Mitigating disparity?: Treatment patterns, survival, and recurrence rates by race, ethnicity, and hospital site across a large urban health system
Ontology highlight
ABSTRACT:
SUBMITTER: Papatla K
PROVIDER: S-EPMC10997945 | biostudies-literature | 2024 Mar
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundHospital admissions involving substance use disorders are increasing and represent an opportunity to engage patients in substance use treatment. Addiction medicine consultation services improve access to medications for opioid use disorder (MOUD) and patient outcomes. However, as hospitals continue to adopt addiction medicine consultation services it is important to identify where disparities may emerge in the process of care.ObjectiveTo describe addiction medicine consultation service use by race and ethnicity as well as substance to identify opportunities to reduce substance use treatment disparities.DesignRetrospective cohort study using 2016-2021 Electronic Health Record data from a large Midwest safety-net hospital.ParticipantsHospitalized adults aged 18 or older, with one or more substance use disorders.Main measuresConsultation orders placed, patient seen by consult provider, and receipt of MOUD by self-reported race.Key resultsBetween 2016 and 2021, we identified 16,895 hospitalized patients with a substance use disorder. Consultation orders were placed for 6344 patients and 2789 were seen by the consult provider. Black patients were less likely (aOR = 0.58; 95% CI: 0.53-0.63) to have an addiction medicine consultation order placed and, among patients with a consultation order, were less likely (aOR = 0.74; 95% CI: 0.65-0.85) to be seen by the consult provider than White patients. Overall, Black patients with OUD were also less likely to receive MOUD in the hospital (aOR = 0.63; 95% CI: 0.50-0.79) compared to White patients. However, there were no differences in MOUD receipt among Black and White patients seen by the consult provider.ConclusionsUsing Electronic Health Record data, we identified racial and ethnic disparities at multiple points in the inpatient addiction medicine consultation process. Addressing these disparities may support more equitable access to MOUD and other substance use treatment in the hospital setting.
| S-EPMC10853106 | biostudies-literature
Project description:ImportanceLittle is known about the distribution of life-saving trauma resources by racial/ethnic composition in US cities, and if racial/ethnic minority populations disproportionately live in US urban trauma deserts.ObjectiveTo examine racial/ethnic differences in geographic access to trauma care in the 3 largest US cities, considering the role of residential segregation and neighborhood poverty.Design, setting, and participantsA cross-sectional, multiple-methods study evaluated census tract data from the 2015 American Community Survey in Chicago, Illinois; Los Angeles (LA), California; and New York City (NYC), New York (N = 3932). These data were paired to geographic coordinates of all adult level I and II trauma centers within an 8.0-km buffer of each city. Between February and September 2018, small-area analyses were conducted to assess trauma desert status as a function of neighborhood racial/ethnic composition, and geospatial analyses were conducted to examine statistically significant trauma desert hot spots.Main outcomes and measuresIn small-area analyses, a trauma desert was defined as travel distance greater than 8.0 km to the nearest adult level I or level II trauma center. In geospatial analyses, relative trauma deserts were identified using travel distance as a continuous measure. Census tracts were classified into (1) racial/ethnic composition categories, based on patterns of residential segregation, including white majority, black majority, Hispanic/Latino majority, and other or integrated; and (2) poverty categories, including nonpoor and poor.ResultsChicago, LA, and NYC contained 798, 1006, and 2128 census tracts, respectively. A large proportion comprised a black majority population in Chicago (35.1%) and NYC (21.4%), compared with LA (2.7%). In primary analyses, black majority census tracts were more likely than white majority census tracts to be located in a trauma desert in Chicago (odds ratio [OR], 8.48; 95% CI, 5.71-12.59) and LA (OR, 5.11; 95% CI, 1.50-17.39). In NYC, racial/ethnic disparities were not significant in unadjusted models, but were significant in models adjusting for poverty and race-poverty interaction effects (adjusted OR, 1.87; 95% CI, 1.27-2.74). In comparison, Hispanic/Latino majority census tracts were less likely to be located in a trauma desert in NYC (OR, 0.03; 95% CI, 0.01-0.11) and LA (OR, 0.30; 95% CI, 0.22-0.40), but slightly more likely in Chicago (OR, 2.38; 95% CI, 1.56-3.64).Conclusions and relevanceIn this study, black majority census tracts were the only racial/ethnic group that appeared to be associated with disparities in geographic access to trauma centers.
| S-EPMC6484639 | biostudies-literature
Project description:Background/Objectives: Reports documenting racial disparities in COVID-19 hospitalization rates from electronic medical record data have used different sample selection methods. Studies including all individuals with a positive COVID-19 test may be vulnerable to misclassification bias if hospitalization status is not captured for all individuals (i.e., if they went to a non-study hospital). A few studies have used only patients who tested positive in the ED and have found different results. In this study, we explore the implications of using different sets of inclusion criteria for analyses that compare COVID-19 hospital admissions by race and ethnicity. Methods: Two separate data sets were created by applying the two different COVID-19 testing inclusion criteria to medical records data from a single academic health system. We used logistic regression to compare the odds of COVID-19 hospitalization across race and ethnicity for each data set and compared our results with previous studies. Results: We found that using all positive COVID-19 tests as the study sample resulted in higher odds of hospitalization for Black and Hispanic patients relative to White patients. In contrast, using only patients who tested positive in the ED resulted in higher odds of hospitalization for White patients. These findings matched the findings of other studies. Conclusions: Patient inclusion criteria should be considered carefully when comparing results from studies of COVID-19 hospitalization.
| S-EPMC11855206 | biostudies-literature
Project description:BackgroundEnvironmental biomonitoring data provide one way to examine race/ethnicity and income-related exposure disparity and identify potential environmental justice concerns.MethodsWe screened U.S. National Health and Nutrition Examination Survey (NHANES) 2001-2008 biomonitoring data for 228 chemicals for race/ethnicity and income-related disparity. We defined six subgroups by race/ethnicity-Mexican American, non-Hispanic black, non-Hispanic white-and income-Low Income: poverty income ratio (PIR) <2, High Income: PIR ≥ 2. We assessed disparity by comparing the central tendency (geometric mean [GM]) of the biomonitoring concentrations of each subgroup to that of the reference subgroup (non-Hispanic white/High Income), adjusting for multiple comparisons using the Holm-Bonferroni procedure.ResultsThere were sufficient data to estimate at least one geometric mean ratio (GMR) for 108 chemicals; 37 had at least one GMR statistically different from one. There was evidence of potential environmental justice concern (GMR significantly >1) for 12 chemicals: cotinine; antimony; lead; thallium; 2,4- and 2,5-dichlorophenol; p,p'-dichlorodiphenyldichloroethylene; methyl and propyl paraben; and mono-ethyl, mono-isobutyl, and mono-n-butyl phthalate. There was also evidence of GMR significantly <1 for 25 chemicals (of which 17 were polychlorinated biphenyls).ConclusionsAlthough many of our results were consistent with the U.S. literature, findings relevant to environmental justice were novel for dichlorophenols and some metals.
| S-EPMC3893603 | biostudies-literature
Project description:Hospital discharge (HD) records contain important information that is used in public health and health care sectors. It is becoming increasingly common to rely mostly or exclusively on HD data to assess and monitor severe maternal morbidity (SMM) overall and by sociodemographic characteristics, including race and ethnicity. Limited studies have validated race and ethnicity in HD or provided estimates on the impact of assessing health differences in maternity populations. This study aims to determine the differences in race and ethnicity reporting between HD and birth certificate (BC) data for maternity hospitals in Florida and to estimate the impact of race and ethnicity misclassification on state- and hospital-specific SMM rates. We conducted a population-based retrospective study of live births using linked BC and HD records from 2016 to 2019 (n = 783,753). BC data were used as the gold standard. Race and ethnicity were categorized as non-Hispanic (NH)-White, NH-Black, Hispanic, NH-Asian Pacific Islander (API), and NH-American Indian or Alaskan Native (AIAN). Overall, race and ethnicity misclassification and its impact on SMM at the state- and hospital levels were estimated. At the state level, NH-AIAN women were the most misclassified (sensitivity: 28.2%; positive predictive value (PPV): 25.2%) and were commonly classified as NH-API (30.3%) in HD records. NH-API women were the next most misclassified (sensitivity: 57.3%; PPV: 85.4%) and were commonly classified as NH-White (5.8%) or NH-other (5.5%). At the hospital level, wide variation in sensitivity and PPV with negative skewing was identified, particularly for NH-White, Hispanic, and NH-API women. Misclassification did not result in large differences in SMM rates at the state level for all race and ethnicity categories except for NH-AIAN women (% difference 78.7). However, at the hospital level, Hispanic women had wide variability of a percent difference in SMM rates and were more likely to have underestimated SMM rates. Reducing race and ethnicity misclassification on HD records is key in assessing and addressing SMM differences and better informing surveillance, research, and quality improvement efforts.
| S-EPMC10178402 | biostudies-literature
Project description:This study examines the interplay between race/ethnicity and educational attainment in shaping completed fertility in the United States for women born 1961-80. Using data from the National Survey of Family Growth, 2006-17, we apply multilevel, multiprocess hazard models to account for unobserved heterogeneity and to estimate (1) cohort total fertility rates, (2) parity progression ratios, and (3) parity-specific fertility timing, for non-Hispanic white, non-Hispanic Black, and Hispanic women by educational attainment. We find that compared with their white counterparts, fertility was higher among Black and Hispanic women with less than high school education. However, among college-educated women, fertility levels were lowest among Black women and highest among Hispanic women. The difference in fertility between college-educated Black and white women is driven mainly by the smaller proportion of Black mothers having second births. We find little evidence that the observed racial/ethnic disparities in fertility levels by educational attainment are driven by differences in fertility timing.
| S-EPMC9613612 | biostudies-literature
Project description:ImportanceWithout knowledge of the degree of misattribution in racial and ethnic designations in data, studies run the risk of missing existing inequities and disparities and identifying others that do not exist. Further, accuracy of racial and ethnic designations is important to clinical care improvement efforts and health outcomes.ObjectiveTo determine the error rate of racial and ethnic attribution in the electronic medical records (EMRs) across the 3 largest pediatric health systems in Michigan.Design, setting, and participantsThis cross-sectional study collected race and ethnicity data from parents in outpatient clinics, emergency departments, and inpatient units at the 3 largest pediatric health systems in Michigan. A total of 1594 parents or guardians participated at health system A, 1537 at health system B, and 1202 at health system C from September 1, 2023, to January 31, 2024. Parent or guardian report of race and ethnicity for a child was used as the gold standard for comparison with the designation in the EMR.ExposureRace and ethnicity designations in the EMR. Options for race designation across the health systems ranged from 6 to 49; options for ethnicity, from 2 to 10.Main outcomes and measuresMatching occurred in 3 stages. First, the exact racial and ethnic designations made by parents for their child were compared with what was found in the EMR. Second, for any child whose parent selected more than 1 racial category or for whom more than 1 appeared in the EMR, the designation of a minoritized racial group was used for matching purposes. Third, starting with the product of stage 2, racial designations were combined or collapsed into 6 (health systems A and C) or 5 (health system B) designations.ResultsA total of 4333 survey responses were included in the analysis. The greatest error rate across the health systems occurred with the exact match of parental report of racial designation with the EMR, which ranged from 41% to 78% across the health systems. Improvement in the matching rate for each health system occurred with consolidation of race options provided. Differences between the health systems narrowed at the final consolidation to varying from 79% to 88% matching. Ethnicity matching between the EMR and the parental report ranged from 65% to 95% across the health systems. Missing race or ethnicity data in the EMR was counted as a nonmatch. Rates of missing racial data varied across the health systems from 2% to 10%. The health system with the greatest number of options for race and ethnicity had the highest error rates.Conclusions and relevanceAlthough there will always be some misattribution of race and ethnicity in the EMR, the results of this cross-sectional study suggest that significant error in these data may undermine strategies to improve care. It is unclear whether those in an organization who determine the number of potential categories are the same persons who use those data to investigate potential disparities and inequities.
| S-EPMC11372483 | biostudies-literature
Project description:The objective of our study is to assess differences in prevalence of multimorbidity by race/ethnicity. We applied the FP-growth algorithm on middle-aged and elderly cohorts stratified by race/ethnicity, age, and obesity level. We used 2016-2017 data from the Cerner HealthFacts electronic health record data warehouse. We identified disease combinations that are shared by all races/ethnicities, those shared by some, and those that are unique to one group for each age/obesity level. Our findings demonstrate that even after stratifying by age and obesity, there are differences in multimorbidity prevalence across races/ethnicities. There are multimorbidity combinations distinct to some racial groups-many of which are understudied. Some multimorbidities are shared by some but not all races/ethnicities. African Americans presented with the most distinct multimorbidities at an earlier age. The identification of prevalent multimorbidity combinations amongst subpopulations provides information specific to their unique clinical needs.
| S-EPMC9188579 | biostudies-literature
Project description:Increasing biomedical workforce diversity remains a persistent challenge. Recent reports have shown that biomedical sciences (BMS) graduate students become less interested in faculty careers as training progresses; however, it is unclear whether or how the career preferences of women and underrepresented minority (URM) scientists change in manners distinct from their better-represented peers. We report results from a survey of 1500 recent American BMS Ph.D. graduates (including 276 URMs) that examined career preferences over the course of their graduate training experiences. On average, scientists from all social backgrounds showed significantly decreased interest in faculty careers at research universities, and significantly increased interest in non-research careers at Ph.D. completion relative to entry. However, group differences emerged in overall levels of interest (at Ph.D. entry and completion), and the magnitude of change in interest in these careers. Multiple logistic regression showed that when controlling for career pathway interest at Ph.D. entry, first-author publication rate, faculty support, research self-efficacy, and graduate training experiences, differences in career pathway interest between social identity groups persisted. All groups were less likely than men from well-represented (WR) racial/ethnic backgrounds to report high interest in faculty careers at research-intensive universities (URM men: OR 0.60, 95% CI: 0.36-0.98, p = 0.04; WR women: OR: 0.64, 95% CI: 0.47-0.89, p = 0.008; URM women: OR: 0.46, 95% CI: 0.30-0.71, p<0.001), and URM women were more likely than all other groups to report high interest in non-research careers (OR: 1.93, 95% CI: 1.28-2.90, p = 0.002). The persistence of disparities in the career interests of Ph.D. recipients suggests that a supply-side (or "pipeline") framing of biomedical workforce diversity challenges may limit the effectiveness of efforts to attract and retain the best and most diverse workforce. We propose incorporation of an ecological perspective of career development when considering strategies to enhance the biomedical workforce and professoriate through diversity.
| S-EPMC4262437 | biostudies-literature
Project description:IntroductionInfant mortality rates are higher in nonmetropolitan areas versus large metropolitan areas. Variation by race/ethnicity and cause of death has not been assessed. Urban-rural infant mortality rate differences were quantified by race/ethnicity and cause of death.MethodsNational Vital Statistics System linked birth/infant death data (2014-2016) were analyzed in 2019 by 3 urban-rural county classifications: large metropolitan, medium/small metropolitan, and nonmetropolitan. Excess infant mortality rates (rate differences) by urban-rural classification were calculated relative to large metropolitan areas overall and for each racial/ethnic group. The number of excess deaths, population attributable fraction, and proportion of excess deaths attributable to underlying causes of death was calculated.ResultsNonmetropolitan areas had the highest excess infant mortality rate overall. Excess infant mortality rates were substantially lower for Hispanic infants than other races/ethnicities. Overall, 7.4% of infant deaths would be prevented if all areas had the infant mortality rate of large metropolitan areas. With more than half of births occurring outside of large metropolitan areas, the population attributable fraction was highest for American Indian/Alaska Natives (20.3%) and whites, non-Hispanic (14.3%). Excess infant mortality rates in both nonmetropolitan and medium/small metropolitan areas were primarily attributable to sudden unexpected infant deaths (42.3% and 31.9%) and congenital anomalies (30.1% and 26.8%). This pattern was consistent for all racial/ethnic groups except black, non-Hispanic infants, for whom preterm-related and sudden unexpected infant deaths accounted for the largest share of excess infant mortality rates.ConclusionsInfant mortality increases with rurality, and excess infant mortality rates are predominantly attributable to sudden unexpected infant deaths and congenital anomalies, with differences by race/ethnicity regarding magnitude and cause of death.
| S-EPMC6980981 | biostudies-literature