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

Cowden, John D.; Araujo, Gabriela; Chow, Tiffany W.; Rodriguez, Patricia; Chamblee, Tracy B.; Mackey, Megan; Lyren, Anne; Gutzeit, Michael F.

doi:10.1007/s40615-020-00716-8

Cited by 26 publications

(22 citation statements)

References 16 publications

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“…In constructing our neighborhoods, we were limited to using ZIP codes available in our EMR and were not able to use a neighborhood-level socioeconomic status indicator, which could be helpful in evaluating the difference in neighborhood-level IMCOs we found in our study. Finally, consistent with other literature on EMR data in pediatric hospitals [38], we had a considerable proportion of unknown data for some demographic variables: race/ethnicity (23%), insurance (20%), and language (6%). We addressed this by conducting two analyses, a primary analysis that included unknowns as a separate category and a secondary analysis in which unknowns were imputed.…”

Section: Discussionsupporting

confidence: 83%

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

Mateo

Johnston

Wilkinson

et al. 2022

Journal of the American College of Radiology

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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 ¼ .002). IMCOs were more likely for appointments at the main hospital compared with satellites (P < .001), during work hours (P ¼ .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.

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Section: Discussionsupporting

confidence: 83%

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

Mateo

Johnston

Wilkinson

et al. 2022

Journal of the American College of Radiology

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“…Collecting and understanding these data are linked directly to our commitment to identify and mitigate pediatric health care disparities and to develop interventions to eliminate them. Additionally, the OHEI collaborated closely with the Program for Patient Safety and Quality, Office of Experience, and the Information Services Department to improve the collection of race, ethnicity and language data [ 11 ] from our patients. With a deeper understanding of our patients’ demographic characteristics [ 11 ], the OHEI, Program for Patient Safety and Quality and other clinical and research collaborators can perform assessments of our health care interventions.…”

Section: Resultsmentioning

confidence: 99%

“…Additionally, the OHEI collaborated closely with the Program for Patient Safety and Quality, Office of Experience, and the Information Services Department to improve the collection of race, ethnicity and language data [ 11 ] from our patients. With a deeper understanding of our patients’ demographic characteristics [ 11 ], the OHEI, Program for Patient Safety and Quality and other clinical and research collaborators can perform assessments of our health care interventions. In short, we recognized that an intentional collaboration between the experts in health equity and the experts in quality and safety was essential; without an effective measurement and data collection strategy, there would be no accountability for the effects of health care policies or programs [ 1 ].…”

Section: Resultsmentioning

confidence: 99%

“…It is important to underscore that we operationalized these EDI initiatives, with multi-specialty and interprofessional collaboration among pediatric subspecialists (pediatric radiologists), pediatricians, nurses, researchers and senior executive hospital leaders. Intentional efforts to build EDI initiatives must be implemented within the overall institutional priorities of a medical center and include: developing equity-driven educational programming and research initiatives; creating training opportunities for health equity research; improving collection and analysis of pediatric patient race, ethnicity and language demographic data and health equity–quality metrics to identify and address health care disparities [ 11 , 22 ]; creating hospital-wide education to address unconscious biases, create inclusive learning and working environments in health care settings [ 23 ] and build pipeline programs at high school and college levels; and expanding faculty development and research grant programs to increase underrepresented faculty workforce diversity, retention and academic advancement/promotion [ 2 ]. The original data presented here provide the evidence for the priorities addressed and highlight the lessons learned in the creation of an office of health equity and inclusion within an academic medical center with the overall aim to be intentional in the important work to improve pediatric health equity.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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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 methodsWe 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. ResultsThe 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. ConclusionThe 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.

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“…The survey questionnaire was developed based on phrasing and language used in other studies on sociodemographic data [ 6 ]. We pilot tested the survey with three emergency physicians and refined it based on the feedback.…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2022

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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. Supplementary Information The online version contains supplementary material available at 10.1007/s43678-022-00388-9.

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

Cited by 26 publications

References 16 publications

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

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

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

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

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