Variation in documented care for unhealthy alcohol consumption across race/ethnicity in the department of veterans affairs healthcare system.
ABSTRACT The VA Healthcare System has made progress implementing evidence-based care for unhealthy alcohol use, but whether there are differences in care across race/ethnicity is unclear. We describe alcohol-related care for 3 racial/ethnic groups among VA outpatients with unhealthy alcohol use.
This cross-sectional study utilized secondary quality improvement data collected for the VA Office of Quality and Performance (July 2006 to June 2007) to identify a sample of 9,194 black (n = 1,436), Hispanic (n = 500), and white (n = 7,258) VA outpatients who screened positive for unhealthy alcohol use (AUDIT-C score ≥4 men; ≥3 women). Alcohol-related care was defined as medical record documentation of brief intervention (advice or feedback) and/or referral (discussion of or scheduled). Logistic regression models estimated the prevalence of alcohol-related care among black, Hispanic, and white patients after adjustment for sociodemographic characteristics, alcohol use severity, other substance use, and mental health comorbidity.
Among all eligible patients, 2,903 (32%) had documented alcohol-related care. Adjusted prevalences were 35.3% (95% CI 30.0 to 40.5) for black, 27.3% (95% CI 21.1 to 33.5) for Hispanic, and 28.9% (95% CI 25.5 to 32.3) for white patients. Differences in documented alcohol-related care between all racial/ethnic groups were significant (p-values all < 0.05).
Among VA patients with unhealthy alcohol use, black patients had the highest, and Hispanic the lowest, prevalence of documented alcohol-related care. Future research should evaluate contextual and system-, provider-, or patient-level factors that may attenuate racial/ethnic differences in documented alcohol-related care, as well as whether differences in documented care are associated with differences in outcomes.
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ABSTRACT: Aim This article presents a conceptual model to help facilitate the transition from primary care to specialty substance use disorder (SUD) care for appropriate patients. Substance misuse is a common health condition among patients presenting to primary care settings and may complicate the treatment of chronic health conditions such as diabetes and hypertension. It is therefore critical that primary care providers be prepared to identify and determine appropriate treatment options for patients presenting with substance misuse. We conducted a narrative review that occurred in three stages: literature review of health care transition models, identification of conceptual domains common across care transition models, and identification of SUD-specific model elements. Findings The conceptual model presented describes patient, provider, and system-level facilitators and barriers to the transition process, and includes intervention strategies that can be utilized by primary care clinics to potentially improve the process of transitioning patients from primary care to SUD care. Recognizing that primary care clinics vary in available resources, we present three examples of care practices along an intensity continuum from low (counseling and referral) to moderate (telephone monitoring) to high (intensive case management) resource demands for adoption. We also provide a list of common outcomes clinics might consider when evaluating the impact of care transition practices in this patient population; these include process outcomes such as patients' increased knowledge of available treatment resources, and health outcomes such as patients' reduced substance use and better quality of life.Primary Health Care Research & Development 05/2014; DOI:10.1017/S1463423614000164
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ABSTRACT: Alcohol use disorder (AUD) is among the most stigmatized health conditions and is frequently comorbid with mood, anxiety, and drug use disorders. Theoretical frameworks have conceptualized stigma-related stress as a predictor of psychiatric disorders. We described profiles of psychiatric comorbidity among people with AUD and compared levels of perceived alcohol stigma across profiles.Alcoholism Clinical and Experimental Research 05/2014; DOI:10.1111/acer.12422 · 3.31 Impact Factor
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ABSTRACT: OBJECTIVE This study characterized racial-ethnic differences in treatment of veterans with chronic depression by examining antidepressant and psychotherapy use among non-Hispanic black, non-Hispanic white, Hispanic, Asian, and American Indian-Alaska Native (AI/AN) veterans. METHODS Logistic regression models were estimated with data from the U.S. Department of Veterans Affairs (VA) medical records for a sample of 62,095 chronically depressed patients. Data (2009-2010) were from the VA External Peer Review Program. Three primary outcome measures were used: receipt of adequate antidepressant therapy (≥80% medications on hand), receipt of adequate psychotherapy (at least six sessions in six months), and receipt of guideline-concordant treatment (either of these treatments). RESULTS Compared with whites, nearly all minority groups had lower odds of adequate antidepressant use and guideline-concordant care in unadjusted and adjusted models (antidepressant adjusted odds ratio [AOR] range=.53-.82, p<.05; guideline-concordant AOR range=.59-.83, p<.05). Although receipt of adequate psychotherapy was more common among veterans from minority groups in unadjusted analyses, differences between Hispanic, AI/AN, and white veterans were no longer significant after covariate adjustment. After adjustment for distance to the VA facility, the difference between black and white veterans was no longer significant. CONCLUSIONS A better understanding of how patient preferences and provider and system factors interact to generate differences in depression care is needed to improve care for patients from racial-ethnic minority groups. It will become increasingly important to differentiate between health service use patterns that stem from genuine differences in patient preferences and those that signify inequitable quality of depression care.Psychiatric services (Washington, D.C.) 11/2013; 65(2). DOI:10.1176/appi.ps.201300057 · 1.99 Impact Factor