The intersection of race and opioid use disorder treatment: A quantitative analysis

Entress, Rebecca

doi:10.1016/j.jsat.2021.108589

Cited by 20 publications

(8 citation statements)

References 31 publications

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“…However, BISG-based approaches in claims data suggested the Black-White disparity for receiving ongoing substance use treatment may be underestimated when based on incomplete self-reported data. Taken together, these findings highlight the persistence of racialized medical care for pain management and substance use disorder treatment, [35][36][37][38][39][40] and the imperativeness of accurate disparities surveillance. Indeed, indirect methods, including BISG, are recommended when less than 80% of self-reported race and ethnicity are available for quality measurement.…”

Section: Discussionmentioning

confidence: 99%

Implications of missingness in self‐reported data for estimating racial and ethnic disparities in Medicaid quality measures

Yee

Hoopes

Giebultowicz

et al. 2022

Health Services Research

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Objective: To assess the feasibility and implications of imputing race and ethnicity for quality and utilization measurement in Medicaid. Data Sources and StudySetting: 2017 Oregon Medicaid claims from the Oregon Health Authority and electronic health records (EHR) from OCHIN, a clinical data research network, were used. Study Design: We cross-sectionally assessed Hispanic-White, Black-White, and Asian-White disparities in 22 quality and utilization measures, comparing selfreported race and ethnicity to imputed values from the Bayesian Improved Surname Geocoding (BISG) algorithm.Data Collection: Race and ethnicity were obtained from self-reported data and imputed using BISG.Principal Findings: 42.5%/4.9% of claims/EHR were missing self-reported data; BISG estimates were available for >99% of each and had good concordance (0.87-0.95) with Asian, Black, Hispanic, and White self-report. All estimated racial and ethnic disparities were statistically similar in self-reported and imputed EHR-based measures.However, within claims, BISG estimates and incomplete self-reported data yielded substantially different disparities in almost half of the measures, with BISG-based Black-White disparities generally larger than self-reported race and ethnicity data.Conclusions: BISG imputation methods are feasible for Medicaid claims data and reduced missingness to <1%. Disparities may be larger than what is estimated using self-reported data with high rates of missingness.

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Section: Discussionmentioning

confidence: 99%

Implications of missingness in self‐reported data for estimating racial and ethnic disparities in Medicaid quality measures

Yee

Hoopes

Giebultowicz

et al. 2022

Health Services Research

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“…30 Another study argued that minorities were less likely to be treated for OUD. 31 Ransome et al 32 demonstrated that Black women with AUD have more adverse health effects than White women with AUD, with much of the difference due to socioeconomic status, healthcare factors, and psychosocial stressors. This study found that White patients have a higher incidence of seizure, AUD, and OUD.…”

Section: Discussion Demographicsmentioning

confidence: 99%

Association Between Opioid Use Disorder and Seizure Incidents Among Alcohol Use Disorder Patients

et al. 2023

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Many previous studies have discussed an association between alcohol use disorder (AUD) and seizure incidents. There are also case reports of seizures during opioid withdrawals. Therefore, it is possible that AUD patients may have a higher risk of seizures if they also have opioid use disorder (OUD). However, it remains unproven whether AUD patients with a dual diagnosis of OUD have higher seizure incidents, to our knowledge. This study explored seizure incidents among the patients with a dual diagnosis of AUD and OUD as well as seizures among AUD only or OUD only patients. This study utilized de-identified data from 30 777 928 hospital inpatient encounters at 948 healthcare systems over 4 years (9/1/2018-8/31/2022) from the Vizient® Clinical Database for this study. Applying the International Classification of Diseases 10th Revision (ICD-10) diagnostic codes, AUD (1 953 575), OUD (768 982), and seizure (1 209 471) encounters were retrieved from the database to examine the effects of OUD on seizure incidence among AUD patients. This study also stratified patient encounters for demographic factors such as gender, age, and race, as well as the Vizient-categorized primary payer. Greatest gender differences were identified among AUD followed by OUD, and seizure patient groups. The mean age for seizure incidents was 57.6 years, while that of AUD was 54.7 years, and OUD 48.9 years. The greatest proportion of patients in all 3 groups were White, followed by Black, with Medicare being the most common primary payer in all 3 categories. Seizure incidents were statistically more common ( P < .001, chi-square) in patients with a dual diagnosis of AUD and OUD (8.07%) compared to those with AUD only (7.55%). The patients with the dual diagnosis had a higher odd ratio than those with AUD only or OUD only. These findings across more than 900 health systems provide a greater understanding of seizure risks. Consequently, this information may help in triaging AUD and OUD patients in certain higher-risk demographic groups.

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“…People who identify as members of underrepresented groups comprise over one-third of the admissions to publicly funded SUTx programs [ 9 ]; however, recent research suggests these individuals may be at particular risk for poor treatment outcomes, due in part to socioeconomic factors [ 10 ] and racism [ 11 , 12 ]. Despite socioeconomic challenges, the digital gap among members of underrepresented groups and Caucasian individuals has narrowed over the past 15 years [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Technology-Based Interventions in Substance Use Treatment to Promote Health Equity Among People Who Identify as African American/Black, Hispanic/Latinx, and American Indian/Alaskan Native: Protocol for a Scoping Review

Hichborn¹,

Moore²,

Gauthier³

et al. 2022

JMIR Res Protoc

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Background Technology-based interventions (TBIs; ie, web-based and mobile interventions) have the potential to promote health equity in substance use treatment (SUTx) for underrepresented groups (people who identify as African American/Black, Hispanic/Latinx, and American Indian/Alaskan Native) by removing barriers and increasing access to culturally relevant effective treatments. However, technologies (emergent and more long-standing) may have unintended consequences that could perpetuate health care disparities among people who identify as a member of one of the underrepresented groups. Health care research, and SUTx research specifically, is infrequently conducted with people who identify with these groups as the main focus. Therefore, an improved understanding of the literature at the intersection of SUTx, TBIs, and underrepresented groups is warranted to avoid exacerbating inequities and to promote health equity. Objective This study aims to explore peer-reviewed literature (January 2000-March 2021) that includes people who identify as a member of one of the underrepresented groups in SUTx research using TBIs. We further seek to explore whether this subset of research is race/ethnicity conscious (does the research consider members of underrepresented groups beyond their inclusion as study participants in the introduction, methods, results, or discussion). Methods Five electronic databases (MEDLINE, Scopus, Cochrane Library, CINAHL, and PsycInfo) were searched to identify SUTx research using TBIs, and studies were screened for eligibility at the title/abstract and full-text levels. Studies were included if their sample comprised of people who identify as a member of one of the underrepresented groups at 50% or more when combined. Results Title/abstract and full-text reviews were completed in 2021. These efforts netted a sample of 185 studies that appear to meet inclusionary criteria. Due to the uniqueness of tobacco relative to other substances in the SUTx space, as well as the large number of studies netted, we plan to separately publish a scoping review on tobacco-focused studies that meet all other criteria. Filtering for tobacco-focused studies (n=31) netted a final full-text sample for a main scoping review of 154 studies. The tobacco-focused scoping review manuscript is expected to be submitted for peer review in Spring 2022. The main scoping review data extraction and data validation to confirm the accuracy and consistency of data extraction across records was completed in March 2022. We expect to publish the main scoping review findings by the end of 2022. Conclusions Research is needed to increase our understanding of the range and nature of TBIs being used in SUTx research studies with members of underrepresented groups. The planned scoping review will highlight research at this intersection to promote health equity. International Registered Report Identifier (IRRID) DERR1-10.2196/34508

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The intersection of race and opioid use disorder treatment: A quantitative analysis

Cited by 20 publications

References 31 publications

Implications of missingness in self‐reported data for estimating racial and ethnic disparities in Medicaid quality measures

Implications of missingness in self‐reported data for estimating racial and ethnic disparities in Medicaid quality measures

Association Between Opioid Use Disorder and Seizure Incidents Among Alcohol Use Disorder Patients

Technology-Based Interventions in Substance Use Treatment to Promote Health Equity Among People Who Identify as African American/Black, Hispanic/Latinx, and American Indian/Alaskan Native: Protocol for a Scoping Review

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