Medications for Alcohol Use Disorder: Rates and Predictors of Prescription Order and Fill in Outpatient Settings.

BACKGROUND: Alcohol use disorders (AUD) are prevalent and responsible for substantial morbidity and mortality; yet efficacious treatments are underused. Previous studies have identified demographic and clinical predictors of medication fills, yet these studies typically do not include patients who were prescribed a medication but did not fill it. OBJECTIVES: To examine rates of and factors associated with prescription order and prescription fill for medications for AUD (MAUD) among individuals diagnosed with AUD in outpatient settings. DESIGN: In a cross-sectional analysis, we used multivariate logistic regression to identify factors associated with prescription order and fill. PATIENTS: We used data from the Optum Labs Data Warehouse that linked 2016-2021 de-identified claims and electronic health record (EHR) data, allowing us to observe prescription orders and whether they were filled. We identified 14,674 patients aged ≥ 18 who had an index outpatient encounter with an AUD diagnosis in the EHR. KEY MEASURES: We computed the proportion for whom a MAUD prescription was ordered within 1 year of index visit, and for whom one was filled within 30 days of the order. KEY RESULTS: 5.8% of the sample had a MAUD prescription order within 1 year of their index visit. Among those with an order, 87% filled their MAUD prescription within 30 days of receipt (i.e., 5.1% of full sample). After multivariable adjustment, receipt of a MAUD prescription order was more likely for patients who were female (adjusted odds ratio (aOR) [95%CI] = 1.44 [1.24-1.67]), or had moderate or severe AUD (1.74 [1.50-2.01]). Patients receiving an order were more likely to fill it if they had a comorbid mental disorder (1.64 [1.09-2.49]). CONCLUSIONS: The low rate of prescription orders was notable. Low use of MAUD appears to result chiefly from prescription order decisions, rather than from prescription fill decisions made by patients.

Prescribing Medications for Alcohol Use Disorder: A Qualitative Study of Primary Care Physician Decision Making.

PURPOSE: Over 29 million Americans have alcohol use disorder (AUD). Though there are effective medications for AUD (MAUD) that can be prescribed within primary care, they are underutilized. We aimed to explore how primary care physicians familiar with MAUD make prescribing decisions and to identify reasons for underuse of MAUD within primary care. METHODS: We conducted semistructured interviews with 19 primary care physicians recruited from a large online database of medical professionals. Physicians had to have started a patient on MAUD within the last 6 months in an outpatient setting. Inductive and deductive thematic analysis was informed by the theory of planned behavior. RESULTS: Physicians endorsed that it is challenging to prescribe MAUD due to several reasons, including: (1) somewhat negative personal beliefs about medication effectiveness and likelihood of patient adherence; (2) competing demands in primary care that make MAUD a lower priority; and, (3) few positive subjective norms around prescribing. To make MAUD prescribing a smaller component of their practice, physicians reported applying various rules of thumb to select patients for MAUD. These included recommending MAUD to the patients who seemed the most motivated to reduce drinking, those with the most severe AUD, and those who were also receiving other treatments for AUD. CONCLUSIONS: There is a challenging implementation context for MAUD due to competing demands within primary care. Future research should explore which strategies for identifying a subset of patients for MAUD are the most appropriate and most likely to improve population health and health equity.

Financial Sustainability of Novel Delivery Models in Behavioral Health Treatment.

BACKGROUND: In the US, much of the research into new intervention and delivery models for behavioral health care is funded by research institutes and foundations, typically through grants to develop and test the new interventions. The original grant funding is typically time-limited. This implies that eventually communities, clinicians, and others must find resources to replace the grant funding -otherwise the innovation will not be adopted. Diffusion is challenged by the continued dominance in the US of fee-for-service reimbursement, especially for behavioral health care. AIMS: To understand the financial challenges to disseminating innovative behavioral health delivery models posed by fee-for-service reimbursement, and to explore alternative payment models that promise to accelerate adoption by better addressing need for flexibility and sustainability. METHODS: We review US experience with three specific novel delivery models that emerged in recent years. The models are: collaborative care model for depression (CoCM), outpatient based opioid treatment (OBOT), and the certified community behavioral health clinic (CCBHC) model. These examples were selected as illustrating some common themes and some different issues affecting diffusion. For each model, we discuss its core components; evidence on its effectiveness and cost-effectiveness; how its dissemination was funded; how providers are paid; and what has been the uptake so far. RESULTS: The collaborative care model has existed for longest, but has been slow to disseminate, due in part to a lack of billing codes for key components until recently. The OBOT model faced that problem, and also (until recently) a regulatory requirement requiring physicians to obtain federal waivers in order to prescribe buprenorphine. Similarly, the CCBHC model includes previously nonbillable services, but it appears to be diffusing more successfully than some other innovations, due in part to the approach taken by funders. DISCUSSION: A common challenge for all three models has been their inclusion of services that were not (initially) reimbursable in a fee-for-service system. However, even establishing new procedure codes may not be enough to give providers the flexibility needed to implement these models, unless payers also implement alternative payment models. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE: For providers who receive time-limited grant funding to implement these novel delivery models, one key lesson is the need to start early on planning how services will be sustained after the grant ends. IMPLICATIONS FOR HEALTH POLICY: For research funders (e.g., federal agencies), it is clearly important to speed up the process of obtaining coverage for each novel delivery model, including the development of new billable service codes, and to plan for this as early as possible. Funders also need to collaborate with providers early in the grant period on sustainability planning for the post-grant environment. For payers, a key lesson is the need to fold novel models into stable existing funding streams such as Medicaid and commercial insurance coverage, rather than leaving them at the mercy of revolving time-limited grants, and to provide pathways for contracting for innovations under new payment models. IMPLICATIONS FOR FURTHER RESEARCH: For researchers, a key recommendation would be to pay greater attention to the payment environment when designing new delivery models and interventions.

Opioid use disorder Cascade of care framework design: A roadmap.

Unintentional overdose deaths, most involving opioids, have eclipsed all other causes of US deaths for individuals less than 50 years of age. An estimated 2.4 to 5 million individuals have opioid use disorder (OUD) yet a minority receive treatment in a given year. Medications for OUD (MOUD) are the gold standard treatment for OUD however early dropout remains a major challenge for improving clinical outcomes. A Cascade of Care (CoC) framework, first popularized as a public health accountability strategy to stem the spread of HIV, has been adapted specifically for OUD. The CoC framework has been promoted by the NIH and several states and jurisdictions for organizing quality improvement efforts through clinical, policy, and administrative levers to improve OUD treatment initiation and retention. This roadmap details CoC design domains based on available data and potential linkages as individual state agencies and health systems typically rely on limited datasets subject to diverse legal and regulatory requirements constraining options for evaluations. Both graphical decision trees and catalogued studies are provided to help guide efforts by state agencies and health systems to improve data collection and monitoring efforts under the OUD CoC framework.

Evaluating the feasibility and impact of case rate payment for recovery support navigator services: a mixed methods study.

BACKGROUND: Acute 24-h detoxification services (detox) are necessary but insufficient for many individuals working towards long-term recovery from opiate, alcohol or other drug addiction. Longer engagement in substance use disorder (SUD) treatment can lead to better health outcomes and reductions in overall healthcare costs. Connecting individuals with post-detox SUD treatment and supportive services is a vital next step. Toward this end, the Massachusetts Medicaid program reimburses Community Support Program staff (CSPs) to facilitate these connections. CSP support services are typically paid on a units-of-service basis. As part of a larger study testing health care innovations, one large Medicaid insurer developed a new cadre of workers, called Recovery Support Navigators (RSNs). RSNs performed similar tasks to CSPs but received more extensive training and coaching and were paid an experimental case rate (a flat negotiated reimbursement). This sub-study evaluates the feasibility and impact of case rate payments for RSN services as compared to CSP services paid fee-for-service. METHODS: We analyzed claims data and RSN service data for a segment of the Massachusetts Medicaid population who had more than one detox admission in the last year and also engaged in post-discharge CSP or RSN services. Qualitative data from key informant interviews and Learning Collaboratives with CSPs and RSNs supplemented the findings. RESULTS: Clients receiving RSN services under the case rate utilized the service significantly longer than clients receiving CSP services under unit-based billing. This resulted in a lower average cost per member per month for RSN clients. However, when calculating total SUD treatment costs per member, RSN client costs were 50% higher than CSP client costs. Provider organizations employing RSNs successfully implemented case rate billing. Benefits included allowing time for outreach efforts and training and coaching, activities not paid under the unit-based system. Yet, RSNs identified staffing and larger systems level challenges to consider when using a case rate payment model. CONCLUSIONS: Addiction is a chronic disease that requires long-term investments. Case rate billing offers a promising option for payers and providers as it promotes continued engagement with service providers. To fully realize the benefits of case rate billing, however, larger systems level changes are needed.

Cost Savings from a Navigator Intervention for Repeat Detoxification Clients.

BACKGROUND: Many clients with substance use disorders (SUD) have multiple admissions to a 24-hour level of care for detoxification without ever progressing to SUD treatment. In the US, health insurers have become concerned about the high costs and ineffective results of repeat detox admissions. For other diseases, health systems increasingly target high-risk, high-cost patients with individually tailored interventions delivered by `navigators' who help patients negotiate the complex health care system. Patient incentives are another increasingly common intervention. AIMS OF THE STUDY: (i) To examine how health care spending was affected by an intervention intended to improve entry to SUD treatment among clients who had multiple detox admissions. (ii) To see whether spending effects, overall and by type of service, differed by intervention arm. (iii) To assess whether the intervention resulted in net savings from the payer perspective, after subtracting implementation costs. METHODS: The intervention was implemented in a segment of the Massachusetts Medicaid population, and used Recovery Support Navigators (RSNs) who were trained to effectively engage and connect clients with SUD to follow-up care and community resources. Services were funded using a flat daily rate per client. Additionally, in one of the two intervention arms, clients were offered successive incentive payments for meeting pre-specified milestones to reinforce recovery-oriented behaviors. For this paper, multivariate analyses of claims and administrative data were used to measure the intervention's effect on health care spending, and to estimate net savings to the payer. RESULTS: Health care spending grew 1.6 percentage points more slowly for intervention-enrolled members than for others, implying gross savings of $68 per member per month. After subtracting intervention-related costs, net savings were estimated at $57 per member per month. The intervention was also associated with shifts in the health care service mix from more to less acute settings. DISCUSSION: While the results for total spending did not reach statistical significance, they suggest some potential for insurers to reduce the health care costs associated with repeat detox utilization by using a navigator-based intervention. Analyses reported elsewhere found that this intervention had favorable effects on rates of initiation of SUD treatment. Limitations of the study include the fact that neither subjects nor sites were randomized between study groups; lack of data on crime or productivity outcomes; low participant use of RSN services; and a policy change which altered the participant pool and truncated follow-up for some. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE: These results suggest some potential for payers to reduce the health care costs associated with repeat detox by using a navigator-based intervention. To the extent that this results in shifting resources from repeat detox to actual treatment, the result should provide longer term benefit to the population coping with SUD. IMPLICATIONS FOR HEALTH POLICY: These results may encourage Medicaid and other payers to further experiment with similar interventions using navigators to decrease health care costs and improved the lives of SUD patients. IMPLICATIONS FOR FURTHER RESEARCH: It could be informative to test similar navigator interventions for detox patients in other settings where enrollment periods are longer.

The importance of identification when measuring performance in addiction treatment.

Background: Identifying and effectively treating individuals with substance use disorders (SUDs) is an important priority for state Medicaid programs, given the enormous toll that SUDs take on individuals, their families, and their communities. In this paper, we describe how the Healthcare Effectiveness Data and Information Set (HEDIS) measure "Identification of Alcohol and Other Drug Services" can be used, along with eligible population prevalence rates, to expand states' ability to track how well their Medicaid programs identify enrollees with SUDs and link them with treatment (measured by initiation and engagement performance measures). Methods: We use the 2009 Medicaid MAX data on utilization and enrollment along with information from the National Survey of Drug Use and Health (NSDUH) to obtain state-level estimates of alcohol and drug abuse and dependence among Medicaid beneficiaries for 7 illustrative states. We calculate identification, initiation, and engagement measures using specifications from the National Committee on Quality Assurance (NCQA). Results: NSDUH data showed that the eligible population prevalence rate (the average rate of alcohol or drug abuse or dependence) among the 7 states was 10.0%, whereas the average identification rate was 2.9%. The gap between the prevalence and identification rates ranged from 5.1% to 11.0% among the 7 states. The initiation rates ranged from 36.9% to 57.1%. The states' engagement rates ranged from 11.8% to 31.1%, although rates differ by age, gender, and race/ethnicity in some states. Conclusion: Including identification along with initiation and engagement measures allows states to determine how well they are performing in a more complete spectrum from need, to recognition and documentation of enrollees with SUDs, to initiation of treatment, to continuation of early treatment.

Implementing single-item screening for drug use in a Veterans Health Administration outpatient setting.

BACKGROUND: Unhealthy drug use is a concern in many settings, including military and veteran populations. In 2013, the Veterans Health Administration (VHA) medical center in Bedford, Massachusetts, started requiring routine screening for unhealthy drug use in outpatient primary care and mental health settings, using a validated single question. METHODS: This study used descriptive and multivariable analyses of VHA electronic records for patients eligible for the screening program (N = 16,118). The study assessed first-year rates and predictors of screening and of positive screens, both for drug use and for unhealthy alcohol use, for which screening was already required. RESULTS: During the first year, 70% of patients were screened for unhealthy drug use and 84% were screened for unhealthy alcohol use. In multivariable analyses, screening for drug use was more likely for patients who had 8 or more days with VHA visits or were aged 40 or over. Patients with a prior drug use disorder diagnosis were much less likely to be screened. Three percent of patients screened for unhealthy drug use had a positive screen, and 14% of those screened for unhealthy alcohol use had a positive screen. Strong predictors of a positive drug use screen included a prior-year diagnosis of drug use disorder, any mental health clinic visits, younger age, or being unmarried. CONCLUSIONS: The drug screening initiative was relatively successful in its first-year implementation, having screened 70% of eligible subjects. However, it failed to screen many of those most likely to screen positive, thereby missing many opportunities to address unhealthy drug use. Future refinements should include better training clinicians in how to ask sensitive questions and how to address positive screens.

The Role of Health Plans in Supporting Behavioral Health Integration.

Health plan policies can influence delivery of integrated behavioral health and general medical care. This study provides national estimates for the prevalence of practices used by health plans that may support behavioral health integration. Results indicate that health plans employ financing and other policies likely to support integration. They also directly provide services that facilitate integration. Behavioral health contracting arrangements are associated with use of these policies. Delivery of integrated care requires systemic changes by both providers and payers thus health plans are key players in achieving this goal.

Combat-Acquired Traumatic Brain Injury, Posttraumatic Stress Disorder, and Their Relative Associations With Postdeployment Binge Drinking.

OBJECTIVE: To examine whether experiencing a traumatic brain injury (TBI) on a recent combat deployment was associated with postdeployment binge drinking, independent of posttraumatic stress disorder (PTSD). METHODS: Using the 2008 Department of Defense Survey of Health Related Behaviors among Active Duty Military Personnel, an anonymous survey completed by 28 546 personnel, the study sample included 6824 personnel who had a combat deployment in the past year. Path analysis was used to examine whether PTSD accounted for the total association between TBI and binge drinking. MAIN MEASURES: The dependent variable, binge drinking days, was an ordinal measure capturing the number of times personnel drank 5+ drinks on one occasion (4+ for women) in the past month. Traumatic brain injury level captured the severity of TBI after a combat injury event exposure: TBI-AC (altered consciousness only), TBI-LOC of 20 or less (loss of consciousness up to 20 minutes), and TBI-LOC of more than 20 (loss of consciousness >20 minutes). A PTSD-positive screen relied on the standard diagnostic cutoff of 50+ on the PTSD Checklist-Civilian. RESULTS: The final path model found that while the direct effect of TBI (0.097) on binge drinking was smaller than that of PTSD (0.156), both were significant. Almost 70% of the total effect of TBI on binge drinking was from the direct effect; only 30% represented the indirect effect through PTSD. CONCLUSION: Further research is needed to replicate these findings and to understand the underlying mechanisms that explain the relationship between TBI and increased postdeployment drinking.