For Maintenance, it took approximately two years to reach maximal administration of systemic corticosteroids. Conclusions Indicators of asthma severity and time since the protocol change were significantly associated with EMS administration of systemic corticosteroids to pediatric asthma patients. The two-year time for maximal Reach suggests further work is required to understand how to best implement evidence-based pediatric asthma treatments in EMS.

The Impact of Rural Hospital Closures on Emergency Medical Services Transport Times

Purpose: Previous studies have found disparities in emergency medical service (EMS) transports for rural residents including double the average response time and lower patient survival rates when compared with their urban counterparts. Since 2012, the rate of rural hospitals closures has risen alarmingly from previous years. Previous studies have linked the closure of rural hospitals to increased EMS transport and total activation time. However, data and methods used in previous studies have not included facility-level characteristics, which limits the ability to tease out the nuances of each closure. Thus, the purpose of this study is to examine the impact of rural hospital closures on EMS travel time, as well as the characteristics of the closed hospitals. Sample: Data sources for the study came from a state-level EMS database, the CMS Provider of Service files, and state-level hospital data reports. Methods: Geographic information system software was used to geocode hospital locations and generate service areas based on drive times. We identified rural hospitals that closed in Alabama between 2010-2018 and then identified the 911 call data from the state’s EMS database that occurred within close proximity of each of the hospitals of interest, resulting in a sample of 120,802 EMS calls. Findings: We identified five hospital closures within our time period. For one of the five closures, EMS transport time to the emergency department increased by thirteen minutes post-closure. In two of the five closures, transport time increased by five minutes or less. In two instances, however, transport time decreased. Conclusions: Our findings suggest that not all rural hospital closures result in increased EMS transport times as rural patients may have already been routinely transported to alternate hospitals. Additionally, specific characteristics of a hospital pre-closure may be related to changes in EMS travel times that occur post-closure. Keywords: Rural health, emergency medical services, access, hospital closure, travel distance DOI: https://doi.org/10.14574/ojrnhc.v22i1.690

Analysis of an Alternative Model of Definitive Care For Low-Acuity Emergency Calls: A Natural Experiment.

Emergency medical services (EMS) diversion strategies attempt to limit the impact of low-acuity care on emergency department (ED) crowding, but evidence supporting these strategies is scarce. This study aims to measure the effect of a treat-in-place and alternative destination program on ED transports and EMS utilization. We used a natural experiment study design to measure effects of a pilot prehospital diversion program on ED transport, number of EMS vehicles dispatched, and EMS time on task for low-acuity emergency calls in a midsized urban setting characterized by a high prevalence of health disparities, concentrated poverty, and limited access to primary care between October 2018 and January 2020. We also used direct variable cost to estimate the return on investment attributable to avoided ED visits. Of 3725 calls that met eligibility criteria, the program responded to 1084 (29.1%), with 56.7% of those resulting in an ED visit, compared with 64.6% of the 492 control calls that were eligible but were dispatched when program services were unavailable. Of 1084 calls receiving response, 213 (19.6%) were enrolled in the program, and 8.5% of those were transported by EMS to the ED. Adjusted results show EMS time on task was 23.4 min less for enrolled calls vs. controls. The program can achieve a positive return on investment by enrolling 2.9 patients/day. A prehospital diversion program reduced ED visits and EMS transport times. Improved targeting of patients for enrollment would further increase the intervention's efficacy and cost savings.

Effects of mode and time of EMS transport on the rate and distribution of dead on arrival among trauma population transported to ACSCOT-verified trauma centers in the United States.

Unintentional injury remains the leading cause of death for adults worldwide. We aimed to investigate the rates and distribution of dead on arrival (DOA) patients according to emergency medical services (EMS) mode of transport (MoT), EMS transport time (TT), injury severity score (ISS), and type of injury. This retrospective study utilized de-identified incident-based data from the American College of Surgeons Trauma Quality Improvement Program Participant Use File (ACS-TQIP PUF) dataset (2013-2018) to study Adult DOA patients. DOA was defined according to the data point, "arrived with no signs of life and did not recover". Patients with unknown vitals and patients with no EMS vitals at the scene (HR = 0, RR = 0, and SBP = 0) were excluded to identify DOAs who died during transport. The DOAs included for analysis were sorted into three groups based on injury severity score [low (ISS < 15), intermediate (ISS = 15-24), and severe (ISS ≥ 25)] and subdivided according to injury type (blunt vs. penetrating), EMS Mode of transport and transport times. Statistical significance was defined as p < 0.05. The majority of the evaluated 6030 adult DOA patients were male (73.3%) and 18-64 years of age (79.6%). Most patients sustained blunt injuries (58.2%), and the most common mechanism of injury was motor vehicle collisions (MVCs). Patients who traveled by helicopter EMS (HEMS) experienced less deaths than those traveling by ground EMS (GEMS) despite transporting more severely injured patients over longer time intervals. Median HEMS TTs were greater than their GEMS counterparts for blunt and penetrating injuries across all ISS groups but were associated with fewer deaths. Helicopter emergency medical service use with intermediate and severely injured patients with penetrating injuries is associated with a reduced number of DOAs. Future studies should prospectively investigate EMS performance to confirm the findings identified in this retrospective analysis. Additionally, other factors affecting pre-hospital EMS performance (e.g., geographic variations, weather-related characteristics, in-flight interventions/procedures) should be investigated. Finally, the results of this study highlight the need for standardized HEMS utilization triage criteria.

Abstract 10319: Community Socioeconomic and Urban-Rural Differences in Emergency Medical Services Time Intervals for Suspected Stroke Patients in North Carolina

Introduction: Rapid emergency medical services (EMS) response, care, and transport of acute stroke patients increases the likelihood of receiving time-sensitive treatment. There is limited research on the relationship of community factors with prehospital delays in EMS management of stroke. We compared EMS prehospital time intervals for suspected stroke patients by community socioeconomic status (SES) and urban-rural status in North Carolina (NC). Methods: We analyzed 2019 NC EMS encounter data collected in the National EMS Information System Version 3 standard. Eligible patients were adults requiring a 911 call response by EMS for stroke-like symptoms and transport to the hospital. Incident street addresses were geocoded to census tracts using ArcGIS Pro and linked to SES data from the American Community Survey and rural-urban commuting area (RUCA) codes. Community SES was defined as high, medium, or low based on tertiles of the AHRQ SES index. Urban, suburban, and rural tracts were defined by RUCA codes 1, 2-6, and 7-10, respectively. Differences in mean times by community SES and urban-rural status were evaluated using Kruskal Wallis tests. Results: We identified 17,117 eligible EMS encounters of suspected stroke (65% (11,121 of 17,117) 65+ years old; 55% (9,330 of 17,117) female; 70% (11,839 of 17,117) White) from 2,028 tracts. Median response, scene, and transport times were 8 (interquartile range, IQR 6-11) min, 16 (IQR 12-20) min, and 14 (IQR 9-22) min, respectively. Mean transport times were shorter in low SES (16 min) than in medium and high SES communities (17 min, p&lt;.0001). Mean transport times were longer in rural (21 min) and suburban (19 min) than in urban tracts (14 min, p&lt;.0001). Conclusions: EMS transport times were on average longer for suspected stroke patients in rural but not in low SES tracts. Further research is needed on the role of community socioeconomic deprivation and rurality in contributing to delays in prehospital stroke care.

Association between emergency medical service transport time and survival in patients with traumatic cardiac arrest: a Nationwide retrospective observational study

BackgroundPatients with traumatic cardiac arrest (TCA) are known to have poor prognoses. In 2003, the joint committee of the National Association of EMS Physicians and the American College of Surgeons Committee on Trauma proposed stopping unsuccessful cardiopulmonary resuscitation (CPR) sustained for > 15 min after TCA. However, in 2013, a specific time-limit for terminating resuscitation was dropped, due to the lack of conclusive studies or data. We aimed to define the association between emergency medical services transport time and survival to demonstrate the survival curve of TCA.MethodsA retrospective review of the Japan Trauma Data Bank. Inclusion criteria were age ≥ 16, at least one trauma with Abbreviated Injury Scale score (AIS) ≥ 3, and CPR performed in a prehospital setting. Exclusion criteria were burn injury, AIS score of 6 in any region, and missing data. Estimated survival rate and risk ratio for survival were analyzed according to transport time for all patients. Analysis was also performed separately on patients with sustained TCA at arrival.ResultsOf 292,027 patients in the database, 5336 were included in the study with 4141 sustained TCA. Their median age was 53 years (interquartile range (IQR) 36–70), and 67.2% were male. Their median Injury Severity Score was 29 (IQR 22–41), and median transport time was 11 min (IQR 6–17). Overall survival after TCA was 4.5%; however, survival of patients with sustained TCA at arrival was only 1.2%. The estimated survival rate and risk ratio for sustained TCA rapidly decreased after 15 min of transport time, with estimated survival falling below 1%.ConclusionThe chances of survival for sustained TCA declined rapidly while the patient is transported with CPR support. Time should be one reasonable factor for considering termination of resuscitation in patients with sustained TCA, although clinical signs of life, and type and severity of trauma should be taken into account clinically.

Dutch trauma system performance: Are injured patients treated at the right place?

BackgroundThe goal of trauma systems is to match patient care needs to the capabilities of the receiving centre. Severely injured patients have shown better outcomes if treated in a major trauma centre (MTC). We aimed to evaluate patient distribution in the Dutch trauma system. Furthermore, we sought to identify factors associated with the undertriage and transport of severely injured patients (Injury Severity Score (ISS) >15) to the MTC by emergency medical services (EMS). MethodsData on all acute trauma admissions in the Netherlands (2015-2016) were extracted from the Dutch national trauma registry. An ambulance driving time model was applied to calculate MTC transport times and transport times of ISS >15 patients to the closest MTC and non-MTC. A multivariable logistic regression analysis was performed to identify factors associated with ISS >15 patients’ EMS undertriage to an MTC. ResultsOf the annual average of 78,123 acute trauma admissions, 4.9% had an ISS >15. The nonseverely injured patients were predominantly treated at non-MTCs (79.2%), and 65.4% of patients with an ISS >15 received primary MTC care. This rate varied across the eleven Dutch trauma networks (36.8%-88.4%) and was correlated with the transport times to an MTC (Pearson correlation -0.753, p=0.007). The trauma networks also differed in the rates of secondary transfers of ISS >15 patients to MTC hospitals (7.8% - 59.3%) and definitive MTC care (43.6% - 93.2%). Factors associated with EMS undertriage of ISS >15 patients to the MTC were female sex, older age, severe thoracic and abdominal injury, and longer additional EMS transport times. ConclusionsApproximately one-third of all severely injured patients in the Netherlands are not initially treated at an MTC. Special attention needs to be directed to identifying patient groups with a high risk of undertriage. Furthermore, resources to overcome longer transport times to an MTC, including the availability of ambulance and helicopter services, may improve direct MTC care and result in a decrease in the variation of the undertriage of severely injured patients to MTCs among the Dutch trauma networks. Furthermore, attention needs to be directed to improving primary triage guidelines and instituting uniform interfacility transfer agreements.

EMS Response Time for Patients Critically-Injured from Automobile Accidents Using Regression Analysis

Background: The ability to quickly and effectively receive medical treatment in the event of an automobile collision is one of the most important aspects in emergency medical services (EMS). Emergency medical service providers are the first to respond and manage cases related to trauma, emergency surgery, and critically injured patients. Response time for emergency medical services vehicles is especially important for areas, where travel distances are often much larger, compared to more urban areas. The importance of the present data and analysis procedures are their applicability to multiple environments, including urban settings. Methods: The present study is focused on optimization of analysis tools, and understanding the influences of different traffic-related variables, related to hospital EMS transport times for Pickens County, a county in west Alabama. Optimization of associated analysis tools is important for optimal trauma patient survivability, and as such, is directly relevant to the management of care for severely injured surgical patients. Of particular interest are the effects of variables, such as travel time, time of the day, day of the week, weather, lighting conditions, and crash severity, on the EMS response time (ERT), which are analyzed using two types of advanced regression analysis: geographically weighted regression (GWR) and global regression analysis (GRA). Results: For GWR analysis, the accuracy of the approach is improved by employing an adaptive bi-square kernel weighting function. The GWR approach is also unique because geographic location variations are quantified for local independent variables, as their effects are included. Magnitudes of variable coefficients, and variable t-statistic values provide information on the relative influences and impacts of different variables, and different variable combinations, as they are considered in pairs, triplets, and different combinations. Conclusion: The resulting effects and alterations to optimal EMS response time are provided for a wide range of travel conditions and travel time periods.

Geographic Coverage and Verification of Trauma Centers in a Rural State: Highlighting the Utility of Location Allocationfor Trauma System Planning

Care at verified trauma centers has improved survival and functional outcomes, yet determining the appropriate location of potential trauma centers is often driven by factors other than optimizing system-level patient care. Given the importance of transport time in trauma, we analyzed trauma transport patterns in a rural state lacking an organized trauma system and implemented a geographic information system to inform potential future trauma center locations. Data were collected on trauma ground transport during a 3-year period (2014 through 2016) from the Statewide Incident Reporting Network database. Geographic information system mapping and location-allocation modeling of the best-fit facility for trauma center verification was computed using trauma transport patterns, population density, road network layout, and 60-minute emergency medical services transport time based on current transport protocols. Location-allocation modeling identified 2 regional facilities positioned to become the next verified trauma centers. The proportion of the Vermont population without access to trauma center care within 60 minutes would be reduced from the current 29.68% to 5.81% if the identified facilities become verified centers. Through geospatial mapping and location-allocation modeling, we were able to identify gaps and suggest optimal trauma center locations to maximize population coverage in a rural state lacking a formal, organized trauma system. These findings could inform future decision-making for targeted capacity improvement and system design that emphasizes more equitable access to trauma center care in Vermont.

Early administration of steroids in the ambulance setting: Protocol for a type I hybrid effectiveness-implementation trial with a stepped wedge design

BackgroundPediatric asthma exacerbations are a frequent reason for emergency care. Early administration of oral systemic corticosteroids (OCS) in the emergency department (ED) decreases hospitalization rates and ED length-of-stay (LOS). However, it is unknown whether even earlier OCS administration by emergency medical services (EMS) in the prehospital setting further improves outcomes. PurposeTo describe the background and methods of a type 1 hybrid effectiveness-implementation trial of EMS-administered OCS for pediatric asthma patients incorporating a stepped wedge design and the RE-AIM framework. MethodsThe study employs a non-randomized stepped wedge design where multiple EMS agencies adopt OCS as a treatment for pediatric asthma exacerbations at varying times. This design accommodates ethical considerations of studying pediatric subjects in the prehospital setting where informed consent is not feasible. We will compare hospitalization rates, ED LOS, and short-term healthcare costs between pediatric asthma patients who do and do not receive OCS from EMS. Using geographic information systems (GIS), we will measure how differences in outcomes scale with increasing EMS transport time. We will use the RE-AIM framework to guide a mixed methods analysis of barriers and enablers to EMS administration of OCS for pediatric asthma patients, including quantitative measures of adoption and uptake and qualitative EMS provider focus group data. ConclusionThis trial will determine if earlier EMS administration of OCS to pediatric asthma patients decreases hospitalizations, ED LOS, and short-term healthcare costs, and if those outcomes scale with longer EMS transport times. We will identify barriers and enablers to implementing EMS-administered OCS for pediatric asthma patients.

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

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

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.

Abstract TP256: Ems Run Times by Weekday vs. Weekend For Stroke Patients in San Diego County

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 &lt; 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 &lt; 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.

A Statewide Analysis of EMS’ Pediatric Transport Destination Decisions

Introduction: Deciding where to transport a patient is a key decision made by emergency medical services (EMS), particularly for children because pediatric hospital resources are regionalized. Since evidence-based guidelines for pediatric transport destinations are being developed, the purpose of this study was to use a large statewide EMS database to describe current patterns of EMS providers’ transport destination decisions for pediatric patients.Methods: This is a retrospective study of pediatric transports from 2011-2016 in EMS Tracking and Reporting System (EMSTARS), Florida’s statewide EMS database. We included patients greater than 1 day and less than or equal to 18 years who were primary EMS scene transports. Our primary outcome variable was ‘reason for choosing destination.’ We performed descriptive and comparative analysis between closest facility and all other ‘reason for choosing destination’ choices. We used geospatial analysis to examine destination choice in urban and rural counties.Results: Our final study sample was 446,274, and 48.2% of patients had closest facility as their ‘reason for choosing destination.’ The next largest category was patient/family choice (154,035 patients, 35.7%). Closest facility patients were older (median age 12 versus 10 years, p < 0.0001) and had shorter median EMS transport times (11.3 versus 15 minutes, p < 0.0001) compared to all other destination decisions. Notably, 60% of respiratory distress patients’ and 44% of seizure patients’ reason for choosing destination was something other than closest facility. Geospatial analysis revealed that fewer rural patients were documented as closest facility compared to urban (43.9% versus 47%, p < 0.0001). Correspondingly, more rural patients’ destination decision was patient/family choice than urban patients (36.3% versus 34.3%, p < 0.0001).Conclusions: This large, statewide study describes EMS’ reason for choosing destination for pediatric patients. We found that just under half of patients were documented as closest facility, and over one-third as patient/family choice. Significant differences in destination reasons were noted for rural versus urban counties. This study can help those currently developing pediatric EMS destination guidelines by revealing a high proportion of patient/family choice and identifying conditions with high proportions of destination reasons other than closest facility.

Emergency Medical Services Time Intervals for Acute Chest Pain in the United States, 2015–2016

Background: Chest pain is a leading complaint in emergency settings. Timely emergency medical services (EMS) responses can reduce delays to treatment and improve clinical outcomes for acute myocardial infarction patients and other medical emergencies. We investigated national-level EMS response, scene, and transport times for acute chest pain patients in the United States. Methods: A retrospective analysis was performed using 2015–2016 data from the National EMS Information System (NEMSIS). Eligible patients were identified as having a provider impression of chest pain or discomfort and not due to trauma or resulting in cardiac arrest during EMS care. Descriptive analyses of prehospital time intervals and patient-, response-, and system-level covariates were performed. Multivariable logistic regression was used to measure associations between meeting response and scene time benchmarks (8-min and 15-min, respectively) and covariates. Results: Our study identified 1,672,893 eligible EMS encounters of chest pain. Patients had a mean age of 63.1 years (SD = 14.8). The population was evenly distributed by sex (51% male; 49% female). Most encounters occurred in home or residence (58%) and had lights and sirens response to scene (84%). Most encounters were in urban areas (78%). The median (interquartile range, IQR) response time was 7 (5–10) minutes. The median (IQR) scene time was 16 (12–20) minutes. The median (IQR) transport time was 13 (8–20) minutes. Generally, median response and transport times were longer in rural and frontier areas compared to urban and suburban areas. Only 65% and 49% met the 8-min response and 15-min scene time benchmarks. Responding with lights and sirens was associated with greater compliance with EMS response time benchmark. EMS care of older age groups and females was less likely to meet the scene time benchmark. Conclusions: Substantial proportions of EMS encounters for chest pain did not meet response and scene time benchmarks. Regional and urban-rural differences were observed in adherence with the response time benchmark. Our findings also suggest age and gender disparities in on-scene delays by EMS. Our study contributes important evidence on timely EMS responses for cardiac chest pain and provides suggestions for EMS system benchmarking and quality improvement.

Emergency Medical Services Bypass of the Closest Facility for Pediatric Patients

Objectives: Pediatric specialty care is increasingly regionalized. It is unknown how regionalization affects emergency medical services (EMS) providers’ destination decisions for non-trauma pediatric patients. We sought to characterize the rates of bypass of the closest facility, and destination facilities’ levels of pediatric care in three diverse EMS agencies.Methods: This is a one-year retrospective study of non-trauma pediatric patients less than 18 years of age transported by three EMS agencies (Baltimore City, Prince George’s County, and Queen Anne’s County) in 2016. A priori, a bypass was defined as transport to a facility more than 2 km farther than the distance to the closest facility. We calculated rates of bypass and categorized destination and closest facilities by their pediatric service availability using publicly available information. EMS transport distance and time were also compared for bypass and closest facility patients.Results: The three EMS agencies in 2016 transported a total of 12,258 non-trauma pediatric patients, of whom 11,945 (97%) were successfully geocoded. Overall 43% (n = 5,087) of patients bypassed the nearest facility, of which 87% (n = 4,439) were transported to a facility with higher-level pediatric care than the closest facility. Both bypass rates and destination facility pediatric levels differed between agencies. Bypasses had significantly longer transport times and distances as compared to closest facility transports (p < 0.001). For non-trauma pediatric bypasses alone, an additional 41,494 kilometers traveled, and 979 hours of EMS transport time was attributable to bypassing the closest facility.Conclusions: This study reveals a high rate of pediatric bypass for non-trauma patients in three diverse EMS agencies. Bypass results in increased EMS resource utilization through longer transport time and distance. For non-trauma pediatric patients for whom there is little destination guidance, further work is required to determine bypass’ effects on patient outcomes.

Injury Severity Score alone predicts mortality when compared to EMS scene time and transport time for motor vehicle trauma patients who arrive alive to hospital

ABSTRACTObjective: This study aims to identify the association, if any, between prehospital scene time, prehospital transport time, and Injury Severity Score (ISS) with in-hospital mortality.Methods: A retrospective analysis was performed on patients at least 18 years of age who arrived to the hospital alive via emergency medical services (EMS) after a motor vehicle collision (MVC) between 1992 and 2016. These patients were divided into groups based on minutes spent at the scene and in transport. The ISS of the in-hospital mortalities, as well as the entire patient sample for each time frame, was collected. Patients without documented scene time, transport time, or ISS were excluded.Results: Four thousand one hundred ninety-four patients were captured when analyzing scene time, though only 3,980 met inclusion criteria. In addition, 4,177 patients were captured when analyzing transport time, though only 3,979 met inclusion criteria. Scene time and transport time were not statistically significant predictors of in-hospital mortality (P = .31 and P = .458, respectively). ISS was found to be a statistically significant predictor of in-hospital mortality (P < .001).Conclusions: ISS predicts mortality independent of scene time or transport time for patients who arrive to the hospital alive following an MVC at Guthrie Robert Packer Hospital. Limitations of our study include inability to capture prehospital deaths and inability to correlate ISS with prehospital injury severity scores.

Outcomes After Pediatric Out-of-Hospital Cardiopulmonary Interventions.

The aim of the study was to evaluate outcomes after pediatric out-of-hospital cardiopulmonary interventions (CPIs) by emergency medical services (EMS). Children (age, ≤18 years) who received CPI by EMS from 2001 to 2008 were identified from the Utah Department of Health. Cardiopulmonary intervention was defined as oxygenation, ventilation or CPR, and transport to a hospital by EMS. Univariate and multivariable regression analyses evaluated associations between potential predictors and outcomes (death and new neurologic dysfunction). A total of 464 patients (58% male) received EMS attention. For the 71% patients (327) who were alive on EMS arrival, 63% (205) received CPI without CPR. Of note, 6% (12) of these patients died after arrival to the hospital and new neurologic dysfunction was diagnosed in 6% (13). Among the 12 patients who died, 50% (6) were younger than 1 year.On multivariable regression analysis, factors associated with increased risk of death before and in-hospital are the following: age younger than 1 year (odds ratio [OR], 0.26; 95% confidence interval [CI], 0.17-0.39), shorter EMS transport time (OR, 0.94; 95% CI, 0.89-0.99), and longer EMS dispatch time (OR, 1.23; 95% CI, 1.08-1.40). Factors associated with increased risk of new neurologic dysfunction are the following: lack of pulse (OR, 0.14; 95% CI, 0.04-0.53), requiring CPR (OR, 6.15; 95% CI, 1.48-25.6), and CPR duration (OR, 1.20; 95% CI, 1.05-1.37). Age younger than 1 year, shorter transport time, and longer dispatch time were associated with increased risk of death. Being pulseless upon discovery and receiving CPR were associated with new neurologic dysfunction. Maximizing EMS transport interventions for patients younger than 1 year requiring CPI may improve patient outcomes.

Regional "Call 911" Emergency Department Protocol to Reduce Interfacility Transfer Delay for Patients With ST-Segment-Elevation Myocardial Infarction.

BackgroundWe evaluated the first‐medical‐contact‐to‐balloon (FMC2B) time after implementation of a “Call 911” protocol for ST‐segment–elevation myocardial infarction (STEMI) interfacility transfers in a regional system.Methods and ResultsThis is a retrospective cohort study of consecutive patients with STEMI requiring interfacility transfer from a STEMI referring hospital, to one of 35 percutaneous coronary intervention‐capable STEMI receiving centers (SRCs). The Call 911 protocol allows the referring physician to activate 911 to transport a patient with STEMI to the nearest SRC for primary percutaneous coronary intervention. Patients with interfacility transfers were identified over a 4‐year period (2011–2014) from a registry to which SRCs report treatment and outcomes for all patients with STEMI transported via 911. The primary outcomes were median FMC2B time and the proportion of patients achieving the 120‐minute goal. FMC2B for primary 911 transports were calculated to serve as a system reference. There were 2471 patients with STEMI transferred to SRCs by 911 transport during the study period, of whom 1942 (79%) had emergent coronary angiography and 1410 (73%) received percutaneous coronary intervention. The median age was 61 years (interquartile range [IQR] 52–71) and 73% were men. The median FMC2B time was 111 minutes (IQR 88–153) with 56% of patients meeting the 120‐minute goal. The median STEMI referring hospital door‐in‐door‐out time was 53 minutes (IQR 37–89), emergency medical services transport time was 9 minutes (IQR 7–12), and SRC door‐to‐balloon time was 44 minutes (IQR 32–60). For primary 911 patients (N=4827), the median FMC2B time was 81 minutes (IQR 67–97).ConclusionsUsing a Call 911 protocol in this regional cardiac care system, patients with STEMI requiring interfacility transfers had a median FMC2B time of 111 minutes, with 56% meeting the 120‐minute goal.

911 Emergency Medical Services and Re-Triage to Level I Trauma Centers

Interfacility transfer of undertriaged patients to higher-level trauma centers has been found to result in a delay of appropriate care and an increase in mortality. To address this, for the last 10 years our region has used 911 emergency medical services (EMS) paramedics for rapid re-triage of undertriaged patients to our institution's Level I trauma center. We sought to determine whether using 911 EMS for re-triage to our institution was associated with worse outcomes-with mortality as the primary end point-compared with direct EMS transport from point of injury. We retrospectively reviewed all trauma activations to our institution during a 16-month period; 3,394 active traumas were analyzed. Two hundred and seventy patients (8%) arrived via 911 EMS re-triage and 3,124 (92%) arrived via direct EMS transport. Total EMS transport time was significantly longer (122.5 minutes vs 33.7 minutes; p < 0.001) between the 2 groups, but there was no significant difference in mortality rates (4.1% vs 3.6%; p= 0.67). These data show that although using 911 EMS for re-triage is associated with an increase in total transport time, it does not result in an increase in mortality compared with direct EMS transport. We conclude that the use of 911 EMS can be considered a safe method to re-triage patients to higher-level trauma centers.