Defining Levels of US Hospitals' Pediatric Capabilities.

Importance: Classifying hospitals across a wide range of pediatric capabilities, including medical, surgical, and specialty services, would improve understanding of access and outcomes. Objective: To develop a classification system for hospitals' pediatric capabilities. Design, Setting, and Participants: This cross-sectional study included data from 2019 on all acute care hospitals with emergency departments in 10 US states that treated at least 1 child per day. Statistical analysis was performed from September 2023 to February 2024. Exposure: Pediatric hospital capability level, defined using latent class analysis. The latent class model parameters were the presence or absence of 26 functional capabilities, which ranged from performing laceration repairs to performing organ transplants. A simplified approach to categorization was derived and externally validated by comparing each hospital's latent class model classification with its simplified classification using data from 3 additional states. Main Outcomes and Measures: Health care utilization and structural characteristics, including inpatient beds, pediatric intensive care unit (PICU) beds, and referral rates (proportion of patients transferred among patients unable to be discharged). Results: Using data from 1061 hospitals (716 metropolitan [67.5%]) with a median of 2934 pediatric ED encounters per year (IQR, 1367-5996), the latent class model revealed 4 pediatric levels, with a median confidence of hospital assignment to level of 100% (IQR, 99%-100%). Of 26 functional capabilities, level 1 hospitals had a median of 24 capabilities (IQR, 21-25), level 2 hospitals had a median of 13 (IQR, 11-15), level 3 hospitals had a median of 8 (IQR, 6-9), and level 4 hospitals had a median of 3 (IQR, 2-3). Pediatric level 1 hospitals had a median of 66 inpatient beds (IQR, 42-86), level 2 hospitals had a median of 16 (IQR, 9-22), level 3 hospitals had a median of 0 (IQR, 0-6), and level 4 hospitals had a median of 0 (IQR, 0-0) (P < .001). Level 1 hospitals had a median of 19 PICU beds (IQR, 10-28), level 2 hospitals had a median of 0 (IQR, 0-5), level 3 hospitals had a median of 0 (IQR, 0-0), and level 4 hospitals had a median of 0 (IQR, 0-0) (P < .001). Level 1 hospitals had a median referral rate of 1% (IQR, 1%-3%), level 2 hospitals had a median of 25% (IQR, 9%-45%), level 3 hospitals had a median of 70% (IQR, 52%-84%), and level 4 hospitals had a median of 100% (IQR, 98%-100%) (P < .001). Conclusions and Relevance: In this cross-sectional study of hospitals from 10 US states, a system to classify hospitals' pediatric capabilities in 4 levels was developed and was associated with structural and health care utilization characteristics. This system can be used to understand and track national pediatric acute care access and outcomes.

Frequency of Discordant Documentation of Patient Race and Ethnicity.

This cohort study examines longitudinal changes in race and ethnicity assignment in US hospitals.

A Comparison of State-Specific Pediatric Emergency Medical Facility Recognition Programs, 2020.

OBJECTIVES: Prior research suggests that the presence of state-specific pediatric emergency medical facility recognition programs (PFRPs) is associated with high emergency department (ED) pediatric readiness. The PFRPs aim to improve the quality of pediatric emergency care, but individual state programs differ. We aimed to describe the variation in PFRP characteristics and verification requirements and to describe the availability of pediatric emergency care coordinators (PECCs) in states with PFRPs. METHODS: In mid-2020, we collected information about each PFRP from 3 sources: the state Emergency Medical Services for Children (EMSC) website, the EMSC Innovation and Improvement Center website, or via communication with the state's EMSC program manager. For each state with a PFRP, we documented program characteristics, including program start date, number of tiers, whether participation was required/optional, and requirements for verification. RESULTS: Overall, we identified 17 states with active PFRPs. Five states had only 1 tier or level of recognition whereas the others had multiple. All programs did require presence of a PECC for verification. However, some PRFPs with multiple verification tiers did not require presence of a PECC to achieve each level of verification. In states with PFRPs, EDs with higher total visit volumes, a separate pediatric ED area, located in the Northeast, and earlier program start date were all more likely to have a PECC. CONCLUSIONS: There is variation in state PFRPs, although all prioritize the presence of a PECC. We encourage further research on the effect of different aspects of PFRPs on patient outcomes.

Pediatric capacity crisis: A framework and strategies to prepare for a pediatric surge.

A pediatric capacity crisis developed across the country in the Fall and Winter of 2022 due to a combination of factors, including a surge in respiratory viruses, staffing shortages, and historical closures of inpatient pediatric units. The COVID-19 pandemic and associated surge in critically ill adult patients demonstrated that health care systems and health care workers can quickly implement creative and collaborative system-wide solutions to deliver the best care possible during a capacity crisis. Similar solutions are needed to respond to future surges in pediatric volume and to maintain a high standard of care during such a surge. This paper aims to build upon insights from the COVID-19 and H1N1 pandemic responses and the 2022 pediatric capacity crisis. We provide specific recommendations addressing governmental/policy, hospital/health care system, and individual clinician strategies that can be implemented to manage future surges in pediatric patient volume.

Analysis of a Medication Safety Intervention in the Pediatric Emergency Department.

Importance: Strategies to reduce medication dosing errors are crucial for improving outcomes. The Medication Education for Dosing Safety (MEDS) intervention, consisting of a simplified handout, dosing syringe, dose demonstration and teach-back, was shown to be effective in the emergency department (ED), but optimal intervention strategies to move it into clinical practice remain to be described. Objective: To describe implementation of MEDS in routine clinical practice and associated outcomes. Design, Setting, and Participants: This mixed-methods interrupted time series study of MEDS was conducted April 2021 to December 2022 in an academic pediatric ED using a hybrid type 1 design. Parents and guardians of children aged 90 days to 11.9 years who were discharged with acetaminophen, ibuprofen, or both were eligible for inclusion in the quantitative portion. Clinicians from a diversity of role groups (attending physician, resident, and nurse) were eligible for the qualitative portion. Exposures: The study was conducted in 5 stages (baseline, intervention 1, washout, intervention 2, and sustainability phases). The 2 intervention phases taught clinical staff the MEDS intervention using different implementation strategies. During the intervention 1 phase, in-depth interviews were conducted until thematic saturation was reached; results were analyzed using thematic analysis. Interviews informed intervention 2 phase interventions. Main Outcomes and Measures: The primary outcome was any error (defined as dosing or frequency error) at a 48- to 72-hour follow-up phone call. Results: There were 256 participants (median [IQR] child age, 1.7 [3.0-7.0] years; median [IQR] parent and guardian age, 36.0 [31.0-41.0] years; 200 females among parents and guardians [78.1%]) who consented and completed follow-up. At baseline, 44 of 68 participants (64.7%) made an error compared with 34 of 65 participants (52.3%) during intervention 1, 31 of 63 participants (49.X%) during intervention 2, and 34 of 60 participants (57.X%) during sustainability. After adjustment for language and health literacy, the adjusted odds ratio for error during the combined intervention phases was 0.52 (95% CI, 0.28-0.97) compared with baseline. Conclusions and Relevance: This study found that both MEDS intervention phases were associated with decreased risk of error and that some improvement was sustained without active intervention. These findings suggest that attempts to develop simplified, brief interventions may be associated with improved medication safety for children after discharge from the ED.

Mapping Oral health and Local Area Resources (MOLAR): protocol for a randomised controlled trial connecting emergency department patients with social and dental resources.

INTRODUCTION: There are substantial inequities in oral health access and outcomes in the USA, including by income and racial and ethnic identity. People with adverse social determinants of health (aSDoH), such as housing or food insecurity, are also more likely to have unmet dental needs. Many patients with dental problems present to the emergency department (ED), where minimal dental care or referral is usually available. Nonetheless, the ED represents an important point of contact to facilitate screening and referral for unmet oral health needs and aSDoH, particularly for patients who may not otherwise have access to care. METHODS AND ANALYSIS: Mapping Oral health and Local Area Resources is a randomised controlled trial enrolling 2049 adult and paediatric ED patients with unmet oral health needs into one of three trial arms: (a) a standard handout of nearby dental and aSDoH resources; (b) a geographically matched listing of aSDoH resources and a search link for identification of geographically matched dental resources; or (c) geographically matched resources along with personalised care navigation. Follow-up at 3, 6, 9 and 12 months will evaluate oral health-related quality of life, linkage to resources and dental treatment, ED visits for dental problems and the association between linkage and neighbourhood resource density. ETHICS AND DISSEMINATION: All sites share a single human subjects review board protocol which has been fully approved by the Mass General Brigham Human Subjects Review Board. Informed consent will be obtained from all adults and adult caregivers, and assent will be obtained from age-appropriate child participants. Results will demonstrate the impact of addressing aSDoH on oral health access and the efficacy of various forms of resource navigation compared with enhanced standard care. Our findings will facilitate sustainable, scalable interventions to identify and address aSDoH in the ED to improve oral health and reduce oral health inequities. TRIAL REGISTRATION NUMBER: NCT05688982.

Epidemiology of Emergency Medical Services-Attended out-of-Hospital Deliveries and Complications in the United States.

BACKGROUND: Prehospital obstetric events, including out-of-hospital deliveries and their complications, are a rare but high-risk event encountered by emergency medical services (EMS). Understanding the epidemiology of these encounters would help identify strategies to improve prehospital obstetric care. Our objective was to determine the characteristics of out-of-hospital deliveries and high-risk complications treated by EMS clinicians in the U.S. METHODS: We conducted a cross-sectional analysis of EMS patient care records in the 2018 and 2019 National EMS Information System Public Release Version 3.4 datasets. We included EMS activations after a 9-1-1 scene response for patients aged 12-50 years with evidence of an out-of-hospital delivery or delivery complication, or where the patient was a newborn aged 0-<6 h. We examined patient, community, emergency response, and clinical characteristics using descriptive statistics. RESULTS: Of the 56,735,977 EMS activations included in the 2018 and 2019 datasets, there were 8,614 out-of-hospital deliveries, 1,712 delivery complications, and 5,749 records for newborns. Most maternal (76%) out-of-hospital deliveries involved patients between the ages of 20-34 years, occurred on a weekday (73%), were treated by an advanced life support crew (85%), and occurred in a home or residence (73%). EMS-assisted field delivery was documented in 3,515 (34%) of all maternal activations but only 2% of activations with a delivery complication. Few patients received an EMS-administered medication (e.g., 0.4% received oxytocin). Supplemental oxygen was administered in 870 (15%) of newborn activations. Activations from counties with the most racial/ethnic diversity were more often treated by a BLS-level unit (16% vs. 12%, p < 0.001), and activations from rural areas had significantly longer transport times (19.7 min [IQR 8.7, 32.8] vs. urban, 13.1 min [IQR 8.7, 19.7], p < 0.001). CONCLUSION: In this large, national repository of EMS patient care records from across the U.S., most activations for out-of-hospital delivery, delivery complication, or a newborn included only routine EMS care. There were potential disparities in level of care, clinical care provided, and measures of access to definitive care based on maternal and community factors. We also identified gaps in current practice, such as for postpartum hemorrhage, that could be addressed with changes in EMS clinical protocols and regulations.

Diversity, Equity, and Inclusion: Considerations in the Geriatric Emergency Department Patient.

This article introduces core topics in health equity scholarship and provides examples of how diversity, equity, and inclusion impact the aging population and emergency care of older adults. It offers strategies for promoting diversity, equity, and inclusion to both strengthen the patient-clinician therapeutic relationship and to address operations and systems that impact care of the geriatric emergency department patient.

Race and Ethnicity and Primary Language in Emergency Department Triage.

Importance: Emergency department (ED) triage substantially affects how long patients wait for care but triage scoring relies on few objective criteria. Prior studies suggest that Black and Hispanic patients receive unequal triage scores, paralleled by disparities in the depth of physician evaluations. Objectives: To examine whether racial disparities in triage scores and physician evaluations are present across a multicenter network of academic and community hospitals and evaluate whether patients who do not speak English face similar disparities. Design, Setting, and Participants: This was a cross-sectional, multicenter study examining adults presenting between February 28, 2019, and January 1, 2023, across the Mass General Brigham Integrated Health Care System, encompassing 7 EDs: 2 urban academic hospitals and 5 community hospitals. Analysis included all patients presenting with 1 of 5 common chief symptoms. Exposures: Emergency department nurse-led triage and physician evaluation. Main Outcomes and Measures: Average Triage Emergency Severity Index [ESI] score and average visit work relative value units [wRVUs] were compared across symptoms and between individual minority racial and ethnic groups and White patients. Results: There were 249 829 visits (149 861 female [60%], American Indian or Alaska Native 0.2%, Asian 3.3%, Black 11.8%, Hispanic 18.8%, Native Hawaiian or Other Pacific Islander <0.1%, White 60.8%, and patients identifying as Other race or ethnicity 5.1%). Median age was 48 (IQR, 29-66) years. White patients had more acute ESI scores than Hispanic or Other patients across all symptoms (eg, chest pain: Hispanic, 2.68 [95% CI, 2.67-2.69]; White, 2.55 [95% CI, 2.55-2.56]; Other, 2.66 [95% CI, 2.64-2.68]; P < .001) and Black patients across most symptoms (nausea/vomiting: Black, 2.97 [95% CI, 2.96-2.99]; White: 2.90 [95% CI, 2.89-2.91]; P < .001). These differences were reversed for wRVUs (chest pain: Black, 4.32 [95% CI, 4.25-4.39]; Hispanic, 4.13 [95% CI, 4.08-4.18]; White 3.55 [95% CI, 3.52-3.58]; Other 3.96 [95% CI, 3.84-4.08]; P < .001). Similar patterns were seen for patients whose primary language was not English. Conclusions and Relevance: In this cross-sectional study, patients who identified as Black, Hispanic, and Other race and ethnicity were assigned less acute ESI scores than their White peers despite having received more involved physician workups, suggesting some degree of mistriage. Clinical decision support systems might reduce these disparities but would require careful calibration to avoid replicating bias.

Insurance-Based Disparities in Stroke Center Access in California: A Network Science Approach.

BACKGROUND: Our objectives were to determine whether there is an association between ischemic stroke patient insurance and likelihood of transfer overall and to a stroke center and whether hospital cluster modified the association between insurance and likelihood of stroke center transfer. METHODS: This retrospective network analysis of California data included every nonfederal hospital ischemic stroke admission from 2010 to 2017. Transfers from an emergency department to another hospital were categorized based on whether the patient was discharged from a stroke center (primary or comprehensive). We used logistic regression models to examine the relationship between insurance (private, Medicare, Medicaid, uninsured) and odds of (1) any transfer among patients initially presenting to nonstroke center hospital emergency departments and (2) transfer to a stroke center among transferred patients. We used a network clustering method to identify clusters of hospitals closely connected through transfers. Within each cluster, we quantified the difference between insurance groups with the highest and lowest proportion of transfers discharged from a stroke center. RESULTS: Of 332 995 total ischemic stroke encounters, 51% were female, 70% were ≥65 years, and 3.5% were transferred from the initial emergency department. Of 52 316 presenting to a nonstroke center, 3466 (7.1%) were transferred. Relative to privately insured patients, there were lower odds of transfer and of transfer to a stroke center among all groups (Medicare odds ratio, 0.24 [95% CI, 0.22-0.26] and 0.59 [95% CI, 0.50-0.71], Medicaid odds ratio, 0.26 [95% CI, 0.23-0.29] and odds ratio, 0.49 [95% CI, 0.38-0.62], uninsured odds ratio, 0.75 [95% CI, 0.63-0.89], and 0.72 [95% CI, 0.6-0.8], respectively). Among the 14 identified hospital clusters, insurance-based disparities in transfer varied and the lowest performing cluster (also the largest; n=2364 transfers) fully explained the insurance-based disparity in odds of stroke center transfer. CONCLUSIONS: Uninsured patients had less stroke center access through transfer than patients with insurance. This difference was largely explained by patterns in 1 particular hospital cluster.

Community Validation of an Approach to Detect Delayed Diagnosis of Appendicitis in Big Databases.

BACKGROUND: Detection of delayed diagnosis using administrative databases may illuminate the healthcare settings at highest risk. A method for detection of delays in claims has been validated in children's hospitals. We sought to further validate the method in community emergency departments (EDs). METHODS: We studied patients <21 years old diagnosed with appendicitis from 2008 to 2019 in 8 eastern Massachusetts EDs. Eligible patients had 2 ED encounters within 7 days, the second with an appendicitis diagnosis. Delayed diagnosis was evaluated in medical records by trained reviewers. A previously validated trigger tool was applied to participants' electronic medical record data. The tool used data elements included in administrative data, including initial encounter diagnoses, time between encounters, presence of medical complexity, and ultimate length of stay. The tool assigned a probability of delayed diagnosis for each patient. Test characteristics at 4 confidence thresholds were determined, and the area under the receiver operating curve was calculated. RESULTS: We analyzed 68 children with 2 encounters leading to a diagnosis of appendicitis (i.e., possible delay). When assigning a delayed diagnosis prediction to patients at 4 thresholds of confidence (>0%, >50%, >75%, and >90% confident), the positive predictive values were respectively 74%, 89%, 92%, and 89%; the negative predictive values were respectively 100%, 57%, 50%, and 33%. The area under the receiver operating curve was 0.837 (95% confidence interval 0.719-0.954). CONCLUSIONS: A trigger tool that identifies delays in diagnosis using only administrative data in community EDs has a high positive predictive value for true delay. The tool may be applied in community EDs.

Racial and Ethnic Differences in Insurer Classification of Nonemergent Pediatric Emergency Department Visits.

Importance: Government and commercial health insurers have recently enacted policies to discourage nonemergent emergency department (ED) visits by reducing or denying claims for such visits using retrospective claims algorithms. Low-income Black and Hispanic pediatric patients often experience worse access to primary care services necessary for preventing some ED visits, raising concerns about the uneven impact of these policies. Objective: To estimate potential racial and ethnic disparities in outcomes of Medicaid policies for reducing ED professional reimbursement based on a retrospective diagnosis-based claims algorithm. Design, Setting, and Participants: This simulation study used a retrospective cohort of pediatric ED visits (aged 0-18 years) for Medicaid-insured children and adolescents appearing in the Market Scan Medicaid database between January 1, 2016, and December 31, 2019. Visits missing date of birth, race and ethnicity, professional claims data, and Current Procedural Terminology codes of billing level of complexity were excluded, as were visits that result in admission. Data were analyzed from October 2021 to June 2022. Main Outcomes and Measures: Proportion of ED visits algorithmically classified as nonemergent and simulated per-visit professional reimbursement after applying a current reimbursement reduction policy for potentially nonemergent ED visits. Rates were calculated overall and compared by race and ethnicity. Results: The sample included 8 471 386 unique ED visits (43.0% by patients aged 4-12 years; 39.6% Black, 7.7% Hispanic, and 48.7% White), of which 47.7% were algorithmically identified as potentially nonemergent and subject to reimbursement reduction, resulting in a 37% reduction in ED professional reimbursement across the study cohort. More visits by Black (50.3%) and Hispanic (49.0%) children were algorithmically identified as nonemergent when compared with visits by White children (45.3%; P < .001). Modeling the impact of the reimbursement reductions across the cohort resulted in expected per-visit reimbursement that was 6% lower for visits by Black children and 3% lower for visits by Hispanic children relative to visits by White children. Conclusions and Relevance: In this simulation study of over 8 million unique ED visits, algorithmic approaches for classifying pediatric ED visits that used diagnosis codes identified proportionately more visits by Black and Hispanic children as nonemergent. Insurers applying financial adjustments based on these algorithmic outputs risk creating uneven reimbursement policies across racial and ethnic groups.

Availability of Pediatric Emergency Care Coordinators in US Emergency Departments in 2018.

OBJECTIVES: In 2007, the US Institute of Medicine recommended that every emergency department (ED) appoint pediatric emergency care coordinators (PECCs). Despite this recommendation, our national surveys showed that few (17%) US EDs reported at least 1 PECC in 2015. This number increased slightly to 19% in 2016 and 20% in 2017. The current study objectives were to determine the following: percent of US EDs with at least 1 PECC in 2018, factors associated with availability of at least 1 PECC in 2018, and factors associated with addition of at least 1 PECC between 2015 and 2018. METHODS: In 2019, we conducted a survey of all US EDs to characterize emergency care in 2018. Using the National ED Inventory-USA database, we identified 5514 EDs open in 2018. This survey collected availability of at least 1 PECC in 2018. A similar survey was administered in 2016 and identified availability of at least 1 PECC in 2015. RESULTS: Overall, 4781 (87%) EDs responded to the 2018 survey. Among 4764 EDs with PECC data, 1037 (22%) reported having at least 1 PECC. Three states (Connecticut, Massachusetts, and Rhode Island) had PECCs in 100% of EDs. The EDs in the Northeast and with higher visit volumes were more likely to have at least 1 PECC in 2018 (all P < 0.001). Similarly, EDs in the Northeast and with higher visit volumes were more likely to add a PECC between 2015 and 2018 (all P < 0.05). CONCLUSIONS: The availability of PECCs in EDs remains low (22%), with a small increase in national prevalence between 2015 and 2018. Northeast states report a high PECC prevalence, but more work is needed to appoint PECCs in all other regions.

Pediatric Telehealth Use in U.S. Emergency Departments in 2019.

Objectives: Little is known about the recent usage of pediatric telehealth across all emergency departments (EDs) in the United States. Building upon our prior work, we aimed to characterize the usage of ED pediatric telehealth in the pre-COVID-19 era. Methods: The 2019 National ED Inventory-USA survey characterized all U.S. EDs open in 2019. Among EDs reporting receipt of pediatric telehealth services, we selected a random sample (n = 130) for a second survey on pediatric telehealth usage (2019 ED Pediatric Telehealth Survey). We also recontacted a random sample of EDs that responded to a prior, similar 2017 ED Pediatric Telehealth Survey (n = 107), for a total of 237 EDs in the 2019 ED Pediatric Telehealth Survey sample. Results: Overall, 193 (81%) of the 237 EDs responded to the 2019 Pediatric Telehealth Survey. There were 149 responding EDs that confirmed pediatric telehealth receipt in 2019. Among these, few reported ever having a pediatric emergency medicine (PEM) physician (10%) or pediatrician (9%) available for emergency care. Although 96% of EDs reported availability of pediatric telehealth services 24 h per day, 7 days per week, the majority (60%) reported using services less than once per month and 20% reported using services every 3-4 weeks. EDs most frequently used pediatric telehealth to assist with placement and transfer coordination (91%). Conclusions: Most EDs receiving pediatric telehealth in 2019 had no PEM physician or pediatrician available. Most EDs used pediatric telehealth services infrequently. Understanding barriers to assimilation of telehealth once adopted may be important to enable improved access to pediatric emergency care expertise.