Journal Watch: Pediatric EMS Use by ‘Opportunity’

Reviewed This Month

• The Child Opportunity Index and Pediatric Emergency Medical Services Utilization
• Authors: Ramgopal S, Jaeger L, Cercone A, Martin-Gill C, Fishe J
• Published in: Prehospital Emergency Care, 2022

Previous studies have found EMS utilization is higher among pediatric patients from lower socioeconomic statuses. Some studies suggest EMS use is low among people from those groups but is more often for lower-acuity disease, which results in overutilization of EMS. However, most prior research work in this area focused on regional data. 

Another limitation of previous studies of this topic is the metrics used to identify socioeconomic disparity. Some studies examine per-capita income alone, while others use a composite measure of area deprivation. The study we examine this month used national EMS data from the National EMS Information System (NEMSIS) 2019 data set and the Child Opportunity Index (COI) developed at Brandeis University to evaluate EMS utilization in children through different strata of the COI. Secondarily the authors compared measures of EMS resource utilization and pediatric patient acuity by COI. 

Parameters

We have reviewed a lot of studies that utilized data from NEMSIS, which is a national EMS database that includes standardized patient care records. The COI is a metric that measures and maps the quality of resources and conditions that matter for children to have healthy development. There are 29 key factors among its 3 domains of education, health and environment, and social and economic. The education domain measures quality and access to early childhood education, quality of elementary and secondary schools, and social resources related to educational achievement. The health and environment domain measures features of healthy environments, including access to healthy food and green space, as well as features that are toxic, such as pollution and exposure to extreme heat. The social and economic domain contains 9 indicators that measure access to employment and neighborhood social and economic resources. The COI ranks all neighborhoods in the US on a scale of 1–100, with higher scores indicating higher levels of opportunity. These scores are further classified into 5 categories of very high, high, moderate, low, and very low levels of opportunity. 

The study we review this month included all ALS and BLS calls in the 2019 NEMSIS database for patients less than 18 years of age. Patients were excluded if their age information was missing. Interfacility and nonground transports were also excluded. The NEMSIS data set is deidentified; therefore, to combine NEMSIS data with the COI, the authors had to work with the folks at NEMSIS. NEMSIS leaders  were kind enough to merge NEMSIS data with the COI data and return it to the authors in a way that the authors were blinded to patient zip code. 

Other than the merged COI data, the NEMSIS data also included age, sex, payment source, urbanicity (urban, suburban, rural, wilderness), census region, census division, incident location, chief complaint classified by organ system, injury status, call interval, response interval, scene interval, transport interval, organization type, and primary impression. Patient age was categorized as 0–1 years, 2–5 years, 6–11 years, and 12–17 years. Call time was classified as daytime (8 AM–3:59 PM), evening (4 PM–11:59 PM), or overnight (12 AM–7:59 AM). 

Primary impression was classified using the Diagnosis and Grouping System (DGS), a consensus-derived classification scheme using the primary diagnosis code that classifies patients into 21 major groups. The authors further consolidated the diagnosis groupings that occurred in fewer than 0.5% of encounters into an other category. They also made a group specifically for seizure-specific codes. The authors used identified specific patient care data as proxy measures for disease acuity (vital signs and cardiac arrest) and resource utilization (use of a cardiac monitor, need for a peripheral IV). 

The analysis compared the proportions of patients falling into each category of the COI. The authors calculated the proportions of patients with low and very low COI by census division and compared demographics, EMS factors, and treatment factors between strata of COI for all included patients. 

Results

There were more than 34 million EMS encounters available in the 2019 NEMSIS data set. After applying inclusion and exclusion criteria, almost 1.3 million encounters were included in the final study sample population. The overall study population was 51% male, with a median age of 10 years (interquartile range 3–15 years). When evaluating all pediatric EMS encounters, the distribution of encounters between very high (15%), high (16%), moderate (18%), and low (20%) COI zip codes was similar; however, the number of encounters from very low COI areas was higher (31%). Very low COI areas had a slightly higher proportion of encounters from rural regions compared to encounters from very high COI areas. Very low COI patients were more frequently from the south. Primary impressions were similar between these groups. Groups were similar with respect to time of day, response interval, scene interval, and transport interval. Measures of acuity were similar in most groups, including nontransport and cardiac arrest rates, rates of vital signs documentation, and extreme vital signs.

All studies have limitations. Some in this study included high rates of missing data, use of zip codes rather than census tracts to merge NEMSIS and COI data, and limitations inherent to the NEMSIS data set. 

Conclusion

This was an interesting and important study that found greater use of EMS by children from very low COI areas. However, despite that disproportionate use, the authors found similar rates of resource use across all COI strata, suggestive of similar patient acuity. I congratulate the authors on their creative merging of EMS and socioeconomic data! This a unique look at pediatric prehospital patient care.  

Antonio R. Fernandez, PhD, NRP, is the principal research scientist at ESO and serves on the board of advisors of the Prehospital Care Research Forum at UCLA.