Racial, Ethnic, and Socioeconomic Disparities in Out-of-Hospital Pain Management for Patients With Long Bone Fractures.

STUDY OBJECTIVE: To evaluate racial and ethnic disparities in out-of-hospital analgesic administration, accounting for the influence of clinical characteristics and community socioeconomic vulnerability, among a national cohort of patients with long bone fractures. METHODS: Using the 2019-2020 ESO Data Collaborative, we retrospectively analyzed emergency medical services (EMS) records for 9-1-1 advanced life support transport of adult patients diagnosed with long bone fractures at the emergency department. We calculated adjusted odds ratios (aOR) and 95% confidence intervals (CI) for out-of-hospital analgesic administration by race and ethnicity, accounting for age, sex, insurance, fracture location, transport time, pain severity, and scene Social Vulnerability Index. We reviewed a random sample of EMS narratives without analgesic administration to identify whether other clinical factors or patient preferences could explain differences in analgesic administration by race and ethnicity. RESULTS: Among 35,711 patients transported by 400 EMS agencies, 81% were White, non-Hispanic, 10% were Black, non-Hispanic, and 7% were Hispanic. In crude analyses, Black, non-Hispanic patients with severe pain were less likely to receive analgesics compared with White, non-Hispanic patients (59% versus 72%; Risk Difference: -12.5%, 95% CI: -15.8% to -9.9%). After adjustment, Black, non-Hispanic patients remained less likely to receive analgesics compared with White, non-Hispanic patients (aOR:0.65, 95% CI:0.53 to 0.79). Narrative review identified similar rates of patients declining analgesics offered by EMS and analgesic contraindications across racial and ethnic groups. CONCLUSIONS: Among EMS patients with long bone fractures, Black, non-Hispanic patients were substantially less likely to receive out-of-hospital analgesics compared with White, non-Hispanic patients. These disparities were not explained by differences in clinical presentations, patient preferences, or community socioeconomic conditions.

Patient Outcomes Based on the 2011 CDC Guidelines for Field Triage of Injured Patients.

BACKGROUND: The Centers for Disease Control and Prevention Guidelines for Field Triage of Injured Patients drive the destination decision for millions of emergency medical services (EMS)-transported trauma patients annually, yet limited information exists regarding performance and relationship with patient outcomes as a whole. OBJECTIVE: To evaluate the association of positive findings on Centers for Disease Control and Prevention Guidelines for Field Triage of Injured Patients with hospitalization and mortality. METHODS: This retrospective study included all 911 responses from the 2019 ESO Data Collaborative research dataset with complete Centers for Disease Control and Prevention Guidelines for Field Triage of Injured Patients and linked emergency department dispositions, excluding children and cardiac arrests prior to EMS arrival. Patients were categorized by Centers for Disease Control and Prevention Guidelines for Field Triage of Injured Patients step(s) met. Outcomes were hospitalization and emergency department or inhospital mortality. RESULTS: There were 86,462 records included: n = 65,967 (76.3%) met no criteria, n = 16,443 (19.0%) met one step (n = 1,571 [9.6%] vitals, n = 1,030 [6.3%] anatomy of injury, n = 993 [6.0%] mechanism of injury, and n = 12,849 [78.1%] special considerations), and n = 4,052 (4.7%) met multiple. Compared with meeting no criteria, hospitalization odds increased threefold for vitals (odds ratio [OR]: 3.07, 95% confidence interval [CI]: 2.77-3.40), fourfold for anatomy of injury (OR: 3.94, 95% CI: 3.48-4.46), twofold for mechanism of injury (OR: 2.00, 95% CI: 1.74-2.29), or special considerations (OR: 2.46, 95% CI: 2.36-2.56). Hospitalization odds increased ninefold when positive in multiple steps (OR: 8.97, 95% CI: 8.37-9.62). Overall, n = 84,473 (97.7%) had mortality data available, and n = 886 (1.0%) died. When compared with meeting no criteria, mortality odds increased 10-fold when positive in vitals (OR: 9.58, 95% CI: 7.30-12.56), twofold for anatomy of injury (OR: 2.34, 95% CI: 1.28-4.29), or special considerations (OR: 2.10, 95% CI: 1.71-2.60). There was no difference when only positive for mechanism of injury (OR: 0.22, 95% CI: 0.03-1.54). Mortality odds increased 23-fold when positive in multiple steps (OR: 22.7, 95% CI: 19.7-26.8). CONCLUSIONS: Patients meeting multiple Centers for Disease Control and Prevention Guidelines for Field Triage of Injured Patients steps were at greater risk of hospitalization and death. When meeting only one step, anatomy of injury was associated with greater risk of hospitalization; vital sign criteria were associated with greater risk of mortality.

Out-of-Hospital Ketamine: Indications for Use, Patient Outcomes, and Associated Mortality.

STUDY OBJECTIVE: To describe out-of-hospital ketamine use, patient outcomes, and the potential contribution of ketamine to patient death. METHODS: We retrospectively evaluated consecutive occurrences of out-of-hospital ketamine administration from January 1, 2019 to December 31, 2019 reported to the national ESO Data Collaborative (Austin, TX), a consortium of 1,322 emergency medical service agencies distributed throughout the United States. We descriptively assessed indications for ketamine administration, dosing, route, transport disposition, hypoxia, hypercapnia, and mortality. We reviewed cases involving patient death to determine whether ketamine could be excluded as a potential contributing factor. RESULTS: Indications for out-of-hospital ketamine administrations in our 11,291 patients were trauma/pain (49%; n=5,575), altered mental status/behavioral indications (34%; n=3,795), cardiovascular/pulmonary indications (13%; n=1,454), seizure (2%; n=248), and other (2%; n=219). The highest median dose was for altered mental status/behavioral indications at 3.7 mg/kg (interquartile range, 2.2 to 4.4 mg/kg). Over 99% of patients (n=11,274) were transported to a hospital. Following ketamine administration, hypoxia and hypercapnia were documented in 8.4% (n=897) and 17.2% (n=1,311) of patients, respectively. Eight on-scene and 120 in-hospital deaths were reviewed. Ketamine could not be excluded as a contributing factor in 2 on-scene deaths, representing 0.02% (95% confidence interval 0.00% to 0.07%) of those who received out-of-hospital ketamine. Among those with in-hospital data, ketamine could not be excluded as a contributing factor in 6 deaths (0.3%; 95% confidence interval 0.1% to 0.7%). CONCLUSION: In this large sample, out-of-hospital ketamine was administered for a variety of indications. Patient mortality was rare. Ketamine could not be ruled out as a contributing factor in 8 deaths, representing 0.07% of those who received ketamine.

Initial Prehospital Rapid Emergency Medicine Score (REMS) as a Predictor of Patient Outcomes.

Background: A standardized objective measure of prehospital patient risk of hospitalization or death is needed. The Rapid Emergency Medicine Score (REMS), a validated risk-stratification tool, has not been widely tested for prehospital use. This study's objective was to assess predictive characteristics of initial prehospital REMS for ED disposition and overall patient mortality. Methods: This retrospective analysis used linked prehospital and hospital data from the national ESO Data Collaborative. All 911 responses from 1/1/2019-12/31/2019 were included. REMS (0-26) was calculated using age and first prehospital values for: pulse rate, mean arterial pressure, respiratory rate, oxygen saturation, and Glasgow Coma Scale. Non-transports, patients <18 and cardiac arrests prior to EMS arrival were excluded. The primary outcome was ED disposition, dichotomized to discharge versus admission, transfer, or death. The secondary outcome was overall survival to discharge (ED or inpatient). Transfers and records without inpatient disposition were excluded from the secondary analysis. Predictive ability was assessed using area under the receiver operating curve (AUROC). Optimal REMS cut points were determined using test characteristic curves. Univariable logistic regression modeling was used to quantify the association between initial prehospital REMS and each outcome. Results: Of 579,505 eligible records, 94,640 (16%) were excluded due to missing data needed to calculate REMS. Overall, 62% (n = 298,223) of patients were discharged from the ED, 36% (n = 175,212) were admitted, 2% (n = 10,499) were transferred, and 0.2% (n = 931) died in the ED. A REMS of 5 or lower demonstrated optimal statistical prediction for ED discharge versus not discharged (admission/transfer/death) (AUROC: 0.68). Patients with initial prehospital REMS of 5 or lower showed a three-fold increase in odds of ED discharge (OR: 3.28, 95%CI: 3.24-3.32). Of the 457,226 patients included in overall mortality analysis, >98% (n = 450,112) survived. AUROC of initial prehospital REMS for overall mortality was 0.79. A score 7 or lower was statistically optimal for predicting survival. Initial prehospital REMS of 7 or lower was associated with a five-fold increase in odds of overall survival (OR:5.41, 95%CI:5.15-5.69). Conclusion: Initial prehospital REMS was predictive of ED disposition and overall patient mortality, suggesting value as a risk-stratification measure for EMS agencies, systems and researchers.

Evaluating Firefighter On-Scene Decontamination Practices Using a National Fire Records Management System.

OBJECTIVE: This study describes firefighters' on-scene decontamination procedure use post-working fire and frequency of adherence to best practice. METHODS: This retrospective analysis of working fires was conducted using records from the ESO Data Collaborative (Austin, TX) national research database from January 1, 2021, to December 31, 2021. Documentation of decontamination procedures was examined among records with smoke or combustion products exposure. Firefighter and incident characteristics were evaluated. Descriptive statistics and univariable odds ratios were calculated. RESULTS: Among the 31,281 firefighters included in the study, 8.0% documented a fire-related exposure. Of those, 82% performed at least one on-scene decontamination procedure; 5% documented all decontamination procedures defined as best practices. The odds of documenting any decontamination procedure were significantly decreased among firefighters responding to incidents in rural areas compared with urban areas (odds ratio, 0.70). CONCLUSIONS: Fire personnel may not be taking all necessary decontamination steps post-working fires.

Adverse events following emergent prehospital sedation of patients with behavioral emergencies: A retrospective cohort study.

Background: Patients presenting to emergency medical services (EMS) with behavioral emergencies may require emergent sedation to facilitate care, but concerns about sedation-related adverse events (AEs) exist. This study aimed to describe the frequency of AEs following emergent prehospital sedation with three types of sedative agents: ketamine, benzodiazepines and antipsychotics. Methods: This retrospective cohort study included patients ≥ 15 years who presented to 1031U.S. EMS agencies in calendar year 2019 with behavioral emergencies necessitating emergent prehospital sedation. Serious AEs (SAE) included cardiac arrest, invasive airway placement, and severe oxygen desaturation (<75%). Less-serious AEs included positive pressure ventilation, any oxygen desaturation (<90%), oropharyngeal or nasopharyngeal airway placement, and suctioning. The need for additional sedation was also assessed. Findings: Of 7973 patients, 1996 received ketamine; 4137 received a benzodiazepine; 1532 received an antipsychotic agent; and 308 received an indeterminant agent. Cardiac arrest occurred in 11 patients (0·1%) and any SAE occurred in 165 patients (2·1%). Invasive airway placement was more frequent with ketamine (40, 2·0%) compared with benzodiazepines (17, 0·4%) or antipsychotics (3, 0·2%). Oxygen desaturation below 75% also occurred more frequently with ketamine (51, 2·6%) than with benzodiazepines (52, 1·3%) or antipsychotics (14, 0·9%). Patients sedated with ketamine were less likely to require additional sedation. Propensity-matching to minimize potential confounding between patient condition, sedative choice and AEs did not meaningfully alter the results. Interpretation: Although SAEs were rare among patients receiving emergent prehospital sedation, prehospital clinicians should remain mindful of the potential risks and monitor patients closely. Funding: None.

Initial prehospital Rapid Emergency Medicine Score (REMS) to predict outcomes for COVID-19 patients.

OBJECTIVE: The Rapid Emergency Medicine Score (REMS) has not been widely studied for use in predicting outcomes of COVID-19 patients encountered in the prehospital setting. This study aimed to determine whether the first prehospital REMS could predict emergency department and hospital dispositions for COVID-19 patients transported by emergency medical services. METHODS: This retrospective study used linked prehospital and hospital records from the ESO Data Collaborative for all 911-initiated transports of patients with hospital COVID-19 diagnoses from July 1 to December 31, 2020. We calculated REMS with the first recorded prehospital values for each component. We calculated area under the receiver operating curve (AUROC) for emergency department (ED) mortality, ED discharge, hospital mortality, and hospital length of stay (LOS). We determined optimal REMS cut-points using test characteristic curves. RESULTS: Among 13,830 included COVID-19 patients, median REMS was 6 (interquartile range [IQR]: 5-9). ED mortality was <1% (n = 80). REMS ≥9 predicted ED death (AUROC 0.79). One-quarter of patients (n = 3,419) were discharged from the ED with an optimal REMS cut-point of ≤5 (AUROC 0.72). Eighteen percent (n = 1,742) of admitted patients died. REMS ≥8 optimally predicted hospital mortality (AUROC 0.72). Median hospital LOS was 8.3 days (IQR: 4.1-14.8 days). REMS ≥7 predicted hospitalizations ≥3 days (AUROC 0.62). CONCLUSION: Initial prehospital REMS was modestly predictive of ED and hospital dispositions for patients with COVID-19. Prediction was stronger for outcomes more proximate to the first set of emergency medical services (EMS) vital signs. These findings highlight the potential value of first prehospital REMS for risk stratification of individual patients and system surveillance for resource planning related to COVID-19.