Crossing the line: access to trauma care across state borders.

Objective: This study investigates the challenge posed by state borders by identifying the population, injury, and geographic scope of areas of the country where the closest trauma center is out-of-state, and by collating state emergency medical services (EMS) policies relevant to cross-border trauma transport. Methods: We identified designated levels I, II, and III trauma centers using data from American Trauma Society. ArcGIS was used to map the distance between US census block groups and trauma centers to identify the geographic areas for which cross-border transport may be most expedient. National Highway Traffic Safety Administration data were queried to quantify the proportion of fatal crashes occurring in the areas of interest. State EMS protocols were categorized by stance on cross-border transport. Results: Of 237 596 included US census block groups, 18 499 (7.8%) were closest to an out-of-state designated level I or II trauma center. These census block groups accounted for 6.9% of the US population and 9.5% of all motor vehicle fatalities. With the inclusion of level III trauma centers, the number of US census block groups closest to an out-of-state designated level I, II, or III trauma center decreased to 13 690 (5.8%). These census block groups accounted for 5.1% of the US population and 7.1% of all motor vehicle fatalities. Of the 48 contiguous states, 30 encourage cross-border transport, 2 discourage it, 12 are neutral, and 4 leave it to local discretion. Conclusion: Cross-border transport can expedite access to care in at least 5% of US census block groups. While few states discourage this practice, more robust policy guidance could reduce delays and enhance care. Level of Evidence: III, Epidemiological.

A National Assessment of EMS Performance at the Response and Agency Level.

BACKGROUND: In 2019, the National EMS Quality Alliance (NEMSQA) established a suite of 11 evidence-based EMS quality measures, yet little is known regarding EMS performance on a national level. Our objective was to describe EMS performance at a response and agency level using the National EMS Information System (NEMSIS) dataset. METHODS: The 2019 NEMSIS research dataset of all EMS 9-1-1 responses in the United States was utilized to calculate 10 of 11 NEMSQA quality measures. Measure criteria and pseudocode was implemented to calculate the proportion meeting measure criteria and 95% confidence intervals across all encounters and for each anonymized agency. We omitted Pediatrics-03b because the NEMSIS national dataset does not report patient weight. Agency level analysis was subsequently stratified by call volume and urbanicity. RESULTS: Records from 9,679 agencies responding to 26,502,968 9-1-1 events were analyzed. Run-level average performance ranged from 12% for Safety-01 (encounter documented as initial response without the use of lights and siren to 82% for Pediatrics-02 (documented respiratory assessment in pediatric patients with respiratory distress) At the agency level, significant variation in measure performance existed by agency size and by urbanicity. At the individual agency performance analysis, Trauma-04 (trauma patients transported to trauma center) had the lowest agency-level performance with 47% of agencies reporting 0% of eligible runs with documented transport to a trauma center. CONCLUSION: There is a wide range of performance in key EMS quality measures across the United States that demonstrate a need to identify strategies to improve quality and equity of care in the prehospital environment, system performance and data collection.

Racial and ethnic disparities in emergency department transfers to public hospitals.

OBJECTIVE: To examine racial/ethnic differences in emergency department (ED) transfers to public hospitals and factors explaining these differences. DATA SOURCES AND STUDY SETTING: ED and inpatient data from the Healthcare Cost and Utilization Project for Florida (2010-2019); American Hospital Association Annual Survey (2009-2018). STUDY DESIGN: Logistic regression examined race/ethnicity and payer on the likelihood of transfer to a public hospital among transferred ED patients. The base model was controlled for patient and hospital characteristics and year fixed effects. Models II and III added urbanicity and hospital referral region (HRR), respectively. Model IV used hospital fixed effects, which compares patients within the same hospital. Models V and VI stratified Model IV by payer and condition, respectively. Conditions were classified as emergency care sensitive conditions (ECSCs), where transfer is protocolized, and non-ECSCs. We reported marginal effects at the means. DATA COLLECTION/EXTRACTION METHODS: We examined 1,265,588 adult ED patients transferred from 187 hospitals. PRINCIPAL FINDINGS: Black patients were more likely to be transferred to public hospitals compared with White patients in all models except ECSC patients within the same initial hospital (except trauma). Black patients were 0.5-1.3 percentage points (pp) more likely to be transferred to public hospitals than White patients in the same hospital with the same payer. In the base model, Hispanic patients were more likely to be transferred to public hospitals compared with White patients, but this difference reversed after controlling for HRR. Hispanic patients were - 0.6 pp to -1.2 pp less likely to be transferred to public hospitals than White patients in the same hospital with the same payer. CONCLUSIONS: Large population-level differences in whether ED patients of different races/ethnicities were transferred to public hospitals were largely explained by hospital market and the initial hospital, suggesting that they may play a larger role in explaining differences in transfer to public hospitals, compared with other external factors.

Association of Racial Residential Segregation With Long-Term Outcomes and Readmissions After Out-of-Hospital Cardiac Arrest Among Medicare Beneficiaries.

Background The national impact of racial residential segregation on out-of-hospital cardiac arrest outcomes after initial resuscitation remains poorly understood. We sought to characterize the association between measures of racial and economic residential segregation at the ZIP code level and long-term survival and readmissions after out-of-hospital cardiac arrest among Medicare beneficiaries. Methods and Results In this retrospective cohort study, using Medicare claims data, our primary predictor was the index of concentration at the extremes, a measure of racial and economic segregation. The primary outcomes were death up to 3 years and readmissions. We estimated hazard ratios (HRs) across all 3 types of index of concentration at the extremes measures for each outcome while adjusting for beneficiary demographics, treating hospital characteristics, and index hospital procedures. In fully adjusted models for long-term survival, we found a decreased hazard of death and risk of readmission for beneficiaries residing in the more segregated White communities  and higher-income ZIP codes compared with the more segregated Black communities and lower-income ZIP codes across all 3 indices of concentration at the extremes measures (race: HR, 0.87 [95% CI, 0.81-0.93]; income: HR, 0.75 [95% CI, 0.69-0.78]; and race+income: HR, 0.77 [95% CI, 0.72-0.82]). Conclusions We found a decreased hazard of death and risk for readmission for those residing in the more segregated White communities  and higher-income ZIP codes compared with the more segregated Black communities and lower-income ZIP codes when using validated measures of racial and economic segregation. Although causal pathways and mechanisms remain unclear, disparities in outcomes after out-of-hospital cardiac arrest are associated with the structural components of race and wealth and persist up to 3 years after discharge.

Survival After Out-of-Hospital Cardiac Arrest: The Role of Racial Residential Segregation.

Racial and racialized economic residential segregation has been empirically associated with outcomes across multiple health conditions but not yet explored in relation to out-of-hospital cardiac arrest (OHCA). We sought to examine if measures of racial and economic residential segregation are associated with differences in survival to discharge after OHCA for Black and White Medicare beneficiaries. Utilizing age-eligible Medicare fee-for-service claims data from 2013 to 2015, we identified OHCA claims and determined survival to discharge. The primary predictor, residential segregation, was calculated using the index of concentration at the extremes (ICE) for the beneficiary residential ZIP code. Multilevel modified Poisson regression models were used to determine the association of OHCA outcomes and ZIP code level ICE measures. In total, 194,263 OHCA cases were identified among beneficiaries residing in 75% of US ZIP codes. Black beneficiaries exhibited 12.1% survival to discharge, compared with 12.5% of White beneficiaries. In fully adjusted models of the three ICE measures accounting for differences in treating hospital characteristics, there was as high as a 28% (RR 1.28, CI 1.23-1.26) higher relative likelihood of survival to discharge in the most segregated White ZIP codes (Q5) as compared to the most segregated Black ZIP codes (Q1). Racial residential segregation is independently associated with disparities in OHCA outcomes; among Medicare beneficiaries who generated a claim after suffering an OHCA, ICE measures of racial segregation are associated with a lower likelihood of survival to discharge for those living in the most segregated Black and lower income quintiles compared to higher quintiles.

Emergency departments in the United States treating high proportions of patients with ambulatory care sensitive conditions: a retrospective cross-sectional analysis.

BACKGROUND: One in nine emergency department (ED) visits by Medicare beneficiaries are for ambulatory care sensitive conditions (ACSCs). This study aimed to examine the association between ACSC ED visits to hospitals with the highest proportion of ACSC visits ("high ACSC hospitals) and safety-net status. METHODS: This was a cross-sectional study of ED visits by Medicare fee-for-service beneficiaries ≥ 65 years using 2013-14 claims data, Area Health Resources File data, and County Health Rankings. Logistic regression estimated the association between an ACSC ED visit to high ACSC hospitals, accounting for individual, hospital, and community factors, including whether the visit was to a safety-net hospital. Safety net status was measured by Disproportionate Share Hospital (DSH) index patient percentage; public hospital status; and proportion of dual-eligible beneficiaries. Hospital-level correlation was calculated between ACSC visits, DSH index, and dual-eligible patients. We stratified by type of ACSC visit: acute or chronic. RESULTS: Among 5,192,729 ACSC ED visits, the odds of visiting a high ACSC hospital were higher for patients who were Black (1.37), dual-eligible (1.18), and with the highest comorbidity burden (1.26, p < 0.001 for all). ACSC visits had increased odds of being to high ACSC hospitals if the hospitals were high DSH (1.43), served the highest proportion of dual-eligible beneficiaries (2.23), and were for-profit (relative to non-profit) (1.38), and lower odds were associated with public hospitals (0.64) (p < 0.001 for all). This relationship was similar for visits to high chronic ACSC hospitals (high DSH: 1.59, high dual-eligibility: 2.60, for-profit: 1.41, public: 0.63, all p < 0.001) and to a lesser extent, high acute ACSC hospitals (high DSH: 1.02; high dual-eligibility: 1.48, for-profit: 1.17, public: 0.94, p < 0.001). The proportion of ACSC visits at all hospitals was weakly correlated with DSH proportion (0.2) and the proportion of dual-eligible patients (0.29), and this relationship was also seen for both chronic and acute ACSC visits, though stronger for the chronic ACSC visits. CONCLUSION: Visits to hospitals with a high proportion of acute ACSC ED visits may be less likely to be to hospitals classified as safety net hospitals than those with a high proportion of chronic ACSC visits.

Socioeconomic disparities in layperson CPR training within a large U.S. city.

AIM OF THE STUDY: We sought to understand how individual factors and neighborhood characteristics are associated with a layperson's likelihood of being trained in CPR. We hypothesized that higher socioeconomic status (educational attainment, and median household income (MHI)) would be associated with a higher likelihood of previous CPR training. METHODS: Through the Mobile CPR Project, a program providing hands-only CPR and AED education in Philadelphia, we surveyed participants regarding socioeconomic factors and prior CPR training. Survey questions pertained to race, gender, education, prior CPR training, automated external defibrillator (AED) awareness, and residential area. Community MHI was extrapolated via residential address and census tract data. RESULTS: From 7/2016 to 4/2018, 1703 subjects completed surveys, including location information, prior to participating in a Mobile CPR Project training event. Of these, 70% were female, 70% were non-white, mean age was 42 ±â€¯20 years, and MHI was $39,318 [IQR $27,708-$60,795]. Subjects residing in census tracts with MHI below the cohort median were significantly less likely to have ever received CPR training (lowest quartile: OR 0.65, CI 0.49-0.85, p = 0.002). In multiple logistic regression controlling for age, race, gender, MHI, and education, higher educational attainment was associated with a higher likelihood of ever receiving CPR training (OR 7.96 Masters or Doctoral compared to less than high school, CI 5.24-12.11, p < 0.001). CONCLUSIONS: There is a strong association between socioeconomic factors (MHI and educational attainment) and likelihood of prior layperson CPR training.