Dataset Information

Primary care engagement is associated with increased pharmacotherapy prescribing for alcohol use disorder (AUD).

ABSTRACT:

Background

Primary care provider skills such as screening, longitudinal monitoring, and medication management are generalizable to prescribing alcohol use disorder (AUD) pharmacotherapy. The association between primary care engagement (i.e., longitudinal utilization of primary care services) and prescribing of AUD pharmacotherapy is unknown.

Methods

We examined a 5-year (2010-2014) retrospective cohort of patients with AUD, 18 years and older, at an urban academic medical center in the Bronx, NY, USA. Our main exposure was level of primary care engagement (no primary care, limited primary care, and engaged with primary care) and our outcome was any AUD pharmacotherapy prescription within 2 years of AUD diagnosis. Using multivariable logistic regression, we examined the association between primary care engagement and pharmacotherapy prescribing, accounting for demographic and clinical factors.

Results

Of 21,159 adults (28.9% female) with AUD, 2.1% (n?=?449) were prescribed pharmacotherapy. After adjusting for confounders, the probability of receiving an AUD pharmacotherapy prescription for patients with no primary care was 1.61% (95% CI 1.39, 1.84). The probability of AUD pharmacotherapy prescribing was 2.56% (95% CI 2.06, 3.06) for patients with limited primary care and 2.89% (95% CI 2.44, 3.34%) for patients engaged with primary care.

Conclusions

The percentage of AUD patients prescribed AUD pharmacotherapy was low; however, primary care engagement was associated with a higher, but modest, probability of receiving a prescription. Efforts to increase primary care engagement among patients with AUD may translate into increased AUD pharmacotherapy prescribing; however, strategies to increase prescribing across health care settings are needed.

SUBMITTER: Joudrey PJ

PROVIDER: S-EPMC6492411 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Primary care engagement is associated with increased pharmacotherapy prescribing for alcohol use disorder (AUD).

Joudrey Paul J PJ Kladney Mat M Cunningham Chinazo O CO Bachhuber Marcus A MA

Addiction science & clinical practice 20190501 1

<h4>Background</h4>Primary care provider skills such as screening, longitudinal monitoring, and medication management are generalizable to prescribing alcohol use disorder (AUD) pharmacotherapy. The association between primary care engagement (i.e., longitudinal utilization of primary care services) and prescribing of AUD pharmacotherapy is unknown.<h4>Methods</h4>We examined a 5-year (2010-2014) retrospective cohort of patients with AUD, 18 years and older, at an urban academic medical center i ...[more]

PMID: 31039820

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Project description:Only 7.8 % of individuals meeting diagnostic criteria for alcohol use disorder (AUD) receive treatment in a given year. Most individuals with AUDs are identified in primary care (PC) settings and referred to substance use disorders (SUD) clinics; however, only a minority of those referred attend treatment services. Safe and effective pharmacological treatments for AUD exist, but they are rarely prescribed by PC providers. The objective of this study is to refine, implement, and evaluate an intervention to integrate pharmacological AUD treatment options into PC settings. This paper provides a detailed description of the intervention design and the evaluation components.Three large Veterans Health Administration (VHA) facilities are participating in the intervention. The intervention targets stakeholder groups with tailored strategies based on implementation theory and prior research identifying barriers to implementation of AUD pharmacotherapy. Local SUD providers and primary care mental health integration (PCMHI) providers are trained to serve as local implementation/clinical champions and receive external facilitation. PC providers receive access to consultation from local and national clinical champions, educational materials, and a dashboard of patients with AUD on their caseloads for case identification. Veterans with AUD diagnoses receive educational information in the mail just prior to a scheduled PC visit. Effectiveness of the intervention will be evaluated through an interrupted time series with matched controls to monitor change in facility level AUD pharmacotherapy prescribing rates. Following Stetler's four-phase formative evaluation (FE) strategy, FE methods include (1) developmental FE (pre-implementation interviews with champions, PC providers, and Veterans), (2) implementation-focused FE (tracking attendance at facilitation meetings, academic detailing efforts by local champions, and patient dashboard utilization), (3) progress-focused FE (tracking rates of AUD pharmacotherapy prescribing and rates of referral to PCMHI and SUD specialty care), and (4) interpretive FE (post-implementation interviews with champions and PC providers). Analysis of FE data will be guided by the Consolidated Framework for Implementation Research (CFIR).If demonstrated to be successful, this implementation strategy will provide a replicable, feasible, and relative low-cost method for integrating AUD treatment services into PC settings, thereby increasing access to AUD treatment.

Project description:BackgroundDespite the high prevalence of alcohol use disorders (AUDs), in 2016, only 7.8% of individuals meeting diagnostic criteria received any type of AUD treatment. Developing options for treatment within primary care settings is imperative to increase treatment access. As part of a trial to implement AUD pharmacotherapy in primary care settings, this qualitative study analyzed pre-implementation provider interviews using the Consolidated Framework for Implementation Research (CFIR) to identify implementation barriers.MethodsThree large Veterans Health Administration facilities participated in the implementation intervention. Local providers were trained to serve as implementation/clinical champions and received external facilitation from the project team. Primary care providers received a dashboard of patients with AUD for case identification, educational materials, and access to consultation from clinical champions. Veterans with AUD diagnoses received educational information in the mail. Prior to the start of implementation activities, 24 primary care providers (5-10 per site) participated in semi-structured interviews. Transcripts were analyzed using common coding techniques for qualitative data using the CFIR codebook Innovation/Intervention Characteristics, Outer Setting, Inner Setting, and Characteristics of Individuals domains. Number and type of barriers identified were compared to quantitative changes in AUD pharmacotherapy prescribing rates.ResultsFour major barriers emerged across all three sites: complexity of providing AUD pharmacotherapy in primary care, the limited compatibility of AUD treatment with existing primary care processes, providers' limited knowledge and negative beliefs about AUD pharmacotherapy and providers' negative attitudes toward patients with AUD. Site specific barriers included lack of relative advantage of providing AUD pharmacotherapy in primary care over current practice, complaints about the design quality and packaging of implementation intervention materials, limited priority of addressing AUD in primary care and limited available resources to implement AUD pharmacotherapy in primary care.ConclusionsCFIR constructs were useful for identifying pre-implementation barriers that informed refinements to the implementation intervention. The number and type of pre-implementation barriers identified did not demonstrate a clear relationship to the degree to which sites were able to improve AUD pharmacotherapy prescribing rate. Site-level implementation process factors such as leadership support and provider turn-over likely also interacted with pre-implementation barriers to drive implementation outcomes.

Project description:BackgroundAlcohol use disorder (AUD) causes significant morbidity, mortality, and injuries. According to reports, approximately 5% of all registered deaths in Denmark could be due to AUD. The problem is compounded by the late identification of patients with AUD, a situation that can cause enormous problems, from psychological to physical to economic problems. Many individuals suffering from AUD never undergo specialist treatment during their addiction due to obstacles such as taboo and the poor performance of current screening tools. Therefore, there is a lack of rapid intervention. This can be mitigated by the early detection of patients with AUD. A clinical decision support system (DSS) powered by machine learning (ML) methods can be used to diagnose patients' AUD status earlier.MethodsThis study proposes an effective AUD prediction model (AUDPM), which can be used in a DSS. The proposed model consists of four distinct components: (1) imputation to address missing values using the k-nearest neighbours approach, (2) recursive feature elimination with cross validation to select the most relevant subset of features, (3) a hybrid synthetic minority oversampling technique-edited nearest neighbour approach to remove noise and balance the distribution of the training data, and (4) an ML model for the early detection of patients with AUD. Two data sources, including a questionnaire and electronic health records of 2571 patients, were collected from Odense University Hospital in the Region of Southern Denmark for the AUD-Dataset. Then, the AUD-Dataset was used to build ML models. The results of different ML models, such as support vector machine, K-nearest neighbour, decision tree, random forest, and extreme gradient boosting, were compared. Finally, a combination of all these models in an ensemble learning approach was selected for the AUDPM.ResultsThe results revealed that the proposed ensemble AUDPM outperformed other single models and our previous study results, achieving 0.96, 0.94, 0.95, and 0.97 precision, recall, F1-score, and accuracy, respectively. In addition, we designed and developed an AUD-DSS prototype.ConclusionIt was shown that our proposed AUDPM achieved high classification performance. In addition, we identified clinical factors related to the early detection of patients with AUD. The designed AUD-DSS is intended to be integrated into the existing Danish health care system to provide novel information to clinical staff if a patient shows signs of harmful alcohol use; in other words, it gives staff a good reason for having a conversation with patients for whom a conversation is relevant.

Project description:BackgroundAlcohol use disorder (AUD) imposes a high mortality and economic burden. Effective treatment is available, though underutilized.ObjectiveDescribe trends in AUD pharmacotherapy, variation in prescribing, and associated patient factors.DesignRetrospective cohort using electronic health records from 2010 to 2019.ParticipantsPrimary care patients from 39 clinics in Ohio and Florida with diagnostic codes for alcohol dependence or abuse plus social history indicating alcohol use. PCPs in family or internal medicine with at least 20 AUD patients.Main measuresPharmacotherapy for AUD (naltrexone, acamprosate, and disulfiram), abstinence from alcohol, patient demographics, and comorbidities. Generalized linear mixed models were used to identify patient factors associated with prescriptions and the association of pharmacotherapy with abstinence.Key resultsWe identified 13,250 patients; average age was 54 years, 66.9% were male, 75.0% were White, and median household income was $51,776 per year. Over 10 years, the prescription rate rose from 4.4 to 5.6%. Patients who were Black (aOR 0.74; 95% CI 0.58, 0.94) and insured by Medicare versus commercial insurance (aOR 0.61; 95% CI 0.48, 0.78) were less likely to be treated. Higher median household income ($10,000 increment, aOR 1.06; 95% CI 1.03, 1.10) and Medicaid versus commercial insurance (aOR 1.52; 95% CI 1.24, 1.87) were associated with treatment. Receiving pharmacotherapy was associated with subsequent documented abstinence from alcohol (aOR 1.60; 95% CI 1.33, 1.92). We identified 236 PCPs. The average prescription rate was 3.6% (range 0 to 24%). The top decile prescribed to 14.6% of their patients. The bottom 4 deciles had no prescriptions. Family physicians had higher rates of pharmacotherapy than internists (OR 1.50; 95% CI 1.21, 1.85).ConclusionsMedications for AUD are infrequently prescribed, but there is considerable variation among PCPs. Increasing the use of pharmacotherapy by non-prescribers may increase abstinence from alcohol.

Project description:Background and aimsPharmacotherapy can be an important part of the continuum of care for alcohol use disorder (AUD). The Swedish universal health-care system emphasizes provision of care to marginalized groups. The primary aim was to test associations of neighborhood deprivation and disadvantaged social status with receipt of AUD pharmacotherapy in this context.DesignData from linked population registers were used to follow an open cohort over 7 years.SettingSweden.ParticipantsAlcohol-related ICD-10 codes reported for all hospitalizations in the Swedish Hospital Discharge Register and all clinic/office visits in the Outpatient Care Register between 2005 and 2012 were used to identify 62 549 cases with AUD.MeasurementsThe primary outcome was any AUD pharmacotherapy (naltrexone, disulfiram, acamprosate, nalmefene) picked up by patients between 2005 and 2012 (versus none), based on the Swedish Prescribed Drug Register. Neighborhood deprivation was defined using aggregated data from the Total Population Register; indicators of disadvantaged social status (income, education, country of origin) also came from this source.FindingsApproximately half the cases (53.7%) picked up one or more AUD pharmacotherapy prescriptions. In adjusted models, people living in neighborhoods with moderate [odds ratio (OR) = 0.90, 95% confidence interval (CI) = 0.86, 0.95] or high levels of deprivation (OR = 0.75, 95% CI = 0.70, 0.79) compared with low deprivation, those with lower incomes (for example, lowest quartile: OR = 0.70, 95% CI = 0.66, 0.73 compared with highest) and less education (for example, < 10 years: OR = 0.82, 95% CI = 0.78, 0.85 compared with 12+ years) and people born outside Sweden (OR = 0.74, 95% CI = 0.71, 0.78 compared with Swedish-born) were significantly less likely to pick up a prescription for AUD pharmacotherapy during the study period.ConclusionsThere appear to be socio-economic disparities in the receipt of pharmacotherapy for alcohol use disorder in Sweden.

Dataset Information

Primary care engagement is associated with increased pharmacotherapy prescribing for alcohol use disorder (AUD).

Background

Methods

Results

Conclusions

Publications

Primary care engagement is associated with increased pharmacotherapy prescribing for alcohol use disorder (AUD).

Similar Datasets

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