Accuracy of race, ethnicity, and language preference in an electronic health record

"Racial mortality inversion": Black-white disparities in mortality among people experiencing homelessness in the United States

Disparities in mortality between Black and White people have long been observed. These disparities persist at all income levels. However, similar patterns in racial mortality disparities are not observed among people experiencing homelessness. Instead, studies in a handful of cities show a reversal in the Black-White mortality disparity in the United States: Black people experiencing homelessness are less likely to die compared to White people experiencing homelessness. We propose a theory of "racial mortality inversion" and test whether inverted Black-White mortality patterns are observable in homeless populations throughout the United States. Using a novel dataset of 18,618 homeless decedents in 20 localities across 10 states and the District of Columbia, we find consistent evidence for "racial mortality inversion" across time and place. Between 2015 and 2020, the aggregate White homeless mortality rate was 67.8%-138.4% higher than the rate for the Black homeless population. Inverted racial mortality rates were observed in all 20 localities and in nearly every year. Across the entire sample, higher average ages of death were also observed for Black people compared to White people experiencing homelessness in 5 of 6 years, though racial inversion in age was not consistent across localities. These findings offer novel insight into racial health disparities among people experiencing homelessness and may inform policies and programs that seek to prevent homelessness and homeless mortality across racial groups.

Risk management or racial Bias? The disparate use of restraints in the Emergency Department of an Urban Safety-Net Hospital

OBJECTIVES

Limited data exist on racial-ethnic differences in the application of restraints for patients visitng the emergency department (ED). This study examines whether there is an association between race and patient ED visit type with the application of four-point mechanical restraints in a high acuity safety-net urban academic hospital.

METHODS

The study retrospectively reviewed 198,610 visits to the ED at Boston Medical Center made by patients between 18 and 89 years old between May 1, 2014 and May 1, 2019. ED visit type was categorized based on primary billing code for the visit as either medical or behavioral; behavioral visits were further categorized into 5 groups based on corresponding primary psychiatric billing code category. The relationships between race/ethnicity and four-point mechanical restraints were analyzed using binary logistic regression models in SPSS.

RESULTS

1.4% of unique visits involved the use of four-point mechanical restraints. Patients with a behavioral visit were significantly over 16 times more likely to be restrained than those with a medical visit. Black patients were significantly more likely to be restrained than white patients for behavioral visits but less likely for medical visits. Black and Hispanic patients were also significantly more likely to be restrained for a behavioral visit regardless of psychiatric diagnosis. Asian patients were less likely to be restrained regardless of ED visit type.

CONCLUSIONS

Significant racial differences in restraints for White patients with medical visits and Black and Hispanic patients with behavioral visits prompts further investigation on the role of clinician bias when managing acute patients.

Racial Disparities in Palliative Care at End-of-life in Children with Advanced Heart Disease in the South

OBJECTIVE

To examine specialty pediatric palliative care (SPPC) and end-of-life (EOL) care for children with advanced heart disease in Alabama, including rates of and disparities in SPPC involvement.

STUDY DESIGN

We performed a retrospective study from electronic health records of children (≤21 years at death) who died with advanced heart disease at a single institution between 2012 and 2019 (n=128). The main outcome was SPPC consult; we assessed clinical and sociodemographic factors associated with SPPC.

RESULTS

The median age at death was 6 months (IQR=1-25 months) with 80 (63%) ≤1 year; 46% were Black and 45% non-Hispanic White. Seventy (55%) children had critical congenital heart disease, 45 (35%) non-critical congenital heart disease, and 13 (10%) acquired heart disease. Twenty-nine children (22%) received SPPC. Children ≤1 year at time of death and Black children were less likely to receive SPPC (adjusted odds ratio [95% confidence interval]: 0.2 [0.1-0.6], reference >1 year; 0.2 [0.1-0.7], reference non-Hispanic White). SPPC was associated with death while receiving comfort-focused care (30.6 [4.5-210]), do not resuscitate orders (8.2 [2.1-31.3]), and hospice enrollment (no children without SPPC care were enrolled in hospice) but not medically intense EOL care (ICU admission, mechanical ventilation, hemodialysis, or CPR) or death outside the ICU.

CONCLUSIONS

Children dying with advanced heart disease in Alabama did not have routine SPPC involvement; infants and Black children had lower odds of SPPC. SPPC was associated with more comfort-focused care. Disparities in SPPC utilization for children with advanced heart disease need further examination.

Exploring ethnicity dynamics in Wales: a longitudinal population-scale linked data study and development of a harmonised ethnicity spine

OBJECTIVE

This study aims to create a national ethnicity spine based on all available ethnicity records in linkable anonymised electronic health record and administrative data sources.

DESIGN

A longitudinal study using anonymised individual-level population-scale ethnicity data from 26 data sources available within the Secure Anonymised Information Linkage Databank.

SETTING

The national ethnicity spine is created based on longitudinal national data for the population of Wales-UK over 22 years (between 2000 and 2021).

PROCEDURE AND PARTICIPANTS

A total of 46 million ethnicity records for 4 297 694 individuals have been extracted, harmonised, deduplicated and made available within a longitudinal research ready data asset.

OUTCOME MEASURES

(1) Comparing the distribution of ethnicity records over time for four different selection approaches (latest, mode, weighted mode and composite) across age bands, sex, deprivation quintiles, health board and residential location and (2) distribution and completeness of records against the ONS census 2011.

RESULTS

The distribution of the dominant group (white) is minimally affected based on the four different selection approaches. Across all other ethnic group categorisations, the mixed group was most susceptible to variation in distribution depending on the selection approach used and varied from a 0.6% prevalence across the latest and mode approach to a 1.1% prevalence for the weighted mode, compared with the 3.1% prevalence for the composite approach. Substantial alignment was observed with ONS 2011 census with the Latest group method (kappa=0.68, 95% CI (0.67 to 0.71)) across all subgroups. The record completeness rate was over 95% in 2021.

CONCLUSION

In conclusion, our development of the population-scale ethnicity spine provides robust ethnicity measures for healthcare research in Wales and a template which can easily be deployed in other trusted research environments in the UK and beyond.

Racial and Ethnic Patient Care Disparities in Anesthesiology: History, Current State, and a Way Forward

Disparities in patient care and outcomes are well-documented in medicine but have received comparatively less attention in anesthesiology. Those disparities linked to racial and ethnic identity are pervasive, with compelling evidence in operative anesthesiology, obstetric anesthesiology, pain medicine, and critical care. This narrative review presents an overview of disparities in perioperative patient care that is grounded in historical context followed by potential solutions for mitigating disparities and inequities.

Incorporating Anti-racist Principles Throughout the Research Lifecycle: A Position Statement from the Society of General Internal Medicine (SGIM)

Biomedical research has advanced medicine but also contributed to widening racial and ethnic health inequities. Despite a growing acknowledgment of the need to incorporate anti-racist objectives into research, there remains a need for practical guidance for recognizing and addressing the influence of ingrained practices perpetuating racial harms, particularly for general internists. Through a review of the literature, and informed by the Research Lifecycle Framework, this position statement from the Society of General Internal Medicine presents a conceptual framework suggesting multi-level systemic changes and strategies for researchers to incorporate an anti-racist perspective throughout the research lifecycle. It begins with a clear assertion that race and ethnicity are socio-political constructs that have important consequences on health and health disparities through various forms of racism. Recommendations include leveraging a comprehensive approach to integrate anti-racist principles and acknowledging that racism, not race, drives health inequities. Individual researchers must acknowledge systemic racism's impact on health, engage in self-education to mitigate biases, hire diverse teams, and include historically excluded communities in research. Institutions must provide clear guidelines on the use of race and ethnicity in research, reject stigmatizing language, and invest in systemic commitments to diversity, equity, and anti-racism. National organizations must call for race-conscious research standards and training, and create measures to ensure accountability, establishing standards for race-conscious research for research funding. This position statement emphasizes our collective responsibility to combat systemic racism in research, and urges a transformative shift toward anti-racist practices throughout the research cycle.

Changes in Spirometry Interpretative Strategies: Implications for Classifying COPD and Predicting Exacerbations

BACKGROUND

Recent guidelines for spirometry interpretation recommend both race-neutral reference equations and use of z score thresholds to define severity of airflow obstruction.

RESEARCH QUESTION

How does the transition from race-specific to race-neutral equations impact severity classifications for patients with COPD when using % predicted vs z score thresholds, and do changes in severity correspond to clinical risk?

STUDY DESIGN AND METHODS

This retrospective cohort study included Black and White patients with COPD and available spirometry from the Johns Hopkins Health System. Global Lung Function Initiative (GLI) 2012 (race-specific) equations and GLI Global (race-neutral) equations were used to determine FEV1 % predicted and z score values. Patients were classified as having mild, moderate, or severe disease according to % predicted or z score thresholds. Associations between a change in severity classification from race-specific to race-neutral with COPD exacerbations and all-cause hospitalizations were evaluated using logistic regression.

RESULTS

This cohort included 13,324 patients, of whom 9,232 patients (69.3%) were White (mean age, 65.7 years) and 4,092 patients (30.7%) were Black (mean age, 61.1 years). More Black than White patients showed a change in severity classification between approaches when using % predicted thresholds (20.2% vs 6.1%; P < .001), but not with z score thresholds (12.6% vs 12.3%; P = .68). An increased severity classification with a race-neutral approach was associated with increased risk of exacerbation when using z score thresholds (OR, 2.34; 95% CI, 1.51-3.63), but not when using % predicted thresholds (OR, 1.08; 95% CI, 0.61-1.93). A decreased severity classification with a race-neutral approach was associated with lower risk of exacerbation with both % predicted (OR, 0.49; 95% CI, 0.28-0.87) and z score (OR 0.67; 95% CI, 0.50-0.90) thresholds.

INTERPRETATION

The proportions of Black and White individuals reclassified were similar with z score thresholds, and changes in severity corresponded to clinical risk with z scores. These results support recent recommendations for use of race-neutral equations and z score thresholds for spirometry interpretation.

Community collaboration to advance racial/ethnic equity in colorectal Cancer screening: Protocol for a multilevel intervention to improve screening and follow-up in community Health centers

INTRODUCTION

Colorectal cancer (CRC) screening utilization is low among low-income, uninsured, and minority populations that receive care in community health centers (CHCs). There is a need for evidence-based interventions to increase screening and follow-up care in these settings.

METHODS

A multilevel, multi-component pragmatic cluster randomized controlled trial is being conducted at 8 CHCs in two metropolitan areas (Boston and Los Angeles), with two arms: (1) Mailed FIT outreach with text reminders, and (2) Mailed FIT-DNA with patient support. We also include an additional CHC in Rapid City (South Dakota) that follows a parallel protocol for FIT-DNA but is not randomized due to lack of a comparison group. Eligible individuals in participating clinics are primary care patients ages 45-75, at average-risk for CRC, and overdue for CRC screening. Participants with abnormal screening results are offered navigation for follow-up colonoscopy and CRC risk assessment.

RESULTS

The primary outcome is the completion rate of CRC screening at 90 days. Secondary outcomes include the screening completion rate at 180 days and the rate of colonoscopy completion within 6 months among participants with an abnormal result. Additional goals are to enhance our understanding of facilitators and barriers to CRC risk assessment in CHC settings.

CONCLUSIONS

This study assesses the effectiveness of two multilevel interventions to increase screening participation and follow-up after abnormal screening in under-resourced clinical settings, informing future efforts to address CRC disparities.

TRIAL REGISTRATION

NCT05714644.

Prevalence of Late-Stage Parkinson's Disease in the US Healthcare System: Insights from TriNetX

BACKGROUND

Patients in late-stage Parkinson's disease (PDLS) are caregiver-dependent, have low quality of life, and higher healthcare costs.

OBJECTIVE

To estimate the prevalence of PDLS patients in the current US healthcare system.

METHODS

We downloaded the 2010-2022 data from the TriNetX Diamond claims network that consists of 92 US healthcare sites. PD was identified using standard diagnosis codes, and PDLS was identified by the usage of wheelchair dependence, personal care assistance, and/or presence of diagnoses of dementia. Age of PDLS identification and survival information were obtained and stratified by demographic and the disability subgroups.

RESULTS

We identified 1,031,377 PD patients in the TriNetX database. Of these, 18.8% fitted our definition of PDLS (n = 194,297), and 10.2% met two or more late-stage criteria. Among all PDLS, the mean age of PDLS identification was 78.1 (±7.7) years, and 49% were already reported as deceased. PDLS patients were predominantly male (58.5%) with similar distribution across PDLS subgroups. The majority did not have race (71%) or ethnicity (69%) information, but for the available information >90% (n = 53,162) were White, 8.2% (n = 5121) Hispanic/Latino, 7.8% (n = 4557) Black, and <0.01% (n = 408) Asian. Of the PDLS cohort, 71.6% identified with dementia, 12.9% had personal care assistance, and 4.8% were wheelchair-bound.

CONCLUSIONS

Late-stage patients are a significant part of the PD landscape in the current US healthcare system, and largely missed by traditional motor-based disability staging. It is imperative to include this population as a clinical, social, and research priority. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The Impact of Social Vulnerability on Structural and Functional Glaucoma Severity, Worsening, and Variability

PURPOSE

To determine the associations between social vulnerability index (SVI) and baseline severity, worsening, and variability of glaucoma, as assessed by visual field (VF) and OCT.

DESIGN

Retrospective longitudinal cohort study.

PARTICIPANTS

Adults with glaucoma or glaucoma suspect status in 1 or both eyes. Visual fields were derived from 7897 eyes from 4482 patients, while OCTs were derived from 6271 eyes from 3976 patients. All eyes had a minimum of 5 tests over follow-up using either the Humphrey Field Analyzer or the Cirrus HD-OCT.

METHODS

Social vulnerability index, which measures neighborhood-level environmental factors, was linked to patients' addresses at the census tract level. Rates of change in mean deviation (MD) and retinal nerve fiber layer (RNFL) thickness were computed using linear regression. The slope of the regression line was used to assess worsening, while the standard deviation of residuals was used as a measure of variability. Multivariable linear mixed-effects models were used to investigate the impact of SVI on baseline, worsening, and variability in both MD and RNFL. We further explored the interaction effect of mean intraocular pressure (IOP) and SVI on worsening in MD and RNFL.

MAIN OUTCOME MEASURES

Glaucoma severity defined based on baseline MD and RNFL thickness. Worsening defined as MD and RNFL slope. Variability defined as the standard deviation of the residuals obtained from MD and RNFL slopes.

RESULTS

Increased (worse) SVI was significantly associated with worse baseline MD (β = -1.07 dB, 95% confidence interval [CI]: [-1.54, -0.60]), thicker baseline RNFL (β = 2.46 μm, 95% CI: [0.75, 4.17]), greater rates of RNFL loss (β = -0.12 μm, 95% CI: [-0.23, -0.02]), and greater VF variability (β = 0.16 dB, 95% CI: [0.07, 0.24]). Having worse SVI was associated with worse RNFL loss with increases in IOP (βinteraction = -0.07, 95% CI: [-0.12, -0.02]).

CONCLUSIONS

Increased SVI score is associated with worse functional (VF) loss at baseline, higher rates of structural (OCT) worsening over time, higher VF variability, and a greater effect of IOP on RNFL loss. Further studies are needed to enhance our understanding of these relationships and establish their cause.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Racial and ethnic associations with comprehensive cancer center access and clinical trial enrollment for acute leukemia

BACKGROUND

Clinical trial participation at Comprehensive Cancer Centers (CCC) is inequitable for minoritized racial and ethnic groups with acute leukemia. CCCs care for a high proportion of adults with acute leukemia. It is unclear if participation inequities are due to CCC access, post-access enrollment, or both.

METHODS

We conducted a retrospective cohort study of adults with acute leukemia (2010-2019) residing within Massachusetts, the designated catchment area of the Dana-Farber/Harvard Cancer Center (DF/HCC). Individuals were categorized as non-Hispanic Asian (NHA), Black (NHB), White (NHW), Hispanic White (HW), or Other. Decomposition analyses assessed covariate contributions to disparities in (1) access to DF/HCC care and (2) post-access enrollment.

RESULTS

Of 3698 individuals with acute leukemia, 85.9% were NHW, 4.5% HW, 4.3% NHB, 3.7% NHA, and 1.3% Other. Access was lower for HW (age- and sex-adjusted OR = 0.64, 95% CI = 0.45 to 0.90) and reduced post-access enrollment for HW (aOR = 0.54, 95% CI =0.34 to 0.86) and NHB (aOR = 0.60, 95% CI = 0.39 to 0.92) compared to NHW. Payor and socioeconomic status (SES) accounted for 25.2% and 21.2% of the +1.1% absolute difference in HW access. Marital status and SES accounted for 8.0% and 7.0% of the -8.8% absolute disparity in HW enrollment; 76.4% of the disparity was unexplained. SES and marital status accounted for 8.2% and 7.1% of the -9.1% absolute disparity in NHB enrollment; 73.0% of the disparity was unexplained.

CONCLUSIONS

A substantial proportion of racial and ethnic inequities in acute leukemia trial enrollment at CCCs are from post-access enrollment, the majority of which was not explained by sociodemographic factors.

Association between language discordance and unplanned hospital readmissions or emergency department revisits: a systematic review and meta-analysis

BACKGROUND AND OBJECTIVE

Studies conflict about whether language discordance increases rates of hospital readmissions or emergency department (ED) revisits for adult and paediatric patients. The literature was systematically reviewed to investigate the association between language discordance and hospital readmission and ED revisit rates.

DATA SOURCES

Searches were performed in PubMed, Embase and Google Scholar on 21 January 2021, and updated on 27 October 2022. No date or language limits were used.

STUDY SELECTION

Articles that (1) were peer-reviewed publications; (2) contained data about patient or parental language skills and (3) included either unplanned hospital readmission or ED revisit as one of the outcomes, were screened for inclusion. Articles were excluded if: unavailable in English; contained no primary data or inaccessible in a full-text form (eg, abstract only).

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently extracted data using Preferred Reporting Items for Systematic Reviews and Meta-Analyses-extension for scoping reviews guidelines. We used the Newcastle-Ottawa Scale to assess data quality. Data were pooled using DerSimonian and Laird random-effects models. We performed a meta-analysis of 18 adult studies for 28-day or 30-day hospital readmission; 7 adult studies of 30-day ED revisits and 5 paediatric studies of 72-hour or 7-day ED revisits. We also conducted a stratified analysis by whether access to interpretation services was verified/provided for the adult readmission analysis.

MAIN OUTCOMES AND MEASURES

Odds of hospital readmissions within a 28-day or 30-day period and ED revisits within a 7-day period.

RESULTS

We generated 4830 citations from all data sources, of which 49 (12 paediatric; 36 adult; 1 with both adult and paediatric) were included. In our meta-analysis, language discordant adult patients had increased odds of hospital readmissions (OR 1.11, 95% CI 1.04 to 1.18). Among the 4 studies that verified interpretation services for language discordant patient-clinician interactions, there was no difference in readmission (OR 0.90, 95% CI 0.77 to 1.05), while studies that did not specify interpretation service access/use found higher odds of readmission (OR 1.14, 95% CI 1.06 to 1.22). Adult patients with a non-dominant language preference had higher odds of ED revisits (OR 1.07, 95% CI 1.004 to 1.152) compared with adults with a dominant language preference. In 5 paediatric studies, children of parents language discordant with providers had higher odds of ED revisits at 72 hours (OR 1.12, 95% CI 1.05 to 1.19) and 7 days (OR 1.02, 95% CI 1.01 to 1.03) compared with patients whose parents had language concordant communications.

DISCUSSION

Adult patients with a non-dominant language preference have more hospital readmissions and ED revisits, and children with parents who have a non-dominant language preference have more ED revisits. Providing interpretation services may mitigate the impact of language discordance and reduce hospital readmissions among adult patients.

PROSPERO REGISTRATION NUMBER

CRD42022302871.

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.

Epidemiology and prevalence of dementia and Alzheimer's disease in American Indians: Data from the Strong Heart Study

INTRODUCTION

Accurate epidemiologic estimates for dementia are lacking for American Indians, despite substantive social and health disparities.

METHODS

The Strong Heart Study, a population-based cohort of 11 American Indian tribes, conducted detailed cognitive testing and examinations over two visits approximately 7 years apart. An expert panel reviewed case materials for consensus adjudication of cognitive status (intact; mild cognitive impairment [MCI]; dementia; other impaired/not MCI) and probable etiology (Alzheimer's disease [AD], vascular bain injury [VBI], traumatic brain injury [TBI], other).

RESULTS

American Indians aged 70-95 years had 54% cognitive impairment including 10% dementia. VBI and AD were primary etiology approximately equal proportions (>40%). Apolipoprotein (APO) Eε4 carriers were more common among those with dementia (p = 0.040). Plasma pTau, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) were higher among those with cognitive impairment, but not amyloid beta (Aβ). Cognitive intact had mean 3MSE 92.2 (SD 6.4) and mean Montreal Cognitive Assessment (MoCA) score of 21.3 (SD 3.2).

DISCUSSION

This is the first population-based study to estimate the prevalence of vascular and Alzheimer's dementias in a population-based study of American Indians.

HIGHLIGHTS

The Strong Heart Study is a population-based cohort of American Indian tribes, conducted over 30+ years and three US geographic regions (Northern Plains, Southern Plains, Southwest). Our teams conducted detailed cognitive testing, neurological examination, and brain imaging over two visits approximately 7 years apart. An expert panel reviewed collected materials for consensus-based adjudication of cognitive status (intact; MCI; dementia; other impaired/not MCI) and probable underlying etiology (AD; VBI; TBI; other). In this cohort of American Indians aged 70-95, 54% were adjudicated with cognitive impairment, including approximately 35% MCI and 10% dementia. These data expand on prior reports from studies using electronic health records, which had suggested prevalence, and incidence of dementia in American Indians to be more comparable to the majority population or non-Hispanic White individuals, perhaps due to latent case undercounts in clinical settings. Vascular and neurodegenerative injuries were approximately equally responsible for cognitive impairment, suggesting that reduction of cardiovascular disease is needed for primary prevention. Traumatic injury was more prevalent than in other populations, and common among those in the "other/not MCI" cognitive impairment category. Mean scores for common dementia screening instruments-even among those adjudicated as unimpaired-were relatively low compared to other populations (mean unimpaired 3MSE 92.2, SD 6.4; mean unimpaired MoCA 21.3, SD 3.2), suggesting the need for cultural and environmental adaptation of common screening and evaluation instruments.

Implementing paper-based patient-reported outcome collection within outpatient integrative health and medicine

OBJECTIVE

To investigate the feasibility of pre- and post-encounter patient-reported outcome (PRO) measure collection within an outpatient integrative health and medicine (IHM) clinic and to characterize factors associated with successful completion.

METHODS

We conducted a retrospective review of 27,464 outpatient IHM encounters including 9,520 chiropractic; 8,237 acupuncture; 5,847 massage; 2,345 IHM consultation; and 1,515 osteopathic manipulation treatment encounters at four clinics offering IHM over 18 months. Patients were asked to complete paper questionnaires rating pain, anxiety, and stress from 0-10 immediately pre- and post-encounter. Generalized linear mixed effect regression models were used to examine the relationship between demographic, clinical, and operational covariates and completing (1) pre-encounter and (2) paired (i.e., pre and post) PROs.

RESULTS

Patients (N = 5587, mean age 49 years, 74% white, 77% female) generally presented for musculoskeletal conditions (81.7%), with a chief complaint of pain (55.1%). 21,852 (79.6%) encounters were among patients who completed pre-encounter PROs; 11,709/21,852 (53.6%) completed subsequent post-encounter PROs. Odds of PRO completion were more impacted by provider, operational, and clinical-level factors than patient factors. Covariates associated with increased odds of pre-encounter PRO completion included being female, having additional IHM encounters, and having a pain or anxiety complaint. Covariates associated with increased odds of paired PRO completion included being aged 31-40 vs. 51-60 years and having additional IHM encounters.

CONCLUSION

Implementing a paper-based PRO collection system in outpatient IHM is feasible; however, collecting post-encounter PROs was challenging. Future endeavors should leverage the electronic health record and patient portals to optimize PRO collection and engage patients and clinical providers.

Leveraging Novel Clinical Decision Support to Improve Preferred Language Documentation in a Neonatal Intensive Care Unit

BACKGROUND

 Recognition of the patient and family's diverse backgrounds and language preference is critical for communicating effectively. In our hospital's electronic health record, a patient or family's identified language for communication is documented in a discrete field known as "preferred language." This field serves as an interdepartmental method to identify patients with a non-English preferred language, creating a bolded banner for non-English speakers easily identifiable by health care professionals. Despite the importance of documenting preferred language to facilitate equitable care, this field is often blank.

OBJECTIVES

 Using the Institute for Healthcare Improvement's Model for Improvement, our team sought to increase preferred language documentation within the neonatal intensive care unit (NICU) from a baseline of 74% in September 2021 to above 90% within 6 months.

METHODS

 A multidisciplinary team was assembled to address preferred language documentation. Our team incorporated guidance regarding preferred language documentation into a novel clinical decision support (CDS) tool aimed at addressing various safety and quality measures within the NICU. Our primary outcome metric was documentation of family's preferred language. Process measures included overall compliance with the CDS tool. A secondary outcome was the assessment of preferred language documentation accuracy.

RESULTS

 The average rate of preferred language documentation increased from a baseline of 74 to 92% within 6 months and is currently sustained at 96%. Moreover, our follow-up assessments found that 100% of a random sample of contacted patients (n = 88) had their language preferences documented correctly. Overall compliance with the CDS tool remained at 85% throughout the project.

CONCLUSION

 Using a quality improvement framework coupled with a CDS initiative, our team was able to successfully and accurately improve preferred language documentation in our NICU. Future projects include strategies for more equitable care for patients with non-English preferences such as improved interpreter usage and discharge instructions in their preferred language.

Ascertaining the Francophone population in Ontario: validating the language variable in health data

BACKGROUND

Language barriers can impact health care and outcomes. Valid and reliable language data is central to studying health inequalities in linguistic minorities. In Canada, language variables are available in administrative health databases; however, the validity of these variables has not been studied. This study assessed concordance between language variables from administrative health databases and language variables from the Canadian Community Health Survey (CCHS) to identify Francophones in Ontario.

METHODS

An Ontario combined sample of CCHS cycles from 2000 to 2012 (from participants who consented to link their data) was individually linked to three administrative databases (home care, long-term care [LTC], and mental health admissions). In total, 27,111 respondents had at least one encounter in one of the three databases. Language spoken at home (LOSH) and first official language spoken (FOLS) from CCHS were used as reference standards to assess their concordance with the language variables in administrative health databases, using the Cohen kappa, sensitivity, specificity, positive predictive value (PPV), and negative predictive values (NPV).

RESULTS

Language variables from home care and LTC databases had the highest agreement with LOSH (kappa = 0.76 [95%CI, 0.735-0.793] and 0.75 [95%CI, 0.70-0.80], respectively) and FOLS (kappa = 0.66 for both). Sensitivity was higher with LOSH as the reference standard (75.5% [95%CI, 71.6-79.0] and 74.2% [95%CI, 67.3-80.1] for home care and LTC, respectively). With FOLS as the reference standard, the language variables in both data sources had modest sensitivity (53.1% [95%CI, 49.8-56.4] and 54.1% [95%CI, 48.3-59.7] in home care and LTC, respectively) but very high specificity (99.8% [95%CI, 99.7-99.9] and 99.6% [95%CI, 99.4-99.8]) and predictive values. The language variable from mental health admissions had poor agreement with all language variables in the CCHS.

CONCLUSIONS

Language variables in home care and LTC health databases were most consistent with the language often spoken at home. Studies using language variables from administrative data can use the sensitivity and specificity reported from this study to gauge the level of mis-ascertainment error and the resulting bias.

Sociotechnical feasibility of natural language processing-driven tools in clinical trial eligibility prescreening for Alzheimer's disease and related dementias

BACKGROUND

Alzheimer's disease and related dementias (ADRD) affect over 55 million globally. Current clinical trials suffer from low recruitment rates, a challenge potentially addressable via natural language processing (NLP) technologies for researchers to effectively identify eligible clinical trial participants.

OBJECTIVE

This study investigates the sociotechnical feasibility of NLP-driven tools for ADRD research prescreening and analyzes the tools' cognitive complexity's effect on usability to identify cognitive support strategies.

METHODS

A randomized experiment was conducted with 60 clinical research staff using three prescreening tools (Criteria2Query, Informatics for Integrating Biology and the Bedside [i2b2], and Leaf). Cognitive task analysis was employed to analyze the usability of each tool using the Health Information Technology Usability Evaluation Scale. Data analysis involved calculating descriptive statistics, interrater agreement via intraclass correlation coefficient, cognitive complexity, and Generalized Estimating Equations models.

RESULTS

Leaf scored highest for usability followed by Criteria2Query and i2b2. Cognitive complexity was found to be affected by age, computer literacy, and number of criteria, but was not significantly associated with usability.

DISCUSSION

Adopting NLP for ADRD prescreening demands careful task delegation, comprehensive training, precise translation of eligibility criteria, and increased research accessibility. The study highlights the relevance of these factors in enhancing NLP-driven tools' usability and efficacy in clinical research prescreening.

CONCLUSION

User-modifiable NLP-driven prescreening tools were favorably received, with system type, evaluation sequence, and user's computer literacy influencing usability more than cognitive complexity. The study emphasizes NLP's potential in improving recruitment for clinical trials, endorsing a mixed-methods approach for future system evaluation and enhancements.

Screening tools to address social determinants of health in the United States: A systematic review

The Centers for Medicare & Medicaid Services have mandated that hospitals implement measures to screen social determinants of health (SDoH). We sought to report on available SDoH screening tools. PubMed, Scopus, Web of Science, as well as the grey literature were searched (1980 to November 2023). The included studies were US-based, written in English, and examined a screening tool to assess SDoH. Thirty studies were included in the analytic cohort. The number of questions in any given SDoH assessment tool varied considerably and ranged from 5 to 50 (mean: 16.6). A total of 19 SDoH domains were examined. Housing (n = 23, 92%) and safety/violence (n = 21, 84%) were the domains assessed most frequently. Food/nutrition (n = 17, 68%), income/financial (n = 16, 64%), transportation (n = 15, 60%), family/social support (n = 14, 56%), utilities (n = 13, 52%), and education/literacy (n = 13, 52%) were also commonly included domains in most screening tools. Eighteen studies proposed specific interventions to address SDoH. SDoH screening tools are critical to identify various social needs and vulnerabilities to help develop interventions to address patient needs. Moreover, there is marked heterogeneity of SDoH screening tools, as well as the significant variability in the SDoH domains assessed by currently available screening tools.

Regression with race-modifiers: towards equity and interpretability

The pervasive effects of structural racism and racial discrimination are well-established and offer strong evidence that the effects of many important variables on health and life outcomes vary by race. Alarmingly, standard practices for statistical regression analysis introduce racial biases into the estimation and presentation of these race-modified effects. We introduce abundance-based constraints (ABCs) to eliminate these racial biases. ABCs offer a remarkable invariance property: estimates and inference for main effects are nearly unchanged by the inclusion of race-modifiers. Thus, quantitative researchers can estimate race-specific effects "for free"-without sacrificing parameter interpretability, equitability, or statistical efficiency. The benefits extend to prominent statistical learning techniques, especially regularization and selection. We leverage these tools to estimate the joint effects of environmental, social, and other factors on 4th end-of-grade readings scores for students in North Carolina (n = 27, 638) and identify race-modified effects for racial (residential) isolation, PM2.5 exposure, and mother's age at birth.

Accuracy of patient race and ethnicity data in a central cancer registry

PURPOSE

Race and Hispanic ethnicity data can be challenging for central cancer registries to collect. We evaluated the accuracy of the race and Hispanic ethnicity variables collected by the Utah Cancer Registry compared to self-report.

METHODS

Participants were 3,162 cancer survivors who completed questionnaires administered in 2015-2022 by the Utah Cancer Registry. Each survey included separate questions collecting race and Hispanic ethnicity, respectively. Registry-collected race and Hispanic ethnicity were compared to self-reported values for the same individuals. We calculated sensitivity and specificity for each race category and Hispanic ethnicity separately.

RESULTS

Survey participants included 323 (10.2%) survivors identifying as Hispanic, a lower proportion Hispanic than the 12.1% in the registry Hispanic variable (sensitivity 88.2%, specificity 96.5%). For race, 43 participants (1.4%) self-identified as American Indian or Alaska Native (AIAN), 32 (1.0%) as Asian, 23 (0.7%) as Black or African American, 16 (0.5%) Pacific Islander (PI), and 2994 (94.7%) as White. The registry race variable classified a smaller proportion of survivors as members of each of these race groups except White. Sensitivity for classification of race as AIAN was 9.3%, Asian 40.6%, Black 60.9%, PI 25.0%, and specificity for each of these groups was > 99%. Sensitivity and specificity for White were 98.8% and 47.4%.

CONCLUSION

Cancer registry race and Hispanic ethnicity data often did not match the individual's self-identification. Of particular concern is the high proportion of AIAN individuals whose race is misclassified. Continued attention should be directed to the accurate capture of race and ethnicity data by hospitals.

Regression with race-modifiers: towards equity and interpretability

The pervasive effects of structural racism and racial discrimination are well-established and offer strong evidence that the effects of many important variables on health and life outcomes vary by race. Alarmingly, standard practices for statistical regression analysis introduce racial biases into the estimation and presentation of these race-modified effects. We introduce abundance-based constraints (ABCs) to eliminate these racial biases. ABCs offer a remarkable invariance property: estimates and inference for main effects are nearly unchanged by the inclusion of race-modifiers. Thus, quantitative researchers can estimate race-specific effects "for free"-without sacrificing parameter interpretability, equitability, or statistical efficiency. The benefits extend to prominent statistical learning techniques, especially regularization and selection. We leverage these tools to estimate the joint effects of environmental, social, and other factors on 4th end-of-grade readings scores for students in North Carolina (n = 27, 638) and identify race-modified effects for racial (residential) isolation, PM2.5 exposure, and mother's age at birth.

Unique Breast Cancer Screening Disparities in a Safety-Net Health System

INTRODUCTION

Breast cancer screening (BCS) disparities leave historically underserved groups more vulnerable to adverse outcomes. This study explores granular associations between BCS and patient sociodemographic factors in a large urban safety-net health system.

METHODS

A retrospective review among female patients ages 50-74 within an urban safety-net health system was conducted in 2019. All patients had a primary care visit in the past 2 years. Multiple patient health and sociodemographic characteristics were reviewed, as well as provider gender and specialty. Bivariate analyses and multivariable logistic regression were performed in 2022.

RESULTS

The BCS rate among 11,962 women was 69.7%. Over half of patients were non-White (63.6%) and had public insurance (72.3%). Patients with limited English proficiency made up 44.3% of the cohort. Compared to their sociodemographic counterparts, patients with White race, English proficiency, and Medicare insurance had the lowest rates of BCS. Serious mental illness and substance use disorder were associated with lower odds of BCS. In multivariable analysis, when using White race and English speakers as a reference, most other races (Black, Hispanic, and Other) and languages (Spanish, Portuguese, and Other) had significantly higher odds of screening ranging from 8% to 63% higher, except Asian race and Haitian Creole language. Female (versus male) and internal medicine-trained providers were associated with higher screening odds.

CONCLUSIONS

Multiple unique variables contribute to BCS disparities, influenced by patient and health system factors. Defining and understanding the interplay of these variables can guide policymaking and identify avenues to improve BCS for vulnerable or traditionally under-resourced populations.

Development of an Equity, Diversity, and Inclusion Committee for a collaborative quality improvement network: Pediatric Cardiac Critical Care Consortium (PC4) Equity, Diversity and Inclusion (EDI) Committee: white paper 2023

Racial and ethnic disparities are well described in paediatric cardiac critical care outcomes. However, understanding the mechanisms behind these outcomes and implementing interventions to reduce and eliminate disparities remain a gap in the field of paediatric cardiac critical care. The Pediatric Cardiac Critical Care Consortium (PC4) established the Equity, Diversity, and Inclusion (EDI) Committee in 2020 to promote an equity lens to its aim of improving paediatric cardiac critical care quality and outcomes across North America. The PC4 EDI Committee is working to increase research, quality improvement, and programming efforts to work towards health equity. It also aims to promote health equity considerations in PC4 research. In addition to a focus on patient outcomes and research, the committee aims to increase the inclusion of Black, Indigenous, and People of Color (BIPOC) members in the PC4 collaborative. The following manuscript outlines the development, structure, and aims of the PC4 EDI Committee and describes an analysis of social determinants of health in published PC4 research.

Race and Ethnic Representation in Crohn's Disease Trials of Biologic and Small Molecule Medications: A Systematic Review and Meta-analysis

BACKGROUND AND AIMS

Randomised controlled trials historically under-represent marginalised racial and ethnic populations. As incidence and prevalence of Crohn's disease in these groups rise, it is important to characterise their inclusion in randomised controlled trials on first-line and pipe-line medications.

METHODS

PubMed was searched systematically for randomised controlled trials of biologic and small molecule inhibitor [SMI] medications, with a primary outcome related to efficacy following PRISMA guidelines. We used descriptive statistics to summarise demographic variables and meta-regression analyses to estimate temporal trends in racial inclusion.

RESULTS

More than a half of trials did not report any racial/ethnic demographics [53.7%] and several reported racial demographics for only one race [20.9%]. When racial data were reported, Whites made up 90.2% of participants. Percentages of Black, Asian, Native American/Pacific Islander, and participants considered 'Other' averaged 2.9%, 11.6%, 0.5%, and 1.6% out of the total sample sizes of 3901, 3742, 828 and 4027, respectively. Proportional representation of White participants decreased over time [p <0.01] and proportional representation of Asian participants increased over time [p = 0.047]. In ordinal logistic regression, mean year of trial enrolment significantly increased the number of racial groups reported [p <0.001].

CONCLUSIONS

Half of published randomised controlled trials in Crohn's disease contain no racial or ethnic demographics, and the remaining often only have limited inclusion of Black, Native American/Pacific Islander, and Hispanic patients. Further work should characterise representation in observational and prospective trials. Researchers should work to: 1] increase reporting of racial and ethnic demographics; and 2] improve recruitment and retention of marginalised populations.

Pediatric oral food challenges in the outpatient setting: A single-center experience

Background

Oral food challenge (OFC) is the criterion standard for diagnosing food allergy (FA). It is important to have parameters to aid in selecting ideal OFC candidates.

Objective

We sought to characterize outcomes and predictors of OFCs for common food allergens.

Methods

We completed a retrospective chart review of all OFCs for IgE-mediated FA performed at Duke University pediatric allergy clinics from June 2017 through May 2022. Patients were deemed eligible for milk, egg, and nut OFC if testing revealed a specific IgE level not exceeding 2 kU/L and a skin prick test (SPT) resulting in a wheal size not exceeding 5 mm. Different parameters were followed for selecting candidates for baked challenge.

Results

A total of 663 OFCs were conducted on 510 patients (59% male). The most common foods challenged were peanut (26%), plain egg (23%), baked egg (8%), and milk (8%), with pass rates of 84%, 88%, 62%, and 84%, respectively. Of the patients who failed OFC, 84% had objective symptoms, 23% had multisystemic reactions, and 15% required epinephrine. Although the presence of a personal or family history of atopy or prior failed OFC was not associated with outcomes, a history of anaphylaxis (regardless of the trigger) was associated with increased risk of failure.

Conclusion

Although there are no established consensus guidelines, our study provides a benchmark illustrating that cutoffs of a specific IgE level not exceeding 2 kU/L and SPT finding not exceeding 5 mm result in a failure rate of approximately 13% for nonbaked milk, nonbaked egg, and nuts. The high rate of failed baked egg OFCs is likely related to selection bias, but our results illustrate the low negative predictive value of ovomucoid.

Are There Racial Disparities in Perioperative Pain? A Retrospective Study of a Gynecological Surgery Cohort

PURPOSE

The purpose of this study was to examine whether racial disparities exist in immediate postoperative pain scores and intraoperative analgesic regimens in a single surgical cohort.

DESIGN

A single-center, retrospective analysis.

METHODS

This retrospective study of a single surgical cohort was conducted via chart review of the existing electronic health record. A total of 203 patients who underwent minimally invasive hysterectomy were included in the analysis. Three initially reviewed patient records were excluded from the final analysis due to the small size of their racial cohorts (two Asian or Pacific Islander and one Native American). The White patients (n = 103) and Black patients (n = 100) were compared for differences in pain scores in the postanesthesia care unit (PACU). The patients' intraoperative analgesic regimens were also compared.

FINDINGS

There were no significant differences between races in the postoperative pain scores in the PACU or in the analgesia administered by the anesthesia provider intraoperatively.

CONCLUSIONS

In this specific population, there was no evidence of racial disparities in postoperative pain or intraoperative analgesia administration. Further research is needed to understand the unique factors of the perioperative period, to see if the absence of disparities in this study is repeated in other cohorts, and to mitigate any disparities that are found.

Identifying and improving the "ground truth" of race in disparities research through improved EMR data reporting. A systematic review

BACKGROUND

Studies about racial disparities in healthcare are increasing in quantity; however, they are subject to vast differences in definition, classification, and utilization of race/ethnicity data. Improved standardization of this information can strengthen conclusions drawn from studies using such data. The objective of this study is to examine how data related to race/ethnicity are recorded in research through examining articles on race/ethnicity health disparities and examine problems and solutions in data reporting that may impact overall data quality.

METHODS

In this systematic review, Business Source Complete, Embase.com, IEEE Xplore, PubMed, Scopus and Web of Science Core Collection were searched for relevant articles published from 2000 to 2020. Search terms related to the concepts of electronic medical records, race/ethnicity, and data entry related to race/ethnicity were used. Exclusion criteria included articles not in the English language and those describing pediatric populations. Data were extracted from published articles. This review was organized and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement for systematic reviews.

FINDINGS

In this systematic review, 109 full text articles were reviewed. Weaknesses and possible solutions have been discussed in current literature, with the predominant problem and solution as follows: the electronic medical record (EMR) is vulnerable to inaccuracies and incompleteness in the methods that research staff collect this data; however, improved standardization of the collection and use of race data in patient care may help alleviate these inaccuracies.

INTERPRETATION

Conclusions drawn from large datasets concerning peoples of certain race/ethnic groups should be made cautiously, and a careful review of the methodology of each publication should be considered prior to implementation in patient care.

Development and validation of a risk model for hospital-acquired venous thrombosis: the Medical Inpatients Thrombosis and Hemostasis study

BACKGROUND

Regulatory organizations recommend assessing hospital-acquired (HA) venous thromboembolism (VTE) risk for medical inpatients.

OBJECTIVES

To develop and validate a risk assessment model (RAM) for HA-VTE in medical inpatients using objective and assessable risk factors knowable at admission.

METHODS

The development cohort included people admitted to medical services at the University of Vermont Medical Center (Burlington, Vermont) between 2010 and 2019, and the validation cohorts included people admitted to Hennepin County Medical Center (Minneapolis, Minnesota), University of Michigan Medical Center (Ann Arbor, Michigan), and Harris Health Systems (Houston, Texas). Individuals with VTE at admission, aged <18 years, and admitted for <1 midnight were excluded. We used a Bayesian penalized regression technique to select candidate HA-VTE risk factors for final inclusion in the RAM.

RESULTS

The development cohort included 60 633 admissions and 227 HA-VTE, and the validation cohorts included 111 269 admissions and 651 HA-VTE. Seven HA-VTE risk factors with t statistics ≥1.5 were included in the RAM: history of VTE, low hemoglobin level, elevated creatinine level, active cancer, hyponatremia, increased red cell distribution width, and malnutrition. The areas under the receiver operating characteristic curve and calibration slope were 0.72 and 1.10, respectively. The areas under the receiver operating characteristic curve and calibration slope were 0.70 and 0.93 at Hennepin County Medical Center, 0.70 and 0.87 at the University of Michigan Medical Center, and 0.71 and 1.00 at Harris Health Systems, respectively. The RAM performed well stratified by age, sex, and race.

CONCLUSION

We developed and validated a RAM for HA-VTE in medical inpatients. By quantifying risk, clinicians can determine the potential benefits of measures to reduce HA-VTE.

Prevalence of neuromyelitis optica spectrum disorder in the United States

BACKGROUND

Neuromyelitis optic spectrum disorder (NMOSD) is a rare demyelinating, autoimmune disease and the burden in United States is not well characterized.

OBJECTIVE

The objective of this study was to determine the 2022 US prevalence of NMOSD.

METHODS

We constructed a cross-sectional study using aggregated electronic health record data for 25.7 million patients who had a 2022 clinical encounter. The data originated from the TriNetX US Collaborative Network of 55 healthcare organizations that span all 50 states. NMOSD prevalence was determined by querying for age-interval, sex, and race combinations, with direct standardization to the 2022 US Census data.

RESULTS

There were 1772 NMOSD patients among 25,743,039 patients for a prevalence of 6.88/100,000. Prevalence was the highest in Blacks (12.99/100,000) who represented 27.7% of NMOSD patients, then Asians (9.41/100,000and Whites (5.58/100,000). Among females, the prevalence of NMOSD was 9.48/100,000, and Black and Asian females had a 2.65- and 1.94-times higher prevalence than White females. In males, the prevalence of NMOSD was 3.52/100,000 and it did not differ by race. We observed a 3/5:1 female-to-male ratio in NMOSD. The age- and sex-adjusted 2022 estimate of persons with NMOSD in the United States was 15,413 females and 6233 males.

CONCLUSION

We estimate that there were near 22,000 Americans living with NMOSD in 2022.

Racial disparities in septic shock mortality: a retrospective cohort study

Background

Patients with septic shock have the highest risk of death from sepsis, however, racial disparities in mortality outcomes in this cohort have not been rigorously investigated. Our objective was to describe the association between race/ethnicity and mortality in patients with septic shock.

Methods

Our study is a retrospective cohort study of adult patients in the OneFlorida Data Trust (Florida, United States of America) admitted with septic shock between January 2012 and July 2018. We identified patients as having septic shock if they received vasopressors during their hospital encounter and had either an explicit International Classification of Disease (ICD) code for sepsis, or had an infection ICD code and received intravenous antibiotics. Our primary outcome was 90-day mortality. Our secondary outcome was in-hospital mortality. Multiple logistic regression with Least Absolute Shrinkage and Selection Operator (LASSO) for variable selection was used to assess associations.

Findings

There were 13,932 patients with septic shock in our cohort. The mean age was 61 years (SD 16), 68% of the cohort identified as White (n = 9419), 28% identified as Black (n = 3936), 2% (n = 294) identified as Hispanic ethnicity, and 2% as other races not specified in the previous groups (n = 283). In our logistic regression model for 90-day mortality, patients identified as Black had 1.57 times the odds of mortality (95% CI 1.07-2.29, p = 0.02) compared to White patients. Other significant predictors included mechanical ventilation (OR 3.66, 95% CI 3.35-4.00, p < 0.01), liver disease (OR 1.75, 95% CI 1.59-1.93, p < 0.01), laboratory components of the Sequential Organ Failure Assessment score (OR 1.18, 95% CI 1.16-1.21, p < 0.01), lactate (OR 1.10, 95% CI 1.08-1.12, p < 0.01), congestive heart failure (OR 1.19, 95% CI 1.10-1.30, p < 0.01), human immunodeficiency virus (OR 1.35, 95% CI 1.04-1.75, p = 0.03), age (OR 1.04, 95% CI 1.04-1.04, p < 0.01), and the interaction between age and race (OR 0.99, 95% CI 0.99-1.00, p < 0.01). Among younger patients (<45 years), patients identified as Black accounted for a higher proportion of the deaths. Results were similar in the in-hospital mortality model.

Interpretation

In this retrospective study of septic shock patients, we found that patients identified as Black had higher odds of mortality compared to patients identified as non-Hispanic White. Our findings suggest that the greatest disparities in mortality are among younger Black patients with septic shock.

Funding

National Institutes of Health National Center for Advancing Translational Sciences (1KL2TR001429); National Institute of Health National Institute of General Medical Sciences (1K23GM144802).

Effectiveness of Medical Music Therapy Practice: Integrative Research Using the Electronic Health Record: Rationale, Design, and Population Characteristics

Background: Several clinical trials support the efficacy of music therapy (MT) for improving outcomes in hospitalized patients, but few studies have evaluated the real-world delivery and integration of MT across multiple medical centers. This article describes the rationale, design, and population characteristics of a retrospective study examining the delivery and integration of MT within a large health system. Methods: A retrospective electronic health record (EHR) review was conducted of hospitalized patients seen by and/or referred to MT between January 2017 and July 2020. MT was provided across ten medical centers, including an academic medical center, a freestanding cancer center, and eight community hospitals. Discrete demographic, clinical, and MT treatment and referral characteristics were extracted from the EHR, cleaned, and organized using regular expressions functions, and they were summarized using descriptive statistics. Results: The MT team (average 11.6 clinical fulltime equivalent staff/year) provided 14,261 sessions to 7378 patients across 9091 hospitalizations. Patients were predominantly female (63.7%), White (54.3%) or Black/African American (44.0%), 63.7 ± 18.5 years of age at admission, and insured under Medicare (51.1%), Medicaid (18.1%), or private insurance (14.2%). Patients' hospitalizations (median length of stay: 5 days) were primarily for cardiovascular (11.8%), respiratory (9.9%), or musculoskeletal (8.9%) conditions. Overall, 39.4% of patients' hospital admissions included a mental health diagnosis, and 15.4% were referred to palliative care. Patients were referred by physicians (34.7%), nurses (29.4%), or advanced practice providers (24.7%) for coping (32.0%), anxiety reduction (20.4%), or pain management (10.1%). Therapists provided sessions to patients discharged from medical/surgical (74.5%), oncology (18.4%), or intensive care (5.8%) units. Conclusions: This retrospective study indicates that MT can be integrated across a large health system for addressing the needs of socioeconomically diverse patients. However, future research is needed to assess MT's impact on health care utilization (i.e., length of stay and rates of readmission) and immediate patient-reported outcomes.

Methods for retrospectively improving race/ethnicity data quality: a scoping review

Improving race and ethnicity (hereafter, race/ethnicity) data quality is imperative to ensure underserved populations are represented in data sets used to identify health disparities and inform health care policy. We performed a scoping review of methods that retrospectively improve race/ethnicity classification in secondary data sets. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, searches were conducted in the MEDLINE, Embase, and Web of Science Core Collection databases in July 2022. A total of 2 441 abstracts were dually screened, 453 full-text articles were reviewed, and 120 articles were included. Study characteristics were extracted and described in a narrative analysis. Six main method types for improving race/ethnicity data were identified: expert review (n = 9; 8%), name lists (n = 27, 23%), name algorithms (n = 55, 46%), machine learning (n = 14, 12%), data linkage (n = 9, 8%), and other (n = 6, 5%). The main racial/ethnic groups targeted for classification were Asian (n = 56, 47%) and White (n = 51, 43%). Some form of validation evaluation was included in 86 articles (72%). We discuss the strengths and limitations of different method types and potential harms of identified methods. Innovative methods are needed to better identify racial/ethnic subgroups and further validation studies. Accurately collecting and reporting disaggregated data by race/ethnicity are critical to address the systematic missingness of relevant demographic data that can erroneously guide policymaking and hinder the effectiveness of health care practices and intervention.

Treatment Patterns by Race and Ethnicity in Newly Diagnosed Persons with Multiple Sclerosis

BACKGROUND

Non-Hispanic Black and Hispanic persons with MS (pwMS) are more likely to experience rapid disease progression and severe disability than non-Hispanic White pwMS; however, it is unknown how the initiation of high-efficacy disease-modifying therapies (DMTs) differs by race/ethnicity. This real-world study describes DMT treatment patterns in newly diagnosed pwMS in the United States (US) overall and by race/ethnicity.

METHODS

This retrospective analysis used the US Optum Market Clarity claims/electronic health records database (January 2015-September 2020). pwMS who were first diagnosed in 2016 or later and initiated any DMT in the two years following diagnosis were included. Continuous enrollment in the claims data for ≥ 12 months before and ≥ 24 months after diagnosis was required. Treatment patterns 2 years after diagnosis were analyzed descriptively overall and by race/ethnicity.

RESULTS

The sample included 682 newly diagnosed and treated pwMS (non-Hispanic Black, n = 99; non-Hispanic White, n = 479; Hispanic, n = 35; other/unknown race/ethnicity, n = 69). The mean time from diagnosis to DMT initiation was 4.9 months in all pwMS. Glatiramer acetate and dimethyl fumarate were the most common first-line DMTs in non-Hispanic Black (28% and 20% respectively) and Hispanic pwMS (31%, 29%); however, glatiramer acetate and ocrelizumab were the most common in non-Hispanic White pwMS (33%, 18%). Use of first-line high-efficacy DMTs was limited across all race/ethnicity subgroups (11-29%), but uptake increased in non-Hispanic Black and White pwMS over the study period.

CONCLUSION

Use of high-efficacy DMTs was low across all race/ethnicity subgroups of newly diagnosed pwMS in the US, including populations at a greater risk of experiencing rapid disease progression and severe disability.

Lipid-lowering therapy and LDL-C control for primary prevention in persons with diabetes across 90 health systems in the United States

Objective

National guidelines recommend statin therapy for patients with type 2 diabetes. We assessed the extent of moderate- to high-intensity statin therapy utilization in community practice.

Methods

We evaluated lipid-lowering therapy (LLT) and low-density lipoprotein cholesterol (LDL-C) levels at baseline and 1-year follow-up in patients aged 40-75 years with type 2 diabetes but without atherosclerotic cardiovascular disease (ASCVD), across 90 health systems in the United States participating in an electronic health record-derived dataset, Cerner Real-World Data. Multivariable logistic regression was used to evaluate factors associated with utilization of moderate- to high-intensity statin.

Results

We identified 241,232 patients with type 2 diabetes (58.1 % on moderate- to high-intensity statin, 7.0 % on low-intensity statin, and 34.9 % on no statin). Predictors of moderate- to high-intensity statin therapy included retinopathy (adjusted odds ratio [aOR], 1.26; 95 % confidence interval [CI], 1.15-1.38), hypertension (aOR, 1.52; 95 % CI, 1.43-1.61), and stage 3 chronic kidney disease (aOR, 1.14; 95 % CI, 1.07-1.21). Women (aOR, 0.85; 95 % CI, 0.82-0.87), and those with rheumatoid arthritis (aOR, 0.79; 95 % CI, 0.71-0.87), psoriasis (aOR, 0.85; 95 % CI, 0.75-0.96), and hepatitis C (aOR, 0.40; 95 % CI, 0.39-0.46), had reduced odds of moderate- to high-intensity statin treatment. Utilization of ezetimibe was rare (2.0 %). LDL-C control was suboptimal at baseline (37.0 % and 27.9 % had LDL-C ≥100 mg/dL and <70 mg/dL, respectively). At 1-year follow-up, the rate of moderate- to high-intensity statin therapy utilization was 65.3 %.

Conclusion

Increased efforts are needed to improve LDL-C control and LLT use for primary prevention of ASCVD in adults with type 2 diabetes, in particular among women and those with risk-enhancing inflammatory conditions.

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.

Exploring the impact of missingness on racial disparities in predictive performance of a machine learning model for emergency department triage

Objective

To investigate how missing data in the patient problem list may impact racial disparities in the predictive performance of a machine learning (ML) model for emergency department (ED) triage.

Materials and Methods

Racial disparities may exist in the missingness of EHR data (eg, systematic differences in access, testing, and/or treatment) that can impact model predictions across racialized patient groups. We use an ML model that predicts patients' risk for adverse events to produce triage-level recommendations, patterned after a clinical decision support tool deployed at multiple EDs. We compared the model's predictive performance on sets of observed (problem list data at the point of triage) versus manipulated (updated to the more complete problem list at the end of the encounter) test data. These differences were compared between Black and non-Hispanic White patient groups using multiple performance measures relevant to health equity.

Results

There were modest, but significant, changes in predictive performance comparing the observed to manipulated models across both Black and non-Hispanic White patient groups; c-statistic improvement ranged between 0.027 and 0.058. The manipulation produced no between-group differences in c-statistic by race. However, there were small between-group differences in other performance measures, with greater change for non-Hispanic White patients.

Discussion

Problem list missingness impacted model performance for both patient groups, with marginal differences detected by race.

Conclusion

Further exploration is needed to examine how missingness may contribute to racial disparities in clinical model predictions across settings. The novel manipulation method demonstrated may aid future research.

Opportunistic assessment of ischemic heart disease risk using abdominopelvic computed tomography and medical record data: a multimodal explainable artificial intelligence approach

Current risk scores using clinical risk factors for predicting ischemic heart disease (IHD) events-the leading cause of global mortality-have known limitations and may be improved by imaging biomarkers. While body composition (BC) imaging biomarkers derived from abdominopelvic computed tomography (CT) correlate with IHD risk, they are impractical to measure manually. Here, in a retrospective cohort of 8139 contrast-enhanced abdominopelvic CT examinations undergoing up to 5 years of follow-up, we developed multimodal opportunistic risk assessment models for IHD by automatically extracting BC features from abdominal CT images and integrating these with features from each patient's electronic medical record (EMR). Our predictive methods match and, in some cases, outperform clinical risk scores currently used in IHD risk assessment. We provide clinical interpretability of our model using a new method of determining tissue-level contributions from CT along with weightings of EMR features contributing to IHD risk. We conclude that such a multimodal approach, which automatically integrates BC biomarkers and EMR data, can enhance IHD risk assessment and aid primary prevention efforts for IHD. To further promote research, we release the Opportunistic L3 Ischemic heart disease (OL3I) dataset, the first public multimodal dataset for opportunistic CT prediction of IHD.

Adapting a model of cervical carcinogenesis to self-identified Black women to evaluate racial disparities in the United States

BACKGROUND

Self-identified Black women in the United States have higher cervical cancer incidence and mortality than the general population, but these differences have not been clearly attributed across described cancer care inequities.

METHODS

A previously established microsimulation model of cervical cancer was adapted to reflect demographic, screening, and survival data for Black US women and compared with a model reflecting data for all US women. Each model input with stratified data (all-cause mortality, hysterectomy rates, screening frequency, screening modality, follow-up, and cancer survival) was sequentially replaced with Black-race specific data to arrive at a fully specified model reflecting Black women. At each step, we estimated the relative contribution of inputs to observed disparities.

RESULTS

Estimated (hysterectomy-adjusted) cervical cancer incidence was 8.6 per 100 000 in the all-race model vs 10.8 per 100 000 in the Black-race model (relative risk [RR] = 1.24, range = 1.23-1.27). Estimated all-race cervical cancer mortality was 2.9 per 100 000 vs 5.5 per 100 000 in the Black-race model (RR = 1.92, range = 1.85-2.00). We found the largest contributors of incidence disparities were follow-up from positive screening results (47.3% of the total disparity) and screening frequency (32.7%). For mortality disparities, the largest contributor was cancer survival differences (70.1%) followed by screening follow-up (12.7%).

CONCLUSION

To reduce disparities in cervical cancer incidence and mortality, it is important to understand and address differences in care access and quality across the continuum of care. Focusing on the practices and policies that drive differences in treatment and follow-up from cervical abnormalities may have the highest impact.

Associations of Race With Sedation Depth Among Mechanically Ventilated Adults: A Retrospective Cohort Study

OBJECTIVES

To evaluate the association of race with proportion of time in deep sedation among mechanically ventilated adults.

DESIGN

Retrospective cohort study from October 2017 to December 2019.

SETTING

Five hospitals within a single health system.

PATIENTS

Adult patients who identified race as Black or White who were mechanically ventilated for greater than or equal to 24 hours in one of 12 medical, surgical, cardiovascular, cardiothoracic, or mixed ICUs.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The exposure was White compared with Black race. The primary outcome was the proportion of time in deep sedation during the first 48 hours of mechanical ventilation, defined as Richmond Agitation-Sedation Scale values of -3 to -5. For the primary analysis, we performed mixed-effects linear regression models including ICU as a random effect, and adjusting for age, sex, English as preferred language, body mass index, Elixhauser comorbidity index, Laboratory-based Acute Physiology Score, Version 2, ICU admission source, admission for a major surgical procedure, and the presence of septic shock. Of the 3337 included patients, 1242 (37%) identified as Black, 1367 (41%) were female, and 1002 (30%) were admitted to a medical ICU. Black patients spent 48% of the first 48 hours of mechanical ventilation in deep sedation, compared with 43% among White patients in unadjusted analysis. After risk adjustment, Black race was significantly associated with more time in early deep sedation (mean difference, 5%; 95% CI, 2-7%; p < 0.01).

CONCLUSIONS

There are disparities in sedation during the first 48 hours of mechanical ventilation between Black and White patients across a diverse set of ICUs. Future work is needed to determine the clinical significance of these findings, given the known poorer outcomes for patients who experience early deep sedation.

Racial, Ethnic, and Socioeconomic Disparities in Out-of-Hospital Pain Management for Patients With Long Bone Fractures

STUDY OBJECTIVE

To evaluate racial and ethnic disparities in out-of-hospital analgesic administration, accounting for the influence of clinical characteristics and community socioeconomic vulnerability, among a national cohort of patients with long bone fractures.

METHODS

Using the 2019-2020 ESO Data Collaborative, we retrospectively analyzed emergency medical services (EMS) records for 9-1-1 advanced life support transport of adult patients diagnosed with long bone fractures at the emergency department. We calculated adjusted odds ratios (aOR) and 95% confidence intervals (CI) for out-of-hospital analgesic administration by race and ethnicity, accounting for age, sex, insurance, fracture location, transport time, pain severity, and scene Social Vulnerability Index. We reviewed a random sample of EMS narratives without analgesic administration to identify whether other clinical factors or patient preferences could explain differences in analgesic administration by race and ethnicity.

RESULTS

Among 35,711 patients transported by 400 EMS agencies, 81% were White, non-Hispanic, 10% were Black, non-Hispanic, and 7% were Hispanic. In crude analyses, Black, non-Hispanic patients with severe pain were less likely to receive analgesics compared with White, non-Hispanic patients (59% versus 72%; Risk Difference: -12.5%, 95% CI: -15.8% to -9.9%). After adjustment, Black, non-Hispanic patients remained less likely to receive analgesics compared with White, non-Hispanic patients (aOR:0.65, 95% CI:0.53 to 0.79). Narrative review identified similar rates of patients declining analgesics offered by EMS and analgesic contraindications across racial and ethnic groups.

CONCLUSIONS

Among EMS patients with long bone fractures, Black, non-Hispanic patients were substantially less likely to receive out-of-hospital analgesics compared with White, non-Hispanic patients. These disparities were not explained by differences in clinical presentations, patient preferences, or community socioeconomic conditions.

Uptake of Cervical Cancer Screening Among Female Patients Using a Mobile Medical Clinic

INTRODUCTION

Although cervical cancer causes morbidity, it can be prevented if diagnosed early; previous research has shown lower rates of screening in patients with health-related social needs by self-report data. This study assessed cervical cancer screening uptake among female patients with health-related social needs who access care through a community-based mobile medical clinic.

METHODS

A retrospective cohort was developed of all cis-female patients aged 21-65 years who sought care at the mobile medical clinic between January 1, 2016 and December 31, 2019, and their medical data were captured from the electronic health record. Bivariate and multivariate logistic regression (performed in 2022/2023) were used to investigate correlates of ever having received cervical cancer screening and of being up to date with cervical cancer screening.

RESULTS

Less than half of the 1,455 patient cohort had ever undergone Pap testing. In the multivariate model, ever having received cervical cancer screening was directly associated with being Hispanic or Black, living with HIV, and having received human papillomavirus vaccination. People who currently smoke showed significantly lower odds of ever having had cervical cancer screening than people who have never smoked. Patients who were single or had other marital status had lower adjusted odds of being up to date as well as those with a substance use history and those with unstable housing.

CONCLUSIONS

Cervical cancer screening rates in this community-based mobile medical clinic model were low, highlighting a need for increased attention to screening in this high-risk population. Mobile medical clinics have increased screening uptake internationally, and this model could be adopted domestically to promote screening to patients who access health care in various settings.

Are Depression and Anxiety Underdiagnosed in Socially Vulnerable Patients With Inflammatory Bowel Disease?

INTRODUCTION

Depression and anxiety are highly prevalent among individuals with inflammatory bowel disease (IBD); however, little is understood about how social determinants of health (SDOH) may impact mental health diagnoses in this population. The social vulnerability index (SVI) is a publicly available tool that can be used to study SDOH in IBD patients.

METHODS

Home addresses from a retrospective cohort of IBD patients at a single center were used to geocode patients to their individual census tract and corresponding SVI. We used multivariable logistic regression to examine the relationship between SVI and comorbid mental health diagnoses in patients with IBD. Secondarily, data from standardized health questionnaires were then used to determine if patients were adequately screened for depression and anxiety.

RESULTS

In all, 9644 patients were included; 18% had a diagnosis of depression, 21% anxiety, and 32% had a composite of "any mental health diagnosis." Depression (odds ratio [OR], 1.27; 95% confidence interval [CI], 1.02-1.56) but not anxiety (OR, 0.87; 95% CI, 0.71-1.06) nor "any mental health diagnosis" (OR, 1.09; 95% CI, 0.92-1.30) was associated with higher levels of social vulnerability. However, overall rates of screening for depression and anxiety were low (15% and 8%, respectively), with the lowest screening rates among the most socially vulnerable (depression 8.2%, anxiety 6.3%).

CONCLUSIONS

Disparities in the diagnoses of depression and anxiety for socially vulnerable patients with IBD exist. Awareness of these inequities is the first step toward developing interventions to improve mental health screening, eliminate barriers and bias, and promote referrals for appropriate mental health management.

Cancer center-based follow-up among pediatric and adolescent/young adult cancer survivors: the role of a community-based organization and the social determinants of health

PURPOSE

Adherence to survivorship care is suboptimal among pediatric and adolescent/young adult (AYA) cancer survivors. We evaluated predictors of cancer center-based follow-up among pediatric/AYA cancer survivors, with an emphasis on social determinants of health (SDOH).

METHODS

This retrospective cohort study used electronic health record data at an academic medical center to identify patients aged 0-29 years at last cancer treatment who completed treatment 2010-2019. Cancer center-based follow-up was defined by oncology or survivorship clinic visits through 12/31/2022. Multivariate logistic regression models (overall, ages 0-19 [pediatric], 20-29 [YA]) evaluated the association of demographics, clinical/treatment characteristics, and SDOH (insurance type, distance to cancer center, area deprivation index) with clinic attendance. Further modeling accounted for the service area of a community-based organization (CBO) that supports families of children with cancer.

RESULTS

A total of 2210 survivors were included (56% pediatric, 44% YA; 66% non-White). Cancer center-based follow-up decreased from 94% 1-year post-treatment to 35% at > 5-7 years. In adjusted analysis, AYAs had the lowest follow-up (5-7 years post-treatment: OR 0.25 [0.15-0.41] for age 25-29; OR 0.25 [0.16-0.41] for age 20-24; OR 0.32 [0.20-0.52] for age 15-19). Survivors residing within the CBO service area were twice as likely to follow-up (OR 2.10 [1.34-3.29]).

CONCLUSIONS

Among a diverse population, AYA survivors were vulnerable to loss to follow-up. Other SDOH were not consistently associated with follow-up. Support from a CBO may partly explain these findings.

IMPLICATIONS FOR CANCER SURVIVORS

CBOs may strengthen survivorship follow-up within medically underserved communities. More research is needed to understand community support in survivorship.

Racial and Ethnic Disparities in Cervical Cancer Screening From Three U.S. Healthcare Settings

INTRODUCTION

This study sought to characterize racial and ethnic disparities in cervical cancer screening and follow-up of abnormal findings across 3 U.S. healthcare settings.

METHODS

Data were from 2016 to 2019 and were analyzed in 2022, reflecting sites within the Multi-level Optimization of the Cervical Cancer Screening Process in Diverse Settings & Populations Research Center, part of the Population-based Research to Optimize the Screening Process consortium, including a safety-net system in the southwestern U.S., a northwestern mixed-model system, and a northeastern integrated healthcare system. Screening uptake was evaluated among average-risk patients (i.e., no previous abnormalities) by race and ethnicity as captured in the electronic health record, using chi-square tests. Among patients with abnormal findings requiring follow-up, the proportion receiving colposcopy or biopsy within 6 months was reported. Multivariable regression was conducted to assess how clinical, socioeconomic, and structural characteristics mediate observed differences.

RESULTS

Among 188,415 eligible patients, 62.8% received cervical cancer screening during the 3-year study period. Screening use was lower among non-Hispanic Black patients (53.2%) and higher among Hispanic (65.4%,) and Asian/Pacific Islander (66.5%) than among non-Hispanic White patients (63.5%, all p<0.001). Most differences were explained by the distribution of patients across sites and differences in insurance. Hispanic patients remained more likely to screen after controlling for a variety of clinical and sociodemographic factors (risk ratio=1.14, CI=1.12, 1.16). Among those receiving any screening test, Black and Hispanic patients were more likely to receive Pap-only testing (versus receiving co-testing). Follow-up from abnormal results was low for all groups (72.5%) but highest among Hispanic participants (78.8%, p<0.001).

CONCLUSIONS

In a large cohort receiving care across 3 diverse healthcare settings, cervical cancer screening and follow-up were below 80% coverage targets. Lower screening for Black patients was attenuated by controlling for insurance and site of care, underscoring the role of systemic inequity. In addition, it is crucial to improve follow-up after abnormalities are identified, which was low for all populations.

The accuracy of race & ethnicity data in US based healthcare databases: A systematic review

BACKGROUND

The availability and accuracy of data on a patient's race/ethnicity varies across databases. Discrepancies in data quality can negatively impact attempts to study health disparities.

METHODS

We conducted a systematic review to organize information on the accuracy of race/ethnicity data stratified by database type and by specific race/ethnicity categories.

RESULTS

The review included 43 studies. Disease registries showed consistently high levels of data completeness and accuracy. EHRs frequently showed incomplete and/or inaccurate data on the race/ethnicity of patients. Databases had high levels of accurate data for White and Black patients but relatively high levels of misclassification and incomplete data for Hispanic/Latinx patients. Asians, Pacific Islanders, and AI/ANs are the most misclassified. Systems-based interventions to increase self-reported data showed improvement in data quality.

CONCLUSION

Data on race/ethnicity that is collected with the purpose of research and quality improvement appears most reliable. Data accuracy can vary by race/ethnicity status and better collection standards are needed.

A Health System Framework for Addressing Structural Racism: Mass General Brigham's United Against Racism Initiative

The legacy of racism and structural inequality has taken a heavy toll on the health care system and the health outcomes of patients and members of community catchment areas. To achieve optimal health outcomes for all, health systems will need to enact structural change that is meaningful, measurable, and rooted in evidence. We describe an antiracism campaign organized into three pillars of focus (Leadership/Employees/Culture, Patient Care Equity, and Community Health and Policy Advocacy) and implemented across Mass General Brigham, a large integrated health system in the northeast of the United States. Our study ranges from the foundational to the aspirational and examples of data-driven areas of focus, programs (e.g., staff education, social risk mitigation, and new models of clinical service), and metrics developed for the health care workforce, patients, and surrounding communities are presented.

Disparities in Misclassification of Race and Ethnicity in Electronic Medical Records Among Patients with Traumatic Injury

Systems-level barriers to self-reporting of race and ethnicity reduce the integrity of data entered into the medical record and trauma registry among patients with injuries, limiting research assessing the burden of racial disparities. We sought to characterize misclassification of self-identified versus hospital-recorded racial and ethnic identity data among 10,513 patients with traumatic injuries. American Indian/Alaska Native patients (59.9%) and Native Hawaiian/Pacific Islander patients (52.4%) were most likely to be misclassified. Most Hispanic/Latin(x) patients preferred to only be identified as Hispanic/Latin(x) (73.2%) rather than a separate race category (e.g., White). Incorrect identification of race/ethnicity also has substantial implications for the perceived demographics of patient population; according to the medical record, 82.3% of the population were White, although only 70.6% were self-identified as White. The frequency of misclassification of race and ethnicity for persons of color limits research validity on racial and ethnic injury disparities.

Area-Based Sociodemographic Factors Associated with Latent Tuberculosis Infection in a Low-Prevalence Setting

Area-based sociodemographic markers, such as census tract foreign-born population, have been used to identify individuals and communities with a high risk for tuberculosis (TB) infection in the United States. However, these markers have not been evaluated as independent risk factors for TB infection in children. We evaluated associations between census tract poverty, crowding, foreign-born population, and the CDC's Social Vulnerability Index (CDC-SVI) ranking and TB infection in a population of children tested for TB infection in Boston, Massachusetts. After adjustment for age, crowding, and foreign-born percentage, increasing census tract poverty was associated with increased odds of TB infection (adjusted odds ratio [aOR] per 10% increase in population proportion living in poverty: 1.20 [95% CI, 1.04-1.40]; P = 0.01), although this association was attenuated after further adjustment for preferred language. In separate models, increasing CDC-SVI ranking was associated with increased odds of TB infection, including after adjustment for age and language preference (aOR per 10-point increase in CDC-SVI rank: 1.08 [95% CI, 1.02-1.15]; P = 0.01). Our findings suggest area-based sociodemographic factors may be valuable for characterizing TB infection risk and defining the social ecology of pediatric TB infection in low-burden settings.