Ryan Mutter

The role of perceived need and health insurance in substance use treatment: Implications for the Affordable Care Act☆

The expansions in insurance coverage under the Patient Protection & Affordable Care Act (ACA) that took full effect in 2014 have been projected to increase the number of users of behavioral health services. By analyzing data from the 2008-2012 National Survey on Drug Use and Health, this paper examines whether health insurance expansion may result in an increase in substance use disorder (SUD) treatment utilization. The study sample includes 18,600 adults with SUD but no diagnosable mental health condition. The analysis finds that over 80% of that population receives no treatment and 97% do not perceive a need for treatment. When they do receive treatment, they are more likely to receive mental health treatment. Using multinomial logistic regression, the study finds that having Medicaid or private insurance is associated with higher likelihood of receiving SUD treatment, but only when individuals perceive a need for it, compared to being uninsured and not perceiving a need for treatment (the reference category). These results indicate that increased service utilization is associated with perceiving a need for substance abuse treatment, implying that outreach initiatives to raise awareness about SUD and the effective role of substance use treatment are needed to enhance the impact of the structural changes to the substance abuse treatment system resulting from the ACA.

Prescription drug monitoring programs, nonmedical use of prescription drugs, and heroin use: Evidence from the National Survey of Drug Use and Health.

In the United States, nonmedical prescription opioid use is a major public health concern. Various policy initiatives have been undertaken to tackle this crisis, including state prescription drug monitoring programs (PDMPs). This study uses the 2004-2014 National Survey of Drug Use and Health (NSDUH) and exploits state-level variation in the timing of PDMP implementation and PDMP characteristics to investigate whether PDMPs are associated with a reduction in prescription opioid misuse or whether they have the unintended consequence of increasing heroin use. In addition, the study examines the impact of PDMPs on the availability of opioids from various sources. The study finds no effect of PDMP status on various measures of nonmedical prescription opioid use (abuse, dependence, and initiation), but finds evidence of a reduction in the number of days of opioid misuse in the past year. The study also finds that implementation of PDMP was not associated with an increase in heroin use or initiation, but was associated with an increase in number of days of heroin use in the past year. Findings also suggest that PDMPs were associated with a significant decline in doctor shopping among individuals without increasing reliance on illegal sources (e.g., drug dealers, stealing, etc.) or social sources (friends or relatives) as a means of obtaining opioids. The Presidents FY2017 budget proposed the allocation of

Using social media to monitor mental health discussions − evidence from Twitter

1.1 billion in an effort to reduce prescription drug misuse, and highlighted the use of PDMPs as a policy tool. This study documents evidence that PDMPs might be having measurable impact.

The Association of Hospital Cost-Inefficiency With Certificate-of-Need Regulation:

Objectives Given the public health importance of communicating about mental illness and the growing use of social media to convey information, our goal was to develop an empirical model to identify periods of heightened interest in mental health topics on Twitter. Materials and Methods We collected data on 176 million tweets from 2011 to 2014 with content related to depression or suicide. Using an autoregressive integrated moving average (ARIMA) data analysis, we identified deviations from predicted trends in communication about depression and suicide. Results Two types of heightened Twitter activity regarding depression or suicide were identified in 2014: expected increases in response to planned behavioral health events, and unexpected increases in response to unanticipated events. Tweet volume following expected increases went back to the predicted level more rapidly than the volume following unexpected events. Discussion Although ARIMA models have been used extensively in other fields, they have not been used widely in public health. Our findings indicate that our ARIMA model is valid for identifying periods of heightened activity on Twitter related to behavioral health. The model offers an objective and empirically based measure to identify periods of greater interest for timing the dissemination of credible information related to mental health. Conclusion Spikes in tweet volume following a behavioral health event often last for less than 2 days. Individuals and organizations that want to disseminate behavioral health messages on Twitter in response to heightened periods of interest need to take this limited time frame into account.

Post-Discharge Treatment Engagement Among Patients with an Opioid-Use Disorder

Certificate-of-need (CON) regulations can promote hospital efficiency by reducing duplication of services; however, there are practical and theoretical reasons why they might be ineffective, and the empirical evidence generated has been mixed. This study compares the cost-inefficiency of urban, acute care hospitals in states with CON regulations against those in states without CON requirements. Stochastic frontier analysis was performed on pooled time-series, cross-sectional data from 1,552 hospitals in 37 states for the period 2005 to 2009 with controls for variations in hospital product mix, quality, and patient burden of illness. Average estimated cost-inefficiency was less in CON states (8.10%) than in non-CON states (12.46%). Results suggest that CON regulation may be an effective policy instrument in an era of a new medical arms race. However, broader analysis of the effects of CON regulation on efficiency, quality, access, prices, and innovation is needed before a policy recommendation can be made.

Reasons for Not Seeking Substance Use Disorder Treatment: Variations by Health Insurance Coverage

INTRODUCTION Opioid misuse is a growing public health problem, and estimates show a 150% increase in opioid-related hospital stays over the last two decades. This study examined factors associated with substance use treatment engagement following a hospitalization for opioid use disorder or overdose. METHODS This study analyzed the Truven Health Analytics MarketScan® Commercial Claims and Encounters (CCAE) database for 2010 through 2014 to study post-hospitalization substance use disorder (SUD) treatment of individuals aged 18-64 who had an inpatient admission for an opioid-use disorder or opioid overdose. Engagement in post-discharge SUD treatment was defined as having at least two unique outpatient visits within 30 days of a hospitalization. Generalized estimating equations (GEEs) with a binomial link were used to determine the factors associated with SUD treatment engagement. RESULTS Only 17% of patients engaged in SUD treatment within 30 days of hospital discharge. A behavioral health outpatient visit prior to the SUD admission increased the odds of engaging in SUD treatment by 1.34 (CI: 1.25-1.45), an antidepressant prescription drug fill prior to the SUD admission increased the odds by 1.14 (CI: 1.07-1.21), a benzodiazepine fill prior to the SUD admission increased the odds by 1.14 (CI: 1.07-1.21), a principal diagnosis for an SUD at index admission increased the odds by 2.13 (CI: 1.97-2.30), an alcohol-related disorder diagnosis at index admission increased the odds by 3.13 (CI: 2.87-3.42), and an additional SUD diagnosis at the index admission increased the odds by 2.72 (CI: 2.48-2.98). CONCLUSIONS We found low rates of SUD treatment engagement following hospitalizations for opioid use disorders and overdoses. Patients with prior engagements with behavioral health providers were more likely to engage in follow-up care; therefore, providers may need to focus additional efforts on patients admitted to the hospital with opioid-use disorders who do not have an existing provider relationship.

Factors associated with substance use treatment completion in residential facilities.

A large number of adults with substance use disorder (SUD) do not receive treatment for their condition. Using data from the 2008–2013 National Survey of Drug Use and Health (NSDUH), this study analyzes why individuals with SUD report not receiving treatment even when they perceived a need for it. It further examines the variations in reported reasons for not receiving treatment by health insurance status and type. The results suggest that barriers such as stigma, lack of readiness to stop using substances, and not making treatment a priority are more common among the insured population, especially among those with private insurance. Financial barriers, such as not being able to afford the cost of treatment, are more prominent among the uninsured population. Efforts to improve utilization of treatment services will need to address financial as well as barriers related to stigma.

Opioid-overdose laws association with opioid use and overdose mortality

PURPOSE Individuals in residential treatment often face many challenges, which can include limited education, unstable housing, difficulty participating in the workforce, and severe substance use problems. We analyzed factors associated with substance use treatment completion. We focused on factors that can be influenced by health care system changes resulting from the Affordable Care Act (ACA). DATA AND METHODS We used the 2010 Treatment Episode Data Set - Discharges (TEDS-D), which is made available by the Substance Abuse and Mental Health Services Administration (SAMHSA). We analyzed factors associated with substance use treatment completion using logistic regression. RESULTS Individuals in residential treatment were often unemployed or not in the labor force, had prior substance use treatment episodes, used more than one substance, and were uninsured. Factors associated with treatment completion included older age, greater education, employment, criminal justice referral, not being homeless, and private insurance. CONCLUSION The expansion in private insurance coverage as a result of the ACA may result in more treatment completion in residential settings. Changes to the Medicaid program resulting from the ACA, including coverage of substance use treatment as an essential health benefit and greater support for housing, education, and employment, may also contribute to more residential discharges ending in treatment completion.

Using Healthcare Cost and Utilization Project (HCUP) Data for Emergency Medicine Research

INTRODUCTION Since the 1990s, governmental and non-governmental organizations have adopted several measures to increase access to the opioid overdose reversal medication naloxone. These include the implementation of laws that increase layperson naloxone access and overdose-specific Good Samaritan laws that protect those reporting overdoses from criminal sanction. The association of these legal changes with overdose mortality and non-medical opioid use is unknown. We assess the relationship of (1) naloxone access laws and (2) overdose Good Samaritan laws with opioid-overdose mortality and non-medical opioid use in the United States. METHODS We used 2000-2014 National Vital Statistics System data, 2002-2014 National Survey on Drug Use and Health data, and primary datasets of the location and timing of naloxone access laws and overdose Good Samaritan laws. RESULTS By 2014, 30 states had a naloxone access and/or Good Samaritan law. States with naloxone access laws or Good Samaritan laws had a 14% (p = 0.033) and 15% (p = 0.050) lower incidence of opioid-overdose mortality, respectively. Both law types exhibit differential association with opioid-overdose mortality by race and age. No significant relationships were observed between any of the examined laws and non-medical opioid use. CONCLUSIONS Laws designed to increase layperson engagement in opioid-overdose reversal were associated with reduced opioid-overdose mortality. We found no evidence that these measures were associated with increased non-medical opioid use.

Factors that affect choice of mental health provider and receipt of outpatient mental health treatment

Hospital billing data have been used by researchers and policymakers for decades to monitor trends in hospital stays, emergency department (ED) visits, and ambulatory surgery care. One important source for these data is the Healthcare Cost and Utilization Project (HCUP), which is sponsored by the Agency for Healthcare Research and Quality (AHRQ), part of the US Department of Health and Human Services. In this issue, Kocher et al use the HCUP Nationwide Inpatient Sample to examine the association between the volume of ED encounters that result in admission and inpatient mortality. HCUP produces multiple health care databases, including the State Emergency Department Databases (SEDD), State Inpatient Databases (SID), the Nationwide Emergency Department Sample (NEDS), and the Nationwide Inpatient Sample annually, along with related software tools and information products. In 2012, 47 state data organizations, hospital associations, and private data organizations participated in the HCUP partnership, all of which contribute inpatient data and 31 of which contribute treat-andrelease ED data. A subset of theHCUPPartners elects to make their data available to the public through theHCUPCentral Distributor. Price information for HCUP Central Distributor data, including student discounts, online training, and the data use agreement that must be signed, are available on theHCUPUser SupportWeb site. HCUP began releasing SEDD files through the Central Distributor in 1999. The SEDD capture encounters at hospitalaffiliated EDs that do not result in hospitalization at the same facility. The SEDD data can be combined with data on admissions from the ED found in the SID to yield the census of ED encounters in acute care community hospitals in a state. HCUP also creates the NEDS by using ED encounters from the SEDD and SID as a sampling frame to yield national estimates of ED encounters.With nearly 30 million unweighted records representing more than 130 million ED visits, the NEDS, a stratified 20% probability sample of hospital-based EDs, is the largest all-payer ED database in the United States. The stratification variables for the NEDS are US census region, trauma center designation, urban-rural location of the hospital, ownership, and teaching status. The NEDS has been available through the Central Distributor since 2006. Observation services encounters are also captured on someHCUP inpatient and