Rural and urban differences in undersupply of buprenorphine provider availability in the United States, 2018.

BACKGROUND: Medications to treat opioid use disorder (OUD) including buprenorphine products are evidence-based and cost-effective tools for combating the opioid crisis. However, limited availability to buprenorphine is pervasive in the United States (US) and may serve to exacerbate the deadly epidemic. Although prior research points to rural counties as especially needy of strategies that improve buprenorphine availability, it is important to investigate the availability of waivered providers according to treatment need as defined by the county-level rate of opioid-overdose deaths (OOD). This study examined differences in buprenorphine provider availability relative to treatment need among rural and urban counties in the US. METHODS: Buprenorphine provider availability relative to need in each county was defined as the number of waivered providers divided by the rate of OODs (i.e., number of OODs/100,000 population), according to 2018 data. Counties with ratios in the bottom tertile of their state were classified as buprenorphine undersupplied. We estimated logit models to statistically test the association of rurality and state main effects and their interaction terms (independent variables) and the county classified as buprenorphine undersupplied (dependent variable). RESULTS: A total of 38 states and 2595 counties had sufficient non-suppressed data to remain in the analysis. A larger percent of urban counties (36.43%) than rural counties (32.01%) were classified as buprenorphine undersupplied (p = 0.001). The likelihood of a rural county being undersupplied varied considerably by state (Chi Square = 82.88, p = 0.000). All states with significant (p < 0.05 or p < 0.10) interaction terms showed lower likelihood of buprenorphine undersupply in rural counties. CONCLUSIONS: The rural-urban distribution in undersupply of waivered buprenorphine providers relative to need varied markedly by state. Strategies for improving access to buprenorphine-waivered providers should be state-centric and informed by county-specific indicators of need.

The Relationship Between Reductions in WHO Risk Drinking Levels During Treatment and Subsequent Healthcare Costs for the ACTIVE Workgroup.

BACKGROUND: Abstinence has historically been considered the target outcome for alcohol use disorder (AUD) treatment, yet recent work has found drinking reductions after AUD treatment, as measured by World Health Organization (WHO) risk drinking levels, are associated with meaningful improvements in functioning, physical health, and quality of life. OBJECTIVES: This study extends previous analyses of AUD treatment outcomes by estimating the association between changes in WHO risk drinking levels (very high, high, medium, and low, based on average daily alcohol consumption) and healthcare costs. METHODS: Secondary data analysis of the COMBINE study, a multisite randomized clinical trial of acamprosate, naltrexone and behavioral interventions for AUD. Generalized gamma regression models were used to estimate relationships between WHOrisk drinking level reductions over the course of treatment and healthcare costs in the year after treatment (N = 964) and up to 3 years following treatment (N = 651). RESULTS: SustainedWHOrisk drinking reductions of 2 or more levels throughout treatment were associated with 52.0% lower healthcare costs ( P < 0.001) in the year following treatment, and 44.0% lower costs ( P < 0.0025) over 3 years. A reduction of exactly 1 level was associated with 34.8% lower costs over 3 years, which was not significant ( P = 0.05). Cost reductions were driven by lower inpatient behavioral health and emergency department utilization. CONCLUSIONS: Reduction in WHO risk drinking levels of at least 2 levels was associated with lower healthcare costs over 1 and 3 years. Our results add to literature showing drinking reductions are associated with improvement in health.

Stability of Drinking Reductions and Long-term Functioning Among Patients with Alcohol Use Disorder.

BACKGROUND: The World Health Organization (WHO) categorizes alcohol consumption according to grams consumed into low-, medium-, high-, and very-high-risk drinking levels (RDLs). Although abstinence has been considered the ideal outcome of alcohol treatment, reductions in WHO RDLs have been proposed as primary outcomes for alcohol use disorder (AUD) trials. OBJECTIVE: The current study examines the stability of WHO RDL reductions and the association between RDL reductions and long-term functioning for up to 3 years following treatment. DESIGN AND PARTICIPANTS: Secondary data analysis of patients with AUD enrolled in the COMBINE Study and Project MATCH, two multi-site, randomized AUD clinical trials, who were followed for up to 3 years post-treatment (COMBINE: n = 694; MATCH: n = 806). MEASURES: Alcohol use was measured via calendar-based methods. We estimated all models in the total sample and among participants who did not achieve abstinence during treatment. KEY RESULTS: One-level RDL reductions were achieved by 84% of patients at the end of treatment, with 84.9% of those individuals maintaining that reduction at a 3-year follow-up. Two-level RDL reductions were achieved by 68% of patients at the end of treatment, with 77.7% of those individuals maintaining that reduction at a 3-year follow-up. One- and two-level RDL reductions at the end of treatment were associated with significantly better mental health, quality of life (including physical quality of life), and fewer drinking consequences 3 years after treatment (p < 0.05), as compared to no change or increased drinking. CONCLUSION: AUD patients can maintain WHO RDL reductions for up to 3 years after treatment. Patients who had WHO RDL reductions functioned significantly better than those who did not reduce their drinking. These findings are consistent with prior reports suggesting that drinking reductions, short of abstinence, yield meaningful improvements in patient health, well-being, and functioning.

Health economic design for cost, cost-effectiveness and simulation analyses in the HEALing Communities Study.

BACKGROUND: The HEALing Communities Study (HCS) is designed to implement and evaluate the Communities That HEAL (CTH) intervention, a conceptually driven framework to assist communities in selecting and adopting evidence-based practices to reduce opioid overdose deaths. The goal of the HCS is to produce generalizable information for policy makers and community stakeholders seeking to implement CTH or a similar community intervention. To support this objective, one aim of the HCS is a health economics study (HES), the results of which will inform decisions around fiscal feasibility and sustainability relevant to other community settings. METHODS: The HES is integrated into the HCS design: an unblinded, multisite, parallel arm, cluster randomized, wait list-controlled trial of the CTH intervention implemented in 67 communities in four U.S. states: Kentucky, Massachusetts, New York, and Ohio. The objectives of the HES are to estimate the economic costs to communities of implementing and sustaining CTH; estimate broader societal costs associated with CTH; estimate the cost-effectiveness of CTH for overdose deaths avoided; and use simulation modeling to evaluate the short- and long-term health and economic impact of CTH, including future overdose deaths avoided and quality-adjusted life years saved, and to develop a simulation policy tool for communities that seek to implement CTH or a similar community intervention. DISCUSSION: The HCS offers an unprecedented opportunity to conduct health economics research on solutions to the opioid crisis and to increase understanding of the impact and value of complex, community-level interventions.

Using Twitter to Surveil the Opioid Epidemic in North Carolina: An Exploratory Study.

BACKGROUND: Over the last two decades, deaths associated with opioids have escalated in number and geographic spread, impacting more and more individuals, families, and communities. Reflecting on the shifting nature of the opioid overdose crisis, Dasgupta, Beletsky, and Ciccarone offer a triphasic framework to explain that opioid overdose deaths (OODs) shifted from prescription opioids for pain (beginning in 2000), to heroin (2010 to 2015), and then to synthetic opioids (beginning in 2013). Given the rapidly shifting nature of OODs, timelier surveillance data are critical to inform strategies that combat the opioid crisis. Using easily accessible and near real-time social media data to improve public health surveillance efforts related to the opioid crisis is a promising area of research. OBJECTIVE: This study explored the potential of using Twitter data to monitor the opioid epidemic. Specifically, this study investigated the extent to which the content of opioid-related tweets corresponds with the triphasic nature of the opioid crisis and correlates with OODs in North Carolina between 2009 and 2017. METHODS: Opioid-related Twitter posts were obtained using Crimson Hexagon, and were classified as relating to prescription opioids, heroin, and synthetic opioids using natural language processing. This process resulted in a corpus of 100,777 posts consisting of tweets, retweets, mentions, and replies. Using a random sample of 10,000 posts from the corpus, we identified opioid-related terms by analyzing word frequency for each year. OODs were obtained from the Multiple Cause of Death database from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER). Least squares regression and Granger tests compared patterns of opioid-related posts with OODs. RESULTS: The pattern of tweets related to prescription opioids, heroin, and synthetic opioids resembled the triphasic nature of OODs. For prescription opioids, tweet counts and OODs were statistically unrelated. Tweets mentioning heroin and synthetic opioids were significantly associated with heroin OODs and synthetic OODs in the same year (P=.01 and P<.001, respectively), as well as in the following year (P=.03 and P=.01, respectively). Moreover, heroin tweets in a given year predicted heroin deaths better than lagged heroin OODs alone (P=.03). CONCLUSIONS: Findings support using Twitter data as a timely indicator of opioid overdose mortality, especially for heroin.

Recovery From Opioid Use Disorder (OUD) After Monthly Long-acting Buprenorphine Treatment: 12-Month Longitudinal Outcomes From RECOVER, an Observational Study.

OBJECTIVES: While evidence has mounted regarding the short-term effectiveness of pharmacotherapy for opioid use disorder (OUD), little is known about longer-term psychosocial, economic, and health outcomes. We report herein 12-month outcomes for an observational study enrolling participants who had previously taken part in a long-acting buprenorphine subcutaneous injection (BUP-XR) trial for moderate to severe OUD. METHODS: The RECOVER (Remission from Chronic Opioid Use: Studying Environmental and SocioEconomic Factors on Recovery; NCT03604861) study enrolled participants from 35 US community-based sites. Self-reported sustained opioid abstinence over 12 months and self-reported past-week abstinence at 3-, 6-, 9-, and 12-month visits were assessed. Multiple regression models assessed the association of BUP-XR duration with abstinence, controlling for potential confounders. Withdrawal, pain, health-related quality of life, depression, and employment at RECOVER baseline and 12-month visits were also compared to values collected before treatment in the BUP-XR trial. RESULTS: Of 533 RECOVER participants, 425 completed the 12-month visit (average age 42 years; 66% male); 50.8% self-reported sustained 12-month and 68.0% past-week opioid abstinence. In multiple regressions, participants receiving 12-month versus ≤2-month BUP-XR treatment duration had significantly higher likelihood of sustained opioid abstinence (75.3% vs 24.1%; P = 0.001), with similar results for past-week self-reported abstinence over time. During RECOVER, participants had fewer withdrawal symptoms, lower pain, positive health-related quality of life, minimal depression, and higher employment versus pre-trial visit. CONCLUSIONS: RECOVER participants reported positive outcomes over the 12-month observational period, including high opioid abstinence and stable or improved humanistic outcomes. These findings provide insights into the long-term impact of pharmacotherapy in OUD recovery.

Estimating Long-Term Drinking Patterns for People with Lifetime Alcohol Use Disorder.

Background. There is a lack of data on alcohol consumption over time. This study characterizes the long-term drinking patterns of people with lifetime alcohol use disorders who have engaged in treatment or informal care. Methods. We developed multinomial logit models using the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) to estimate short-term transition probabilities (TPs) among the 4 World Health Organization drinking risk levels (low, medium, high, and very high risk) and abstinence by age, sex, and race/ethnicity. We applied an optimization algorithm to convert 3-year TPs from NESARC to 1-year TPs, then used simulated annealing to calibrate TPs to a propensity-scored matched set of participants derived from a separate 16-year study of alcohol consumption. We validated the resulting long-term TPs using NESARC-III, a cross-sectional study conducted on a different cohort. Results. Across 24 demographic groups, the 1-year probability of remaining in the same state averaged 0.93, 0.81, 0.49, 0.51, and 0.63 for abstinent, low, medium, high, and very high-risk states, respectively. After calibration to the 16-year study data (N = 420), resulting TPs produced state distributions that hit the calibration target. We find that the abstinent or low-risk states are very stable, and the annual probability of leaving the very high-risk state increases by about 20 percentage points beyond 8 years. Limitations. TPs for some demographic groups had small cell sizes. The data used to calibrate long-term TPs are based on a geographically narrow study. Conclusions. This study is the first to characterize long-term drinking patterns by combining short-term representative data with long-term data on drinking behaviors. Current research is using these patterns to estimate the long-term cost effectiveness of alcohol treatment.

Remission from chronic opioid use-Studying environmental and socio-economic factors on recovery (RECOVER): Study design and participant characteristics.

Few opioid use disorder (OUD) treatment studies measure meaningful life changes during long-term recovery, focusing instead on retention and abstinence. Here, we report on the design and participant characteristics of the RECOVER study, a study exploring life changes in persons with OUD for up to 24 months following participation in a Phase III trial evaluating buprenorphine extended-release monthly injection for subcutaneous use (known as RBP-6000 during development). This multisite, observational, cohort study tracks clinical, environmental, and socio-economic changes using self-administered assessments, urine drug screens (UDS), and public databases. Outcomes include demographics (e.g., patient characteristics, employment history, criminal history), lifetime and recent OUD drug use and treatment, and current health and resource use. Demographic and psychosocial characteristics are compared to a national, population-based study. RECOVER participants (N = 533) tend to be single, white, males aged 26 years or older. Mean age at first opioid use was 21.7 years; lifetime substance-related overdose was 24.2%. At first assessment, 334 (62.7%) participants reported past 7-day and 296 (55.5%) reported past 28-day opioid abstinence. Five hundred UDS were collected at the first assessment; buprenorphine (90.6%), marijuana (45.2%), and opiates (34.4%) were most commonly identified. Two hundred forty-nine (47.2%) participants reported full- or part-time employment. Participants were like a national sample with differences found for age, race/ethnicity, employment, education, and health-related quality of life. We hope that further research using this approach can provide data supporting the patient-centered development of OUD treatments and be adopted by substance use disorder studies to incorporate recovery-related, life-activity outcomes.

Alcohol use and the wage returns to education and work experience.

Despite a widely held belief that alcohol use should negatively impact wages, much of the literature on the topic suggests a positive relationship between nonproblematic alcohol use and wages. Studies on the effect of alcohol use on educational attainment have also failed to find a consistent, negative effect of alcohol use on years of education. Thus, the connections between alcohol use, human capital, and wages remain a topic of debate in the literature. In this study, we use the 1997 cohort of the National Longitudinal Survey of Youth to estimate a theoretical model of wage determination that links alcohol use to wages via human capital. We find that nonbinge drinking is associated with lower wage returns to education whereas binge drinking is associated with increased wage returns to both education and work experience. We interpret these counterintuitive results as evidence that alcohol use affects wages through both the allocative and productive efficiency of human capital formation and that these effects operate in offsetting directions. We suggest that alcohol control policies should be more nuanced to target alcohol consumption in the contexts within which it causes harm.

Estimation of Breast Cancer Incident Cases and Medical Care Costs Attributable to Alcohol Consumption Among Insured Women Aged <45 Years in the U.S.

INTRODUCTION: This study estimated the percentage of breast cancer cases, total number of incident cases, and total annual medical care costs attributable to alcohol consumption among insured younger women (aged 18-44 years) by type of insurance and stage at diagnosis. METHODS: The study used the 2012-2013 National Survey on Drug Use and Health, cancer incidence data from two national registry programs, and published relative risk measures to estimate the: (1) alcohol-attributable fraction of breast cancer cases among younger women by insurance type; (2) total number of breast cancer incident cases attributable to alcohol consumption by stage at diagnosis and insurance type among younger women; and (3) total annual medical care costs of treating breast cancer incident cases attributable to alcohol consumption among younger women. Analyses were conducted in 2016; costs were expressed in 2014 U.S. dollars. RESULTS: Among younger women enrolled in Medicaid, private insurance, and both groups, 8.7% (95% CI=7.4%, 10.0%), 13.8% (95% CI=13.3%, 14.4%), and 12.3% (95% CI=11.4%, 13.1%) of all breast cancer cases, respectively, were attributable to alcohol consumption. Localized stage was the largest proportion of estimated attributable incident cases. The estimated total number of breast cancer incident alcohol-attributable cases was 1,636 (95% CI=1,570, 1,703) and accounted for estimated total annual medical care costs of $148.4 million (95% CI=$140.6 million, $156.1 million). CONCLUSIONS: Alcohol-attributable breast cancer has estimated medical care costs of nearly $150 million per year. The current findings could be used to support evidence-based interventions to reduce alcohol consumption in younger women.

The Association of Job Strain With Medication Adherence: Is Your Job Affecting Your Compliance With a Prescribed Medication Regimen?

OBJECTIVE: This innovative study examines for the first time the relationship between occupational factors (eg, job strain) and medication adherence. METHODS: An analysis of secondary data collected from a randomized controlled trial (RCT) implemented in 34 drugstores of a national pharmacy chain in Tennessee. Medication adherence, health care utilization, psychosocial assessment, chronic disease status, and occupational health history data were obtained from study participants. RESULTS: The study found that most job strains are less adherent to their medication regimen as measured by proportion of days covered (PDC) than those in a low strain job category. However, statistically significant differences are observed only for renin angiotensin system antagonists (RASA), statins, and when PDC is combined across all medication classes. CONCLUSIONS: Examining occupational factors may prove beneficial in developing interventions that improve medication adherence.

The Relationship Between End-of-Treatment Alcohol Use and Subsequent Healthcare Costs: Do Heavy Drinking Days Predict Higher Healthcare Costs?

BACKGROUND: A challenge for evaluating alcohol treatment efficacy is determining what constitutes a "good" outcome or meaningful improvement. Abstinence at the end of treatment is an unambiguously good outcome; however, a focus on abstinence ignores the potential benefits of patients reducing their drinking to less problematic levels. Patients may be drinking at low-risk levels at the end of treatment but may be high-functioning and impose few social costs. In this study, we estimate the relationship between drinking at the end of COMBINE treatment and subsequent healthcare costs with an emphasis on heavy and nonheavy drinking levels. METHODS: Indicators of heavy drinking days (HDDs; 5+ drinks for men, 4+ for women) and nonheavy drinking days (non-HDDs) during the last 30 days of COMBINE treatment were constructed for 748 patients enrolled in the COMBINE Economic Study. Generalized linear models were used to model total costs following COMBINE treatment as a function of drinking indicators. Different model specifications analyzed alternative counts of HDDs (e.g., 1 HDD and 2 to 30 HDDs), and groups having Both non-HDDs and HDDs. RESULTS: Patients with HDDs had 66.4% (p < 0.01) higher healthcare costs than those who were abstinent. Having more than 2 HDDs was associated with the highest costs (75.9%, p < 0.01). Patients with non-HDDs had costs that were not significantly different than abstainers, even if they also had HDDs. However, those with HDDs only had costs 91.7% higher than abstainers (p < 0.01). CONCLUSIONS: Having HDDs at the end of treatment is associated with higher costs. Patients who had Only HDDs at the end of treatment had worse subsequent outcomes than those who had Both non-HDDs and HDDs. These findings offer new context for evaluating treatment outcomes and provide new information on the association of drinking with consequences.

The mental health consequences of nonmedical prescription drug use among adolescents.

BACKGROUND: Nonmedical prescription drug use is estimated to be the second most abused category of drugs after marijuana among adolescents. Prescription drugs can be highly addictive and prolonged use can produce neurological changes and physiological dependence and could result in adverse mental health outcomes. This topic is largely unexplored, as current knowledge of possible mechanisms of the linkage between adverse mental health consequences and prescription drug misuse is limited. AIM OF THE STUDY: This study explores the relationship between nonmedical use of prescription drugs and depression outcomes among adolescents. Given their complex and confounded relationship, our purpose is to better understand the extent to which nonmedical use of prescription drugs is an antecedent of depressive episodes. METHODS: Using data from the 2008-2012 National Survey on Drug Use and Health, the study employs a propensity score matching methodology to ascertain whether nonmedical use of prescription drugs is linked to major depressive episodes among adolescents. RESULTS: The results document a positive relationship between nonmedical prescription drug use and major depressive episodes among adolescents. Specifically, the results indicate that adolescents who used prescription drugs non-medically are 33% to 35% more likely to experience major depressive episodes compared to their non-abusing counterparts. IMPLICATIONS FOR HEALTH POLICY: This provides additional evidence about the potential public health consequences of misuse of prescription drugs on adverse mental health outcomes. Given the significant increased risk of major depressive episode among adolescents who use prescription drugs nonmedically, it seems that the prevention of nonmedical prescription drug use warrants the utilization of both educational and public health resources. IMPLICATIONS FOR FUTURE RESEARCH: An important area for future research is to understand how any policy initiatives in this area must strike a balance between the need to minimize the misuse of prescription drugs and the need to ensure access for their legitimate health care use.

The cost of implementing a jail diversion program for people with mental illness in San Antonio, Texas.

Jail diversion programs for people with mental illness are designed to redirect offenders with mental illness into community treatment. Although much has been published about program models and their successes, little detail is available to policy makers and community stakeholders on the resources required to start and implement a jail diversion program and which agencies bear how much of the burden. The current study used data on a model jail diversion program in San Antonio, Texas, to address this research gap. Data on staff costs, client contacts, planning, and implementation were collected for three types of diversion: pre-booking police, post-booking bond, and post-booking docket. An activity-based costing algorithm was developed to which parameter values were applied. The start-up cost for the program was $556,638.69. Pre-booking diversion cost $370 per person; 90% of costs were incurred by community mental health agencies for short-term monitoring and screening (>80% of activities). Post-booking bond and docket diversion cost $238 and $205 per person, respectively; the majority of costs were incurred by the courts for court decisions. Developing a multiple-intercept jail diversion program requires significant up-front investment. The share of costs varies greatly depending on the type of diversion.

The impact on taxpayer costs of a jail diversion program for people with serious mental illness.

Mental illness is prevalent among those incarcerated. Jail diversion is one means by which people with mental illness are treated in the community - often with some criminal justice system oversight - instead of being incarcerated. Jail diversion may lead to immediate reductions in taxpayer costs because the person is no longer significantly engaged with the criminal justice system. It may also lead to longer term reductions in costs because effective treatment may ameliorate symptoms, reduce the number of future offenses, and thus subsequent arrests and incarceration. This study estimates the impact on taxpayer costs of a model jail diversion program for people with serious mental illness. Administrative data on criminal justice and treatment events were combined with primary and secondary data on the costs of each event. Propensity score methods and a quasi-experimental design were used to compare treatment and criminal justice costs for a group of people who were diverted to a group of people who were not diverted. Diversion was associated with approximately $2800 lower taxpayer costs per person 2 years after the point of diversion (p<.05). Reductions in criminal justice costs drove this result. Jail diversion for people with mental illness may thus be justified fiscally.

Medication costs to private insurers of diversion of medications for attention-deficit hyperactivity disorder.

BACKGROUND: The diversion of prescription stimulants for misuse, particularly those used in the treatment of attention-deficit hyperactivity disorder (ADHD), is potentially a significant problem for public health and for healthcare funding and delivery. Most prior research on the diversion of prescription stimulants for misuse, particularly those used in the treatment of ADHD, has focused on the 'end users' of diverted medications rather than the suppliers. Furthermore, little is known about the direct costs of diversion for third-party insurance payers in the US. OBJECTIVES: The objectives of this study were to estimate the prevalence in the US of people whose private insurance paid costs for ADHD prescriptions that they gave or sold to another person (diversion), and to estimate medication costs of diversion to private insurers. METHODS: Estimates are from a cross-sectional survey of respondents from two Internet survey panels targeting individuals aged 18-49 years in the civilian, noninstitutionalized US population, principally for those who filled prescriptions for ADHD medications in the past 30 days that were covered by private health insurance. Analysis weights were post-stratified to control totals from the Current Population Survey and National Health Interview Survey. Weighted prevalence rates and standard errors for diversion are reported, as are the costs of diverted pills using drug prices reported in the 2008 Thomson Reuters RED BOOK™. Sensitivity analyses were conducted that varied the cost assumptions for medications. RESULTS: Among individuals aged 18-49 years whose private insurance paid some costs for ADHD medications in the past 30 days, 16.6% diverted medications from these prescriptions. Men aged 18-49 years for whom private insurance paid some costs of ADHD drugs in the past 30 days were more than twice as likely as their female counterparts to divert medications from these prescriptions (22.5% vs 9.1%; p = 0.03). After a pro-rated co-payment share was subtracted, the estimated value of diverted medications in a 30-day period was $US8.0 million. Lower- and upper-bound estimates were $US6.9 million to $US17 million, for a range of $US83 million to $US204 million annually. Overall, diversion accounted for about 3.6% of the total costs that private insurers paid for ADHD medications (range: 3.5-4.5%). The percentages varied by medication category, although relative differences were sensitive to inclusion of a pro-rated co-payment. A higher percentage of the costs of extended-release (XR) medications was lost to diversion compared with that for immediate-release (IR) medications. CONCLUSIONS: Costs of ADHD medications paid for by private insurers that were lost to diversion were small relative to the total estimated medication costs and relative to total estimated healthcare costs for treating ADHD. Nevertheless, there may be significant cost savings for insurers if diversion can be reduced, particularly for XR medications. These findings represent a first step to informing policies to reduce diversion both in the interest of public health and for direct and indirect cost savings to insurers.