Social Determinants Associated with Substance Use and Treatment Seeking in Females of Reproductive Age in the United States.

Introduction: Females of reproductive age (FoRA; 15-49 years) are the demographic most likely to be diagnosed with a substance use disorder. Preventative treatment prior to or during pregnancy is critical. Stigma and social inequities can delay access to care. There is limited research examining social determinants of health (SDoH) and how they are related to substance use and treatment seeking in this demographic. Methods: We analyzed the 2016-2019 data from the United States National Survey on Drug Use and Health using multivariable logistic regression models. Statistically significant variables were conceptually linked to the Office of Disease Prevention and Health Promotion's (ODPHP's) SDoH framework's five domains. Results: From a total sample of 1,477,336 (weighted) pregnant people and 39,600,523 (weighted) FoRA, substance use was reported by 879,209 (2.14% [95% confidence interval = 2.13-2.15]). Pregnancy status was not associated with substance use or treatment seeking. Past-month substance use was associated with high educational attainment, an annual income <$20,000, a history of criminality, low religiosity, and having health insurance. Past-month treatment-seeking behavior was associated with older age, an annual income >$20,000, a history of criminality, and greater religiosity. Behavioral health support seeking in the past month was associated with some college education. Higher depression severity was associated with all the three models. Conclusions: Using the ODPHP's SDoH framework, we begin to elicit critical connections that can describe substance use and treatment-seeking practices in FoRA. We encourage additional research to inform public health, health care, behavioral health, and other support service programming.

A machine learning model for the prediction of unhealthy alcohol use among women of childbearing age in Alabama.

INTRODUCTION: This study utilizes a machine learning model to predict unhealthy alcohol use treatment levels among women of childbearing age. METHODS: In this cross-sectional study, women of childbearing age (n = 2397) were screened for alcohol use over a 2-year period as part of the AL-SBIRT (screening, brief intervention, and referral to treatment in Alabama) program in three healthcare settings across Alabama for unhealthy alcohol use severity and depression. A support vector machine learning model was estimated to predict unhealthy alcohol use scores based on depression score and age. RESULTS: The machine learning model was effective in predicting no intervention among patients with lower Patient Health Questionnaire (PHQ)-2 scores of any age, but a brief intervention among younger patients (aged 18-27 years) with PHQ-2 scores >3 and a referral to treatment for unhealthy alcohol use among older patients (between the ages of 25 and 50) with PHQ-2 scores >4. CONCLUSIONS: The machine learning model can be an effective tool in predicting unhealthy alcohol use treatment levels and approaches.

Survey of barriers and opportunities for prescribing buprenorphine for opioid use disorder in Alabama.

Opioid-related overdose deaths have significantly increased in the USA and in Alabama. Despite this, medications for opioid use disorder (MOUD) remains significantly underutilized. Thus, this study aims to gain a better understanding of clinicians' viewpoints on potential barriers and opportunities that are likely to impact and improve the access to MOUD, especially buprenorphine prescribing. A cross-sectional survey study was conducted with Alabama's clinicians (n = 492). The survey containing a QR code was mailed to clinicians throughout the state and was asked about their viewpoints and thoughts on prescribing buprenorphine. Multivariable linear regression was used to examine associations between OUD self-efficacy, beliefs about the effectiveness of MOUD, attitudes regarding whether or not MOUD is addictive, and positive affect surrounding the treatment of OUD patients. A minority of respondents (39.8%) reported that they have an active X-waiver for MOUD. Results showed that beliefs that MOUD is addictive were significantly inversely correlated with beliefs about MOUD being effective. Furthermore, both self-efficacy and positive affect were significantly and positively associated with beliefs that MOUD is effective. Furthermore, nurse practitioners were more likely than physicians to have higher scores on the "MAT is Addictive" construct. Self-efficacy with OUD patients was positively associated with the "MOUD is Effective" construct. Finally, results showed that X-waivered providers expressed greater positive affect toward OUD patients than providers who were not X-waivered (b = 2.9, p < 0.001). Belief that MOUD is effective was also positively associated with higher scores on the positive affect construct (b = 0.5, p < 0.001). Several barriers and opportunities were identified in our survey data which could be used to explore MOUD expansion, especially buprenorphine prescribing. Strategic plans in expanding MOUD access may include educational trainings on MOUD, motivating clinicians to utilize their capacity by implementing incentive plans, increasing provider self-efficacy, reducing stigma around MOUD, and providing more financial support to uninsured patients.

Opioid Use Disorder Among the Economically Disadvantaged in the Rural South.

OBJECTIVE: This study aimed to identify county-level hotspots and associated risk factors for opioid use disorder (OUD) in the state of Alabama. METHODS: Using 2015 to 2019 Alabama Medicaid administrative claims data, Medicaid recipients with OUD were identified. We performed local indicators of spatial association analysis to identify hotspots of OUD rates. Using logistic regression, we examined county-level social determinants of health associated with county OUD hotspots. RESULTS: There was a +14.13% percentage change from 2015 to 2019. The county level local indicators of spatial association analysis found that 5 counties in the northwestern part of Alabama remained "hotspots" throughout the entire study period. Results of the logistic regression model showed that location within the Appalachian region was an independent predictor of high OUD rates ( b = 2.58; adjusted odds ratio, 13.27, P = 0.04). CONCLUSIONS: The high rates of OUD may reflect the economic distress and lack of access to resources germane to the Appalachian region in Alabama.

"I am busy enough ": Navigating challenges experienced by Medicaid providers serving pregnant people living with substance use disorders in Alabama.

PURPOSE: Perinatal substance use is a clinical and public health concern. The purpose of the study was to understand the perspectives and experiences of perinatal healthcare providers serving pregnant people who receive Medicaid and are living with a substance use disorder. DESIGN AND METHODS: We conducted a secondary data analysis of the responses from perinatal healthcare providers who completed a survey to assess the state of Alabama's capability to effectively identify and treat individuals with substance use disorder. We analyzed short answer responses using consensus coding. FINDINGS: Nine-hundred and ninety-five Medicaid providers completed the survey, 36 of the respondents identified that they were employed in an obstetric practice. Health insurance limitations, a lack of time and resources, and limited treatment options were the primary barriers indicated in the participants' responses. CONCLUSIONS: Structural and health system barriers negatively impact the capacity of perinatal healthcare providers in Alabama to serve pregnant people who receive Medicaid and are living with a substance use disorder. CLINICAL RELEVANCE: Perinatal healthcare providers need educational opportunities, training, and up-to-date resources to provide supportive, comprehensive care programming for perinatal populations with substance use disorders.

Social Determinants of Opioid Use among Patients in Rural Primary Care Settings.

Opioid use and misuse are a widespread problem across the United States. Identifying and targeting social determinants of opioid use may help to identify predictive factors to influence intervention and policy. The purpose of this study was to identify social determinants of opioid use frequency among patients seeking primary care in rural Alabama healthcare facilities. This survey-based study focused on a patient population located in rural west Alabama surveyed for a screening, brief intervention, and referral to treatment program. The screening tool contained demographic information and questions regarding the social determinants of health and opioid use, among others. Adjusted incidence rate ratios (IRRs) for the relationship between social determinants of health and opioid use frequency (in days/month) were estimated in Poisson regression models. Eleven percent of the population self-reported opioid use in the past 30 days. Three social determinants of health measured (level of education, housing stability, and employment status) were identified as having a significant association with the frequency of opioid use. Targeting certain social determinants of health may allow for further predictive interventions to mitigate opioid misuse and potential fatality or mortality.

Polysubstance abuse associated with more frequent opioid use among patients in rural primary care settings.

OBJECTIVE: Opioid use is a continuing problem for the United States. Individuals who use opioids have a high risk of misuse, especially with prescription opioids. Substances that are often used in combination with opioids include methamphetamines, sedatives, and benzodiazepines, as well as tobacco, alcohol, and marijuana, but not in a medical setting. We sought to determine (a) the relationship between various drugs (eg, methamphetamine, benzodiazepines) and opioid use, as well as (b) the relationship between polysubstance use and opioid use. DESIGN: We created a screening instrument that requested the patients seeking medical care at Federally Qualified Health Centers (FQHC) and Veterans Affairs (VA) hospitals in West Alabama self-report their substance usage. SETTING: This study took place in outpatient primary care settings (FQHCs and VA hospitals) in west Alabama. PARTICIPANTS: De-identified electronic health records for 346 adults were obtained from consenting medical facilities. Missing data were found in 33 of the records obtained. The final usable sample for this study was 311. MAIN OUTCOME MEASURE: The screening tool was comprised of five sections: demographics, tobacco use, alcohol abuse, drug use, and mental health. The primary outcome measure of this study was the number of days of opioid use in the past 30 days. RESULTS: Thirteen individuals (4.18 percent) reported opioid use in the last 30 days. While polysubstance or dual sub-stance use was not in the majority of the participant responses, the significant substances that were used in conjunction with opioids were methamphetamine, hallucinogens, and benzodiazepines. CONCLUSIONS: Individuals who are polysubstance users have a higher likelihood of opioid use. Interventions that target opioid use would serve the population stronger by including screenings and potential treatments for polysubstance use additionally.