Variability in Collection and Use of Race/Ethnicity and Language Data in 93 Pediatric Hospitals

Evaluation of Reliability Between Race and Ethnicity Data Obtained from Self-report Versus Electronic Health Record

INTRODUCTION

Disparities based on perceived race and ethnicity exist in all fields of medicine. Accurate data collection is crucial to addressing these disparities, yet few studies have evaluated the validity of data gathered. This study compares self-reported race and ethnicity data, considered the gold standard, with data documented in the electronic health record (EHR), to assess the validity of that data.

METHODS

Data from self-reported questionnaires was collected from adolescents admitted to a psychiatric inpatient unit from February 2019 to July 2022. Demographic questionnaires were self-administered as part of a larger battery completed during the admission process. Data was compared to demographic information collected from the hospital's EHR for the same patients and time.

RESULTS

In a sample of 1191 patients (ages 11-18, 61.9% female, 89% response rate), substantial agreement was observed for Hispanic ethnicity (κ = 0.64), while agreement for specific racial groups ranged from slight to substantial (κ = 0.10-0.63). In addition, it was noted that there was discrepancy between multiracial identification, with 17.1% of patients identifying as more than one race in self-reported data compared to 3.1% in EHR data.

CONCLUSIONS

The findings from this data set highlight the need for caution when using EHR data to draw conclusions about health disparities. It also suggests that the method of data collection meaningfully influences the responses patients provide. Addressing these challenges is essential for advancing equitable healthcare and mitigating disparities among patients.

Disparities in Racial, Ethnic, and Payer Groups for Pediatric Safety Events in US Hospitals

BACKGROUND AND OBJECTIVES

Health care disparities are pervasive, but little is known about disparities in pediatric safety. We analyzed a national sample of hospitalizations to identify disparities in safety events.

METHODS

In this population-based, retrospective cohort study of the 2019 Kids' Inpatient Database, independent variables were race, ethnicity, and payer. Outcomes were Agency for Healthcare Research and Quality pediatric safety indicators (PDIs). Risk-adjusted odds ratios were calculated using white and private payer reference groups. Differences by payer were evaluated by stratifying race and ethnicity.

RESULTS

Race and ethnicity of the 5 243 750 discharged patients were white, 46%; Hispanic, 19%; Black, 15%; missing, 8%; other race/multiracial, 7%, Asian American/Pacific Islander, 5%; and Native American, 1%. PDI rates (per 10 000 discharges) were 331.4 for neonatal blood stream infection, 267.5 for postoperative respiratory failure, 114.9 for postoperative sepsis, 29.5 for postoperative hemorrhage/hematoma, 5.6 for central-line blood stream infection, 3.5 for accidental puncture/laceration, and 0.7 for iatrogenic pneumothorax. Compared with white patients, Black and Hispanic patients had significantly greater odds in 5 of 7 PDIs; the largest disparities occurred in postoperative sepsis (adjusted odds ratio, 1.55 [1.38-1.73]) for Black patients and postoperative respiratory failure (adjusted odds ratio, 1.34 [1.21-1.49]) for Hispanic patients. Compared with privately insured patients, Medicaid-covered patients had significantly greater odds in 4 of 7 PDIs; the largest disparity occurred in postoperative sepsis (adjusted odds ratios, 1.45 [1.33-1.59]). Stratified analyses demonstrated persistent disparities by race and ethnicity, even among privately insured children.

CONCLUSIONS

Disparities in safety events were identified for Black and Hispanic children, indicating a need for targeted interventions to improve patient safety in the hospital.

Race, Ethnicity, and Intensive Care Utilization for Common Pediatric Diagnoses: U.S. Pediatric Health Information System 2019 Database Study

OBJECTIVES

Racial and ethnic disparities in healthcare delivery for acutely ill children are pervasive in the United States; it is unknown whether differential critical care utilization exists.

DESIGN

Retrospective study of the Pediatric Health Information System (PHIS) database.

SETTING

Multicenter database of academic children's hospitals in the United States.

PATIENTS

Children discharged from a PHIS hospital in 2019 with one of the top ten medical conditions where PICU utilization was present in greater than or equal to 5% of hospitalizations.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Race and ethnicity categories included Asian, Black, Hispanic, White, and other. Primary outcomes of interest were differences in rate of PICU admission, and for children requiring PICU care, total hospital length of stay (LOS). One-quarter (n = 44,200) of the 178,134 hospital discharges included a PICU admission. In adjusted models, Black children had greater adjusted odds ratio (aOR [95% CI]) of PICU admission in bronchiolitis (aOR, 1.08 [95% CI, 1.02-1.14]; p = 0.01), respiratory failure (aOR, 1.18 [95% CI, 1.10-1.28]; p < 0.001), seizure (aOR, 1.28 [95% CI, 1.08-1.51]; p = 0.004), and diabetic ketoacidosis (DKA) (aOR, 1.18 [95% CI, 1.05-1.32]; p = 0.006). Together, Hispanic, Asian, and other race children had greater aOR of PICU admission in five of the diagnostic categories, compared with White children. The geometric mean (± sd) hospital LOS ranged from 47.7 hours (± 2.1 hr) in croup to 206.6 hours (± 2.8 hr) in sepsis. After adjusting for demographics and illness severity, non-White children had longer LOS in respiratory failure, pneumonia, DKA, and sepsis.

CONCLUSIONS

The need for critical care to treat acute illness in children may be inequitable. Additional studies are needed to understand and eradicate differences in PICU utilization based on race and ethnicity.

Racial and ethnic disparities in common inpatient safety outcomes in a children's hospital cohort

BACKGROUND

Emerging evidence has shown racial and ethnic disparities in rates of harm for hospitalised children. Previous work has also demonstrated how highly heterogeneous approaches to collection of race and ethnicity data pose challenges to population-level analyses. This work aims to both create an approach to aggregating safety data from multiple hospitals by race and ethnicity and apply the approach to the examination of potential disparities in high-frequency harm conditions.

METHODS

In this cross-sectional, multicentre study, a cohort of hospitals from the Solutions for Patient Safety network with varying race and ethnicity data collection systems submitted validated central line-associated bloodstream infection (CLABSI) and unplanned extubation (UE) data stratified by patient race and ethnicity categories. Data were submitted using a crosswalk created by the study team that reconciled varying approaches to race and ethnicity data collection by participating hospitals. Harm rates for race and ethnicity categories were compared with reference values reflective of the cohort and broader children's hospital population.

RESULTS

Racial and ethnic disparities were identified in both harm types. Multiracial Hispanic, Combined Hispanic and Native Hawaiian or other Pacific Islander patients had CLABSI rates of 2.6-3.6 SD above reference values. For Black or African American patients, UE rates were 3.2-4.4 SD higher. Rates of both events in White patients were significantly lower than reference values.

CONCLUSIONS

The combination of harm data across hospitals with varying race and ethnicity collection systems was accomplished through iterative development of a race and ethnicity category framework. We identified racial and ethnic disparities in CLABSI and UE that can be addressed in future improvement work by identifying and modifying care delivery factors that contribute to safety disparities.

Discrepancies in Race and Ethnicity in the Electronic Health Record Compared to Self-report

OBJECTIVE

Racial and ethnic disparities are commonplace in health care. Research often relies on sociodemographic information recorded in the electronic health record (EHR). Little evidence is available about the accuracy of EHR-recorded sociodemographic information, and none in pediatrics. Our objective was to determine the accuracy of EHR-recorded race and ethnicity compared to self-report.

METHODS

Patients/guardians enrolled in two prospective observational studies (10/2014-1/2019) provided self-reported sociodemographic information. Corresponding EHR information was abstracted. EHR information was compared to self-report, considered "gold standard." Agreement was evaluated with Cohen's kappa.

RESULTS

A total of 503 patients (42% female, median age 12.8 years) were identified. Self-reported race (N = 484) was 73% White, 16% Black or African American (AA), 4% Asian, 5% multiracial, and 2% other. Self-reported ethnicity (N = 410) was 9% Hispanic/Latino, and 88% non-Hispanic/Latino. Agreement between self-reported and EHR-recorded race was substantial (kappa = 0.77, 95% CI 0.72-0.83). Race was discordant among 10% (47/476). Hispanic/Latino ethnicity also had strong agreement (kappa = 0.77, 95% CI 0.65-0.89). Among those who self-reported Hispanic/Latino and reported race (N = 21), race was less accurately recorded in the EHR (kappa = 0.26, 95% CI 0-0.54). Race did not match among 43% with recorded race (9/21). Among self-reported racial and/or ethnic minorities, 13% (12/164) were misclassified in the EHR as non-Hispanic White.

CONCLUSIONS

We found race and ethnicity are often inaccurately recorded in the EHR for patients who self-identify as minorities, leading to under-representation of minorities in the EHR. Inaccurately recorded race and ethnicity has important implications for disparity research, and for informing health policy. Reliable processes are needed to incorporate self-reported race and ethnicity in the EHR at institutional and national levels.

Reporting and Representation of Participant Race and Ethnicity in National Institutes of Health-Funded Pediatric Clinical Trials

Importance

Enrolling racially and ethnically diverse pediatric research participants is critical to ensuring equitable access to health advances and generalizability of research findings.

Objectives

To examine the reporting of race and ethnicity for National Institutes of Health (NIH)-funded pediatric clinical trials and to assess the representation of pediatric participants from different racial and ethnic groups compared with distributions in the US population.

Design, Setting, and Participants

This cross-sectional study included NIH-funded pediatric (ages 0-17 years) trials with grant funding completed between January 1, 2017, and December 31, 2019, and trial results reported as of June 30, 2022.

Exposures

National Institutes of Health policies and guidance statements on the reporting of race and ethnicity of participants in NIH-funded clinical trials.

Main Outcomes and Measures

The main outcome was reporting of participant race and ethnicity for NIH-funded pediatric clinical trials in publications and ClinicalTrials.gov.

Results

There were 363 NIH-funded pediatric trials included in the analysis. Reporting of race and ethnicity data was similar in publications and ClinicalTrials.gov, with 90.3% (167 of 185) of publications and 93.9% (77 of 82) of ClinicalTrial.gov reports providing data on race and/or ethnicity. Among the 160 publications reporting race, there were 43 different race classifications, with only 3 publications (1.9%) using the NIH-required categories. By contrast, in ClinicalTrials.gov, 61 reports (79.2%) provided participant race and ethnicity using the NIH-specified categories (P < .001). There was racially and ethnically diverse enrollment of pediatric participants, with overrepresentation of racial and ethnic minority groups compared with the US population.

Conclusions and Relevance

This cross-sectional study of NIH-funded pediatric clinical trials found high rates of reporting of participant race and ethnicity, with diverse representation of trial participants. These findings suggest that the NIH is meeting its directive of ensuring diverse participant enrollment in the research it supports.

Cancer Epidemiology in the Northeastern United States (2013-2017)

We tested the hypotheses that adult cancer incidence and mortality in the Northeast region and in Northern New England (NNE) were different than the rest of the United States, and described other related cancer metrics and risk factor prevalence. Using national, publicly available cancer registry data, we compared cancer incidence and mortality in the Northeast region with the United States and NNE with the United States overall and by race/ethnicity, using age-standardized cancer incidence and rate ratios (RR). Compared with the United States, age-adjusted cancer incidence in adults of all races combined was higher in the Northeast (RR, 1.07; 95% confidence interval [CI] 1.07-1.08) and in NNE (RR 1.06; CI 1.05-1.07). However compared with the United States, mortality was lower in the Northeast (RR, 0.98; CI 0.98-0.98) but higher in NNE (RR, 1.05; CI 1.03-1.06). Mortality in NNE was higher than the United States for cancers of the brain (RR, 1.16; CI 1.07-1.26), uterus (RR, 1.32; CI 1.14-1.52), esophagus (RR, 1.36; CI 1.26-1.47), lung (RR, 1.12; CI 1.09-1.15), bladder (RR, 1.23; CI 1.14-1.33), and melanoma (RR, 1.13; CI 1.01-1.27). Significantly higher overall cancer incidence was seen in the Northeast than the United States in all race/ethnicity subgroups except Native American/Alaska Natives (RR, 0.68; CI 0.64-0.72). In conclusion, NNE has higher cancer incidence and mortality than the United States, a pattern that contrasts with the Northeast region, which has lower cancer mortality overall than the United States despite higher incidence.

Significance

These findings highlight the need to identify the causes of higher cancer incidence in the Northeast and the excess cancer mortality in NNE.

Addressing pediatric surgical health inequities through quality improvement efforts

Concepts of healthcare quality and health equity should be inextricably linked but are often pursued separately. Quality improvement (QI) can serve as a powerful means to eliminate health inequities by adopting an equity-focused lens to diagnose and address baseline disparities among pediatric populations using targeted interventions. QI and pediatric surgery practitioners should integrate concepts of equity at every stage of formulating a QI project including conceptualization, planning, and execution. Early adaptation of an equity conscious perspective using QI methodology can prevent exacerbation of preexisting disparities while improving overall outcomes.

Evaluating Demographic Data to Improve Confidence in Equity Analytics in a Children's Hospital

Healthcare institutions are placing greater emphasis on equitable care. To accurately track and validate equity metrics, Akron Children's Hospital evaluated how key fields are collected, analyzed, and visualized throughout the organization. Standardized recommendations in this area vary, and this investigation provided specific ways to advance analytics in this field. In addition, the technical infrastructure needed a comprehensive evaluation to increase confidence in using demographic data.

Methods

First, we reviewed how staff are trained to collect data at registration. Next, the electronic health record team standardized race and ethnicity fields with federal definitions. We found that fields were not consistently accessible across reporting tools. However, when present, all fields are sourced from the same electronic health record field. Finally, 6 months of encounters were analyzed and validated, with limitations to a seldom-populated Race 2 field.

Results

We compared data, including and excluding null values, to provide concise recommendations for standard visualizations. We uncovered many consistencies and a few inconsistencies that informed the next steps.

Conclusions

The results informed 7 recommendations to align Akron Children's Hospital's advancement in analytics for health equity data: standardize race and ethnicity fields across all reporting tools, add Child Opportunity Index 2.0 to the enterprise data warehouse, utilize data at the time of the patient's encounter, include null fields (patient refused, unknown, and not specified) in analysis, increase reporting capabilities for social determinants of health (SDOH), standardize multiracial data visualizations, and optimize reliable upstream data collection to increase reliability for all health equity measures.

Neighborhood Socioeconomic Deprivation and Health Care Utilization of Medically Complex Children

OBJECTIVES

To assess the association between neighborhood socioeconomic deprivation and health care utilization in a cohort of children with medical complexity (CMC).

METHODS

Cross-sectional study of children aged <18 years receiving care in our institution's patient-centered medical home (PCMH) for CMC in 2016 to 2017. Home addresses were assigned to census tracts and a tract-level measure of socioeconomic deprivation (Deprivation Index with range 0-1, higher numbers represent greater deprivation). Health care utilization outcomes included emergency department visits, hospitalizations, inpatient bed days, and missed PCMH clinic appointments. To evaluate the independent association between area-level socioeconomic deprivation and utilization outcomes, multivariable Poisson and linear regression models were used to control for demographic and clinical covariates.

RESULTS

The 512 included CMC lived in neighborhoods with varying degrees of socioeconomic deprivation (median 0.32, interquartile range 0.26-0.42, full range 0.12-0.82). There was no association between area-level deprivation and emergency department visits (adjusted risk ratio [aRR] 0.98; 95% confidence interval [CI]: 0.93 to 1.04), hospitalizations (aRR 0.97; 95% CI: 0.92 to 1.01), or inpatient bed-days (aRR 1.00, 95% CI: 0.80 to 1.27). However, there was a 13% relative increase in the missed clinic visit rate for every 0.1 unit increase in Deprivation Index (95% CI: 8%-18%).

CONCLUSIONS

A child's socioeconomic context is associated with their adherence to PCMH visits. Our PCMH for CMC includes children living in neighborhoods with a range of socioeconomic deprivation and may blunt effects from harmful social determinants. Incorporating knowledge of the socioeconomic context of where CMC and their families live is crucial to ensure equitable health outcomes.

Sociodemographic and Appointment Factors Affecting Missed Opportunities to Provide Neonatal Ultrasound Imaging

PURPOSE

The aim of this study was to assess disparities in outpatient imaging missed care opportunities (IMCOs) for neonatal ultrasound by sociodemographic and appointment factors at a large urban pediatric hospital.

METHODS

A retrospective review was performed among patients aged 0 to 28 days receiving one or more outpatient appointments for head, hip, renal, or spine ultrasound at the main hospital or satellite sites from 2008 to 2018. An IMCO was defined as a missed ultrasound or cancellation <24 hours in advance. Population-average correlated logistic regression modeling estimated the odds of IMCOs for six sociodemographic (age, sex, race/ethnicity, language, insurance, and region of residence) and seven appointment (type of ultrasound, time, day, season, site, year, and distance to appointment) factors. The primary analysis included unknown values as a separate category, and the secondary analysis used multiple imputation to impute genuine categories from unknown variables.

RESULTS

The data set comprised 5,474 patients totaling 6,803 ultrasound appointments. IMCOs accounted for 4.4% of appointments. IMCOs were more likely for Black (odds ratio [OR], 3.31; P < .001) and other-race neonates (OR, 2.66; P < .001) and for patients with public insurance (OR, 1.78; P = .002). IMCOs were more likely for appointments at the main hospital compared with satellites (P < .001), during work hours (P = .021), and on weekends (P < .001). Statistical significance for primary and secondary analyses was quantitatively similar and qualitatively identical.

CONCLUSIONS

Marginalized racial groups and those with public insurance had a higher rate of IMCOs in neonatal ultrasound. This likely represents structural inequities faced by these communities, and more research is needed to identify interventions to address these inequities in care delivery for vulnerable neonatal populations.

Collection of patient race, ethnicity, and language data in emergency departments: a national survey

PURPOSE

There is mounting evidence of racial and ethnic discrimination in the Canadian health care system. Patient level race and ethnicity data are required to identify potential disparities in clinical outcomes and access to health care. However, it is not known what patient race, ethnicity, and language data are collected by Canadian hospitals. This gap limits opportunities to identify and address inequalities in the health care system. The emergency department (ED) is a major point of contact for many patients accessing the health care system, and is therefore a reasonable place to conduct analysis of patient data collection. This study aims to quantify the proportion of Canadian EDs that collect patient race, ethnicity, and primary language data.

METHODS

We identified all Canadian EDs and distributed a survey to 616 EDs across the country.

RESULTS

We received responses representing 202 EDs (32.8%). One fifth (20.3%) of responding EDs reported that they collected race and ethnicity data and 38.1% collected primary language data. Reported uses for these data included quality improvement, research, and direct patient care.

CONCLUSION

The majority of Canadian EDs do not collect patient race, ethnicity, and language data. This gap limits our ability to identify inequalities in health outcomes or access to health care. Lack of race, ethnicity, and language data also hinders our ability to develop and evaluate programs and interventions that aim to correct these inequalities.

Creating a health equity and inclusion office in an academic pediatric medical center: priorities addressed and lessons learned

BACKGROUND

Over the last two decades, medical schools and academic health centers have acknowledged the persistence of health disparities in their patients and the lack of diversity in their faculty, leaders and extended workforce. We established an Office of Health Equity and Inclusion (OHEI) at our pediatric academic medical center after a thorough evaluation of prior diversity initiatives and review of faculty development data.

OBJECTIVE

To describe the lessons learned at a pediatric academic medical center in prioritizing and implementing health equity, diversity and inclusion (EDI) initiatives in creating the OHEI.

MATERIALS AND METHODS

We reviewed internal administrative data and faculty development data, including data related to faculty who are underrepresented in medicine, to understand the role of our EDI initiatives in the strategic priorities addressed and lessons learned in the creation of the OHEI.

RESULTS

The intentional steps taken in our medical center's strategic approach in the creation of this office led to four important lessons to improve pediatric health equity: (1) board, senior executive and institutional prioritization of EDI initiatives; (2) multi-specialty and interprofessional collaboration; (3) academic approach to EDI programmatic development; and (4) intentionality with accountability in all EDI initiatives.

CONCLUSION

The key lessons learned during the creation of an Office of Health Equity and Inclusion can provide guidance to other academic health centers committed to implementing institutional priorities that focus their EDI initiatives on the improvement of pediatric health equity.

We are part of the problem: the role of children's hospitals in addressing health inequity

Racism is an ongoing public health crisis that undermines health equity for all children in hospitals across our nation. The presence and impact of institutionalized racism contributes to health inequity and is under described in the medical literature. In this review, we focus on key interdependent areas to foster inclusion, diversity, and equity in Children's Hospitals, including 1) promotion of workforce diversity 2) provision of anti-racist, equitable hospital patient care, and 3) prioritization of academic scholarship focused on health equity research, quality improvement, medical education, and advocacy. We discuss the implications for clinical and academic practice.Plain Language Summary: Racism in Children's Hospitals harms children. We as health-care providers and hospital systems are part of the problem. We reviewed the literature for the best ways to foster inclusion, diversity, and equity in hospitals. Hospitals can be leaders in improving child health equity by supporting a more diverse workforce, providing anti-racist patient care, and prioritizing health equity scholarship.

Using rising tides to lift all boats: Equity-focused quality improvement as a tool to reduce neonatal health disparities

Evidence of health disparities affecting newborns abounds. Although quality improvement (QI) methodology is often suggested as a tool to advance health equity, the impact of QI initiatives on disparities is variable. QI work may mitigate, worsen, or perpetuate existing disparities. QI projects designed without an intentional focus on equity promotion may foster intervention-generated inequalities that further disadvantage vulnerable groups. This article reviews disparities in perinatal and neonatal care, the impact of QI on health disparities, and the concept of "Equity-Focused Quality Improvement" (EF-QI). EF-QI differs from QI with an equity lens in that it is action-oriented and centered around equity. EF-QI initiatives purposely integrate equity throughout the fabric of the project and are inclusive, collaborative efforts that foreground and address the needs of disadvantaged populations. EF-QI principles are applicable at every stage of project conception, execution, analysis, and dissemination, and may provide opportunities for reducing disparities in neonatal care.