Emergency Medical Services Scene Research Articles

Examination of disparities in prehospital encounters for pediatric asthma exacerbations.

There are disparities in multiple aspects of pediatric asthma care; however, prehospital care disparities are largely undescribed. This study's objective was to examine racial and geographic disparities in emergency medical services (EMS) medication administration to pediatric patients with asthma. This is a substudy of the Early Administration of Steroids in the Ambulance Setting: An Observational Design Trial, which includes data from pediatric asthma patients ages 2-18 years. We examined rates of EMS administration of systemic corticosteroids and inhaled bronchodilators by patient race. We geocoded EMS scene addresses, characterized the locations' neighborhood-based conditions and resources relevant to children using the Child Opportunity Index (COI) 2.0, and analyzed associations between EMS scene address COI with medications administered by EMS. A total of 765 patients had available racial data and 825 had scene addresses that were geocoded to a COI. EMS administered at least 1 bronchodilator to 84.7% (n=492) of non-White patients and 83.2% of White patients (n=153), P=0.6. EMS administered a systemic corticosteroid to 19.4% (n=113) of non-White patients and 20.1% (n=37) of White patients, P=0.8. There was a significant difference in bronchodilator administration between COI categories of low/very low versus moderate/high/very high (85.0%, n=485vs. 75.9%, n=192, respectively, P=0.003). There were no racial differences in EMS administration of medications to pediatric asthma patients. However, there were significantly higher rates of EMS bronchodilator administration for encounters in low/very low COIs. That latter finding may reflect inequities in asthma exacerbation severity for patients living in disadvantaged areas.

Retrospective Study of EMS Scene Times and Mortality in Penetrating Trauma Patients: Improving Transport Standards and Patient Outcomes.

This study aimed to determine the impact of emergency medical service (EMS) scene time variability on adult and pediatric trauma patient outcomes with moderate or severe penetrating injuries. This retrospective study analyzed the American College of Surgeons (ACS) Trauma Quality Improvement Program (TQIP) database between 2017 and 2020 to evaluate the relationship between EMS scene time on adult and pediatric patients with moderate to severe injuries. Primary outcomes included Dead on Arrival (DOA) to the Emergency Department (ED), ED mortality, 24-hour mortality, and in-hospital mortality. Multivariable logistic regression models were used to examine the association of each EMS scene time category and mortality. Adult patients with 10-30minutes of EMS scene time had increased odds of experiencing ED mortality, 24-hour mortality, and in-hospital mortality. Adults with >30minutes of EMS scene time were more likely to be DOA to the ED. There was no significant association with mortality for patients with <10minutes of EMS scene time. In the pediatric subset of patients, those with 10-30minutes of EMS scene time were more likely to experience ED mortality and in-hospital mortality. EMS scene times less than 10minutes were associated with the greatest odds of survival, supporting the "load and go" theory for penetrating trauma. Our study suggests that even an EMS scene time of 10-30minutes results in a significantly increased risk of mortality, and further efforts are needed to improve scene time through improved EMS and hospital policies.

Disparities in Survival Outcomes of Out-of-Hospital Cardiac Arrest Patients between Urban and Rural Areas and the Identification of Modifiable Factors in an Area of South Korea

This retrospective study aimed to compare the survival outcomes of adult out-of-hospital cardiac arrest (OHCA) patients between urban (Busan, Ulsan, Changwon) and rural (Gyeongnam) areas in South Korea and identify modifiable factors in the chain of survival. The primary and secondary outcomes were survival to discharge and modifiable factors in the chain of survival were identified using logistic regression analysis. In total, 1954 patients were analyzed. The survival to discharge rates in the whole region and in urban and rural areas were 6.9%, 8.7% (Busan 8.7%, Ulsan 10.3%, Changwon 7.2%), and 3.4%, respectively. In the urban group, modifiable factors associated with survival to discharge were no advanced airway management (adjusted odds ratio (aOR) 2.065, 95% confidence interval (CI): 1.138–3.747), no mechanical chest compression (aOR 3.932, 95% CI: 2.015–7.674), and an emergency medical service (EMS) transport time of more than 8 min (aOR 3.521, 95% CI: 2.075–5.975). In the rural group, modifiable factors included an EMS scene time of more than 15 min (aOR 0.076, 95% CI: 0.006–0.883) and an EMS transport time of more than 8 min (aOR 4.741, 95% CI: 1.035–21.706). To improve survival outcomes, dedicated resources and attention to EMS practices and transport time in urban areas and EMS scene and transport times in rural areas are needed.

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.

Effect of Prehospital Epinephrine Use on Survival from Out-of-Hospital Cardiac Arrest and on Emergency Medical Services.

This study was to identify the effect of epinephrine on the survival of out-of-hospital cardiac arrest (OHCA) patients and changes in prehospital emergency medical services (EMSs) after the introduction of prehospital epinephrine use by EMS providers. This was a retrospective observational study comparing two groups (epinephrine group and norepinephrine group). We used propensity score matching of the two groups and identified the association between outcome variables regarding survival and epinephrine use, controlling for confounding factors. The epinephrine group was 339 patients of a total 1943 study population. The survival-to-discharge rate and OR (95% CI) of the epinephrine group were 5.0% (p = 0.215) and 0.72 (0.43–1.21) in the total patient population and 4.7% (p = 0.699) and 1.15 (0.55–2.43) in the 1:1 propensity-matched population. The epinephrine group received more mechanical chest compression and had longer EMS response times and scene times than the norepinephrine group. Mechanical chest compression was a negative prognostic factor for survival to discharge and favorable neurological outcomes in the epinephrine group. The introduction of prehospital epinephrine use in OHCA patients yielded no evidence of improvement in survival to discharge and favorable neurological outcomes and adversely affected the practice of EMS providers, exacerbating the factors negatively associated with survival from OHCA.

Use of Time-to-Event Analysis to Develop On-Scene Return of Spontaneous Circulation Prediction for Out-of-Hospital Cardiac Arrest Patients

We aimed to train and validate the time to on-scene return of spontaneous circulation prediction models using time-to-event analysis among out-of-hospital cardiac arrest patients. Using a Korean population-based out-of-hospital cardiac arrest registry, we selected a total of 105,215 adults with presumed cardiac etiologies between 2013 and 2018. Patients from 2013 to 2017 and from 2018 were analyzed for training and test, respectively. We developed 4 time-to-event analyzing models (Cox proportional hazard [Cox], random survival forest, extreme gradient boosting survival, and DeepHit) and 4 classification models (logistic regression, random forest, extreme gradient boosting, and feedforward neural network). Patient characteristics and Utstein elements collected at the scene were used as predictors. Discrimination and calibration were evaluated by Harrell's C-index and integrated Brier score. Among the 105,215 patients (mean age 70 years and 64% men), 86,314 and 18,901 patients belonged to the training and test sets, respectively. On-scene return of spontaneous circulation was achieved in 5,240 (6.1%) patients in the former set and 1,709 (9.0%) patients in the latter. The proportion of emergency medical services (EMS) management was higher and scene time interval longer in the latter. Median time from EMS scene arrival to on-scene return of spontaneous circulation was 8 minutes for both datasets. Classification models showed similar discrimination and poor calibration power compared to survival models; Cox showed high discrimination with the best calibration (C-index [95% confidence interval]: 0.873 [0.865 to 0.882]; integrated Brier score at 30 minutes: 0.060). Incorporating time-to-event analysis could lead to improved performance in prediction models and contribute to personalized field EMS resuscitation decisions.

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.

Most of the Variation in Prehospital Scene Time Is Not Related to Patient Factors, Injury Characteristics, or Geography

ObjectiveThe time spent on scene by emergency medical services remains highly variable. We sought to investigate how much of the prehospital scene time variation in penetrating trauma patients could be explained by prehospital factors. MethodsUsing the 2010 to 2016 Trauma Quality and Improvement database, all adult penetrating trauma patients were included. The prehospital scene time was defined as the time from emergency medical service scene arrival to departure. Using all Trauma Quality and Improvement database variables including patient, injury (eg, Injury Severity Score), geography, and logistical (eg, transport mode) factors, multivariable linear regression models were created to predict the prehospital scene time. The prehospital scene time was treated as a continuous variable, and the degree to which the models could explain the variation in scene time was measured using the coefficient of determination (R). ResultsA total of 45,560 patients were included. The median prehospital scene time was 6 minutes (interquartile range, 3-10 minutes). The R for factors in the multivariable regression model was 0.06, suggesting that 94% of the prehospital scene time variation cannot be explained by the wide range of prehospital factors. ConclusionMost of the variation in prehospital scene time cannot be explained by injury characteristics. The variation may be caused by logistical delays or system-related factors.

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 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.

Cervical Spine Injury Risk Factors in Children With Blunt Trauma.

Adult prediction rules for cervical spine injury (CSI) exist; however, pediatric rules do not. Our objectives were to determine test accuracies of retrospectively identified CSI risk factors in a prospective pediatric cohort and compare them to a de novo risk model. We conducted a 4-center, prospective observational study of children 0 to 17 years old who experienced blunt trauma and underwent emergency medical services scene response, trauma evaluation, and/or cervical imaging. Emergency department providers recorded CSI risk factors. CSIs were classified by reviewing imaging, consultations, and/or telephone follow-up. We calculated bivariable relative risks, multivariable odds ratios, and test characteristics for the retrospective risk model and a de novo model. Of 4091 enrolled children, 74 (1.8%) had CSIs. Fourteen factors had bivariable associations with CSIs: diving, axial load, clotheslining, loss of consciousness, neck pain, inability to move neck, altered mental status, signs of basilar skull fracture, torso injury, thoracic injury, intubation, respiratory distress, decreased oxygen saturation, and neurologic deficits. The retrospective model (high-risk motor vehicle crash, diving, predisposing condition, neck pain, decreased neck mobility (report or exam), altered mental status, neurologic deficits, or torso injury) was 90.5% (95% confidence interval: 83.9%-97.2%) sensitive and 45.6% (44.0%-47.1%) specific for CSIs. The de novo model (diving, axial load, neck pain, inability to move neck, altered mental status, intubation, or respiratory distress) was 92.0% (85.7%-98.1%) sensitive and 50.3% (48.7%-51.8%) specific. Our findings support previously identified pediatric CSI risk factors and prospective pediatric CSI prediction rule development.

Characteristics of Neighborhoods Where Emergency Medical Services Encounter Children at Risk for Maltreatment

Objective: The objective of this study was to determine if neighborhood rates of pediatric Emergency Medical Services (EMS) encounters correlate with rates of child maltreatment reporting and if there are neighborhood-level risk factors for EMS encountering children with maltreatment reports. Methods: We conducted a retrospective cohort study using the electronic medical records of children ages <18 years who had Columbus Division of Fire EMS encounters between 2011 and 2015. We used Nationwide Children’s Hospital electronic medical records to identify child maltreatment reports. The EMS scene addresses and home addresses associated with maltreatment reports were geocoded independently and rates for each Census tract were calculated. The maltreatment reports were matched to the EMS encounters using name, gender, and date of birth. Rates of EMS encounters with children that had a maltreatment report were calculated for each Census tract. Census tract demographic information was obtained from the American Community Survey. Bayesian conditional autoregressive Poisson models were used to calculate rate ratios for census tract variables to determine their relationship to EMS encountering children with maltreatment reports. Results: A total of 44,002 EMS encounters and 4,298 maltreatment reports were included in the study. The Spearman correlation coefficient relating rates of EMS encounters to rates of maltreatment reports within census tracts was 0.72 (95% confidence interval, 0.65–0.77). Within the study period, a total of 1,134 EMS encounters were linked to 578 children with maltreatment reports. Poverty was the only independent risk factor for EMS encountering children with maltreatment reports. The multivariate analysis also identified protective factors, which included neighborhoods with higher proportions of residents who had bachelor’s degrees, spoke a language other than English, and had the same residence the previous year. Conclusion: This study showed that in Franklin County, Ohio, neighborhoods with high EMS utilization had a strong positive correlation with areas that had high rates of child maltreatment reports. We also identified four neighborhood characteristics that were independently associated with EMS encountering children at risk for maltreatment (risk factor: poverty; protective factors: residents with college educations, non-English speaking households, and residents maintaining the same residence as the previous year).

Pediatric Behavioral Health-Related EMS Encounters: A Statewide Analysis

Objectives: Pediatric behavioral health disorders and related emergency department visits are increasing, but effects on emergency medical services (EMS) are unknown. This study’s objective was to describe the statewide epidemiology of pediatric behavioral health-related EMS encounters in Florida, including mental health and substance use. Methods: This analysis is a retrospective study of pediatric behavioral health-related EMS encounters from Florida’s statewide EMS Tracking and Reporting Systems Database from 2011 to 2016. Demographic, clinical, EMS, and geographic characteristics are described. We also compared characteristics between patients who did and did not receive an acute EMS behavioral/psychiatric intervention. Results: There were 22,254 pediatric behavioral health-related EMS encounters during the study period, one-quarter of which were noted to have suspected or confirmed ingestion/substance use. The median age was 16 and the majority of patients were female and white. A total of 946 patients (4%) had an acute EMS behavioral/psychiatric intervention. EMS scene, ED turnaround, and total EMS time were significantly longer for intervention patients. Of the 14 counties in the top quartile of percentages of intervention patients, 7 were rural, 10 did not have any hospitals with child/adolescent psychiatric services, and 7 did not have any child psychiatrists. Conclusions: Pediatric behavioral-health related EMS encounters had a significant proportion of suspected ingestions/substance use, and we found disproportionate effects on rural agencies. Increases in EMS resource utilization (including longer EMS times) occurred in certain settings with limited behavioral health infrastructure. Those findings suggest an opportunity for community paramedicine to alleviate EMS utilization and decrease the frequency of pediatric behavioral health emergencies.

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.

Canceled to Be Called Back: A Retrospective Cohort Study of Canceled Helicopter Emergency Medical Service Scene Calls That Are Later Transferred to a Trauma Center

IntroductionIn our trauma system, helicopter emergency medical services (HEMS) can be requested to attend a scene call for an injured patient before arrival by land paramedics. Land paramedics can cancel this response if they deem it unnecessary. The purpose of this study is to describe the frequency of canceled HEMS scene calls that were subsequently transferred to 2 trauma centers and to assess for any impact on morbidity and mortality. MethodsProbabilistic matching was used to identify canceled HEMS scene call patients who were later transported to 2 trauma centers over a 48-month period. Registry data were used to compare canceled scene call patients with direct from scene patients. ResultsThere were 290 requests for HEMS scene calls, of which 35.2% were canceled. Of those canceled, 24.5% were later transported to our trauma centers. Canceled scene call patients were more likely to be older and to be discharged home from the trauma center without being admitted. ConclusionThere is a significant amount of undertriage of patients for whom an HEMS response was canceled and later transported to a trauma center. These patients face similar morbidity and mortality as patients who are brought directly from scene to a trauma center.

Epidemiology of EMS Responses to Traffic Crashes in the United States for 2014

Background In 2014, there were 6.1 million crashes, resulting in 32,675 fatalities, 2.3 million injured persons, and comprehensive costs of an estimated 836 billion. Reductions in traffic crash fatalities and associated injuries require a comprehensive traffic safety approach that includes emergency medical services (EMS). This study aimed to characterize the EMS response to traffic crashes for the United States in 2014 and examine associations with geographic and socioeconomic factors. Methods Using the 2014 National EMS Database, this study analyzed data from 12 states that had 100% of EMS agencies reporting. Descriptive analyses characterized the EMS response to traffic crashes by time of day, day of week, patient demographics, and urbanicity. Traffic crash incident location zip code was used to link several zip code level socioeconomic variables from the 2010–2014 American Community Survey to each EMS record. Socioeconomic variables were categorized by a quintile distribution. A logistic model was used to determine likelihood estimates between patient demographics and zip-code level socioeconomic variables, with EMS system time, delays, and provider level of service. Results In total there were 288,202 9-1-1 EMS activations dispatched to a traffic crash identified in the 2014 National EMS Database. Activations were concentrated in urban areas (70%) and the majority occurred between the hours of noon and 6 pm (38%). Delays were associated with patient ethnicity and multiple zip code level socioeconomic measures. As the median household income of the zip code crash site decreased, the likelihood of having any EMS delay increased. As the percent of the uninsured population increased, the likelihood of having any EMS delay increased. Patients identified as Hispanic or Latino were two times more likely to have a response and transport delay. American Indians/Alaskan Natives had higher odds of experiencing response delays (OR=1.8), scene delays (OR=1.5), and transport delays (OR =1.9) than any other racial or ethnic group in comparison to Whites. Conclusions Income and racial disparities exist for EMS provider-reported response, scene, and transport delays for traffic crash patients. By identifying disparities, EMS systems should collaborate with public health and traffic safety professionals to develop strategies that decrease gaps in EMS response and service, thereby improving traffic crash mortality and morbidity.

Evaluation of the Implementation of the Trauma Triage and Destination Plan on the Field Triage of Injured Patients in North Carolina

Objective: Timely triage and appropriate destination decision making for injured patients are central challenges faced by emergency medical services (EMS) systems. In 2010, North Carolina (NC) adopted a statewide Trauma Triage and Destination Plan (TTDP) based on the CDC's Field Triage Guidelines to better address these challenges. We sought to characterize the implementation of these guidelines by quantifying their effect on multiple metrics of patient care. Methods: We employed a retrospective pre-post study design utilizing a statewide EMS medical record database. We assessed several metrics of patient care—including changes in destination choice, appropriateness of EMS destination, transit time to first hospital, transit time to definitive care, and others—in a six-month period in the year before and after the implementation of the guidelines. Results: We evaluated a total of 190,307 EMS encounters pre- (n = 93,927) and post-implementation (n = 96,380). Among all patients, there was not a significant difference in the percentage transported to a community hospital or Level I, II, or III trauma center as their first destination. Among those patients meeting TTDP guidelines for transport to a trauma center, the number transported to a Level I or II trauma center decreased 1.0% from 30.6% (n = 2,911) to 29.6% (n = 2,954) (95% CI: −0.2%, 2.2%). Those transported to a Level I trauma center decreased 0.4% from 21.2% to 20.8% in the post-period (95% CI: −0.7%, 1.5%). There were also no significant changes in EMS scene times (14.0 pre-, 14.1 post-) and transport times (12.9 pre-, 13.0 post-). While scene distance from a Level I trauma center showed a decreased likelihood of transport to that center, there was an overall post-implementation increase of 2.5% from 18.0% to 20.5% (95% CI: −3.6%, −1.3%) in transport to a Level I trauma center among patients meeting anatomic criteria across all distance ranges. Conclusions: We found that implementation of region-specific destination plans based on the Field Triage Guidelines had little effect on selected hospital destination, scene times, transport times, and other metrics of EMS decision making and effectiveness. We suspect this is due to delays in information dissemination and adoption by field providers.

Methods for Collecting Paired Observations From Emergency Medical Services and Emergency Department Providers for Pediatric Cervical Spine Injury Risk Factors.

Cervical spine injuries (CSIs) after blunt trauma in children are rare, but cause substantial morbidity and mortality. Emergency medical services (EMS) and emergency department (ED) providers routinely use spinal precautions and cervical spine imaging, respectively, during the management of children experiencing blunt trauma. These practices lack evidence, and there is concern that they may be harmful. A pediatric CSI risk assessment tool is needed to inform EMS and ED provider decision making. Creating this tool requires prospective data collection from EMS and ED providers at the time of patient evaluation. The purpose of this article is to describe the methods used to prospectively capture paired EMS and ED provider observations of children cared for after blunt trauma. Given the rarity of prospective observational research with EMS, the novel use of Research Electronic Data Capture (REDCap) in this study, and the potential to inform future studies, we are publishing our methodology in advance of outcome data related to the risk assessment tool. The study was conducted at four tertiary children's hospitals as a prerequisite for a planned larger study to derive a CSI risk assessment tool. We created a web-based, branch-logic questionnaire using the REDCap data collection system. The survey was administered via tablet computer to ED providers evaluating children with blunt trauma and, if applicable, to EMS providers who provided patient care at the scene. We collected information regarding factors determined a priori to be plausibly associated with CSI in children. Eligible children presenting to the ED after blunt trauma with at least one of the following one of the following were included: prehospital EMS spinal precautions, ED trauma team evaluation, or cervical spine imaging in the ED. Exclusions included penetrating trauma, language barrier, or state's custody. Enrollment occurred when research coordinators (RCs) were available, generally 12-16 hours/day. RCs approached EMS providers prior to departing the ED and ED providers after they completed their patient assessments. An ED provider survey was required for enrollment. Enrolled children were followed for 28 days to determine the presence of CSI (primary outcome) by subsequent imaging or by patient/family telephone follow-up for those without imaging. Over 18 months, we prospectively enrolled 4,144 of 5,764 (71.9%) eligible children, including 74 of 110 (67.3%) children diagnosed with CSI. Enrollment during RC hours was 85.9%. Fifty-three enrolled children were withdrawn from the study. Of those in the final study cohort, 36.5% arrived by EMS scene response in spinal precautions. The remaining 63.5% arrived by EMS scene response without spinal precautions or by private vehicle or interfacility transfer. EMS scene response providers completed surveys for 60.2% of enrolled children arriving in spinal precautions. RCs missed the EMS providers for 37.1% of children; however, EMS declined participation for only 2.6%. Our method of data collection demonstrates the ability to prospectively capture paired observations from EMS and ED personnel for children undergoing evaluation after blunt trauma. While this methodology will be used to implement and evaluate a CSI tool in future studies, it may also be adapted to studies requiring prospective data collection from EMS and ED personnel.