Cost Offsets of Treatment for Serious Mental Illness and Substance Use Disorder.

OBJECTIVE: The authors examined whether timely treatment for serious mental illness and substance use disorder reduces overall health care costs in a 3-year period. METHODS: Claims data from the IBM MarketScan Research Databases (2010-2017) were analyzed. The population studied included 2,997 Medicaid enrollees and 35,805 commercial insurance enrollees ages 18-64 years with an index event for a serious mental illness and 2,315 Medicaid enrollees and 28,419 commercial insurance enrollees with an index event for a substance use disorder. Health care costs in the 3 years after an index event were calculated for enrollees who received care that met a minimum threshold for treatment and for those who did not receive such care. The Toolkit for Weighting and Analysis of Nonequivalent Groups was used to control for statistically significant differences in pretreatment characteristics between the groups. RESULTS: All health care spending for enrollees who were engaged in behavioral health treatment for substance use disorder or a serious mental illness increased from year 0 to year 1 but decreased faster than the spending of enrollees who were not engaged in treatment, with larger trends for those engaged in substance use disorder treatment. Expenses for inpatient and emergency department care decreased over the 3 follow-up years; however, spending on outpatient services was significantly higher in all 3 follow-up years for those engaged in treatment. CONCLUSIONS: Health care delivery and payment models that improve access to behavioral health treatment may reduce emergency department, inpatient, and overall health care costs for particular subpopulations.

Rural-Nonrural Differences in Telemedicine Use for Mental and Substance Use Disorders Among Medicaid Beneficiaries.

OBJECTIVE: This study investigated recent rural-nonrural trends in the prevalence and amount of mental and substance use disorder telemedicine received by adult Medicaid beneficiaries. METHODS: An analysis of 2012-2017 claims data from the IBM MarketScan Multi-State Medicaid Database for adult beneficiaries ages 18-64 years with mental and substance use disorder diagnoses (N= 1,603,066) identified telemedicine services by using procedure modifier codes and ICD-9 and ICD-10 diagnosis codes. Unadjusted trends in telemedicine use were examined, and multivariate regression models compared the prevalence and amount of telemedicine and in-person outpatient treatment received by rural (N=428,697) and nonrural (N= 1,174,369) beneficiaries and by diagnosis. RESULTS: Rates of telemedicine treatment for mental and substance use disorders among Medicaid beneficiaries increased during the study period but remained low. Among rural beneficiaries, there was a 5.9 percentage point increase in telemedicine for mental disorders and a 1.9 percentage point increase in telemedicine for substance use disorders. After control for other individual characteristics, rural beneficiaries were more likely than nonrural beneficiaries to receive any telemedicine for mental disorder (2.2 percentage points more likely) or substance use disorder (0.6 percentage points) treatment. Receipt of telemedicine was associated with receipt of more in-person outpatient services by rural beneficiaries (11.2 more visits for mental disorders and 8.2 more for substance use disorders). CONCLUSIONS: Although provision of telemedicine for mental and substance use disorders increased during the study period and was somewhat more common among rural Medicaid beneficiaries, it remains an underused resource for addressing care shortages in rural areas.

Insurance Financing Increased For Mental Health Conditions But Not For Substance Use Disorders, 1986-2014.

This study updates previous estimates of US spending on mental health and substance use disorders through 2014. The results reveal that the long-term trend of greater insurance financing of mental health care continued in recent years. The share of total mental health treatment expenditures financed by private insurance, Medicare, and Medicaid increased from 44 percent in 1986 to 68 percent in 2014. In contrast, the share of spending for substance use disorder treatment financed by private insurance, Medicare, and Medicaid was 45 percent in 1986 and 46 percent in 2014. From 2004 to 2013, a growing percentage of adults received mental health treatment (12.6 percent and 14.6 percent, respectively), albeit only because of the increased use of psychiatric medications. In the same period, only 1.2-1.3 percent of adults received substance use disorder treatment in inpatient, outpatient, or residential settings, although the use of medications to treat substance use disorders increased rapidly.

Evaluating the inverse reasoning account of object discovery.

People routinely make inferences about unobserved objects. A hotel guest with welts on his arms, for example, will often worry about bed bugs. The discovery of unobserved objects almost always involves a backward inference from some observed effects (e.g., welts) to unobserved causes (e.g., bed bugs). The inverse reasoning account, which is typically formalized as Bayesian inference, posits that the strength of a backward inference is closely connected to the strength of the corresponding forward inference from the unobserved causes to the observed effects. We evaluated the inverse reasoning account of object discovery in three experiments where participants were asked to discover the unobserved "attractors" and "repellers" that controlled a "particle" moving within an arena. Experiments 1 and 2 showed that participants often failed to provide the best explanations for various particle motions, even when the best explanations were simple and when participants enthusiastically endorsed these explanations when presented with them. This failure demonstrates that object discovery is critically dependent on the processes that support hypothesis generation-processes that the inverse reasoning account does not explain. Experiment 3 demonstrated that people sometimes generate explanations that are invalid even according to their own forward inferences, suggesting that the psychological processes that support forward and backward inference are less intertwined than the inverse reasoning account suggests. The experimental findings support an alternative account of object discovery in which people rely on heuristics to generate possible explanations.

Inferential dependencies in causal inference: a comparison of belief-distribution and associative approaches.

Causal evidence is often ambiguous, and ambiguous evidence often gives rise to inferential dependencies, where learning whether one cue causes an effect leads the reasoner to make inferences about whether other cues cause the effect. There are 2 main approaches to explaining inferential dependencies. One approach, adopted by Bayesian and propositional models, distributes belief across multiple explanations, thereby representing ambiguity explicitly. The other approach, adopted by many associative models, posits within-compound associations--associations that form between potential causes--that, together with associations between causes and effects, support inferences about related cues. Although these fundamentally different approaches explain many of the same results in the causal literature, they can be distinguished, theoretically and experimentally. We present an analysis of the differences between these approaches and, through a series of experiments, demonstrate that models that distribute belief across multiple explanations provide a better characterization of human causal reasoning than models that adopt the associative approach.

Convergence of service, policy, and science toward consumer-driven mental health care.

BACKGROUND: A common theme is emerging in sentinel reports on the United States health care system. Consumer relevance and demands on service systems and practices are influencing how mental health care is delivered and how systems will be shaped in the future. AIMS OF THE STUDY: The present report seeks to assemble a confluence of consumer-driven themes from noteworthy reports on the state of the mental health system in the U.S. It also explores innovative efforts, promising practices, collaborative efforts, as well as identification of barriers to consumer-directed care, with possible solutions. METHOD: The report reviews the relevant public mental health policy and data used in published work. RESULTS: The findings indicate an increasing public and private interest in promoting consumer-driven care, even though historical systems of care predominate, and often create, barriers to wide-spread redesign of a consumer-centered mental health care system. Innovative consumer-driven practices are increasing as quality, choice, and self-determination become integral parts of a redesigned U.S. mental health care system. DISCUSSION AND LIMITATIONS: The use of consumer-driven approaches in mental health is limited at best. These programs challenge industry norms and traditional practices. Limitations include the need for additional and thorough evaluations of effectiveness (cost and clinical) and replicability of consumer-directed programs. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE: Consumer-driven services indicate that mental health consumers are expecting to be more participative in their mental health care. This expectation will influence how traditional mental health services and providers become more consumer-centric and meet the demand. IMPLICATIONS FOR HEALTH POLICIES: Public and private interest in consumer-driven health care range from creating cost-conscious consumers to individualized control of recovery. The health care sector should seek to invest more resources in the provision of consumer-driven health care programs. The results of this study have implications and are informative for other countries where consumer-directed care is delivered in either the private or public health care systems. IMPLICATIONS FOR FURTHER RESEARCH: More research is needed to obtain further evidence on the use of consumer-driven services and their overall effectiveness.