Financing the "Village": Establishing a Sustainable Financial System for Child Behavioral Health.

An increased need for child and adolescent behavioral health services compounded by a long-standing professional workforce shortage frames our discussion on how behavioral health services can be sustainably delivered and financed. This article provides an overview of different payment models, such as traditional fee-for-service and alternatives like provider salary, global payments, and pay for performance models. It discusses the advantages and drawbacks of each model, emphasizing the need to transition toward value-based care to improve health care quality and control costs.

Racial-Ethnic Disparities in Quality of Care Among Medicaid Beneficiaries With Schizophrenia.

OBJECTIVE: The authors sought to update and expand the evidence on the quality of health care and disparities in care among Medicaid beneficiaries with schizophrenia. METHODS: Adult beneficiaries of New York State Medicaid with schizophrenia receiving care during 2016-2019 were identified. Composite quality scores were derived from item response theory models by using evidence-based indicators of the quality of mental and general medical health care. Risk-adjusted racial-ethnic differences in quality were estimated and summarized as percentiles relative to White beneficiaries' mean quality scores. RESULTS: The study included 71,013 beneficiaries; 42.8% were Black, 22.9% Latinx, 27.4% White, and 6.9% other race-ethnicity. Overall, 68.8% had a mental health follow-up within 30 days of discharge, and 90.2% had no preventable hospitalizations for chronic obstructive pulmonary disease or asthma. Among beneficiaries receiving antipsychotic medications, medication adherence was adequate for 43.7%. Fourteen indicators for mental and general medical health care quality yielded three composites: two for mental health care (pharmacological and ambulatory) and one for acute mental and general medical health care. Mean quality of pharmacological mental health care for Black and Latinx beneficiaries was lower than for White beneficiaries (39th and 44th percentile, respectively). For Black beneficiaries, mean quality of ambulatory mental health care was also lower (46th percentile). In New York City, Black beneficiaries received lower-quality care in all domains. The only meaningful group difference in the quality of acute mental and general medical health care indicated higher-quality care for individuals with other race-ethnicity. CONCLUSIONS: Disparities in the quality of Medicaid-financed health care persist, particularly for Black beneficiaries. Regional differences merit further attention.

Racial and Ethnic Concordance Between National Health Service Corps Clinicians and Underserved Populations.

Importance: Despite the widely recognized importance of racial and ethnic concordance between patients and clinicians, there is a lack of studies on clinician diversity in medically underserved areas and whether it aligns with the changing demographic landscape. Objective: To assess trends in National Health Services Corps (NHSC) clinician diversity and racial and ethnic concordance between NHSC clinicians and the populations in underserved areas from before to after the 2009 NHSC expansion. Design, Setting, and Participants: This cross-sectional, population-based study compared trends in the diversity of NHSC clinicians practicing in health professional shortage areas (HPSAs) and the HPSA populations during 2003 to 2019 using the Health Resources and Services Administration's NHSC Field Strength Database and Area Health Resources Files. The analysis was performed from February through May 2023. Main Outcomes and Measures: Concordance was measured with an annual community representativeness ratio defined as the ratio of the proportions of same race or ethnicity NHSC clinicians to HPSA population. Results: There were a total of 41 180 clinicians practicing in HPSAs from 2003 to 2019; the median (IQR) age was 34 (30-41) years. Among 38 569 NHSC clinicians who reported gender, 28 444 (73.7%) identified as female and 10 125 (26.3%) identified as male. The average annual number of NHSC clinicians increased from 3357 in 2003 to 2008 to 9592 in 2009 to 2019. Before 2009, 1076 clinicians (5.3%) identified as Black, 9780 (48.6%) as Hispanic, 908 (4.5%) as other, and 8380 (41.6%) as White. During this period, concordance was low among non-Hispanic White and Black individuals due to clinician underrepresentation relative to the population, yet Hispanic clinicians were overrepresented. Following the 2009 NHSC expansion, the main change was the sharp decline in the proportion of Hispanic clinicians, to 1601 (13%) by 2019; while concordance was achieved for non-Hispanic White and Black individuals, Hispanic clinicians became underrepresented relative to population. The results held across 3 specialties: primary care, mental health care, and dental care. Conclusions and Relevance: This cross-sectional study of trends in racial and ethnic concordance found that while the NHSC expansion starting in 2009 improved clinician-population concordance for non-Hispanic White and Black individuals, it reversed a prior trend for Hispanic individuals among whom clinicians became underrepresented relative to the population. Targeted NHSC clinician recruitment efforts are needed to improve concordance for Hispanic individuals in underserved areas, especially given Hispanics' projected growth in the US.

Targeted learning in observational studies with multi-valued treatments: An evaluation of antipsychotic drug treatment safety.

We investigate estimation of causal effects of multiple competing (multi-valued) treatments in the absence of randomization. Our work is motivated by an intention-to-treat study of the relative cardiometabolic risk of assignment to one of six commonly prescribed antipsychotic drugs in a cohort of nearly 39 000 adults with serious mental illnesses. Doubly-robust estimators, such as targeted minimum loss-based estimation (TMLE), require correct specification of either the treatment model or outcome model to ensure consistent estimation; however, common TMLE implementations estimate treatment probabilities using multiple binomial regressions rather than multinomial regression. We implement a TMLE estimator that uses multinomial treatment assignment and ensemble machine learning to estimate average treatment effects. Our multinomial implementation improves coverage, but does not necessarily reduce bias, relative to the binomial implementation in simulation experiments with varying treatment propensity overlap and event rates. Evaluating the causal effects of the antipsychotics on 3-year diabetes risk or death, we find a safety benefit of moving from a second-generation drug considered among the safest of the second-generation drugs to an infrequently prescribed first-generation drug known for having low cardiometabolic risk.

Healthcare Access for a Diverse Population with Schizophrenia Following the Onset of the COVID-19 Pandemic.

COVID-19 has had a disproportionate impact on the most disadvantaged members of society, including minorities and those with disabling chronic illnesses such as schizophrenia. We examined the pandemic's impacts among New York State's Medicaid beneficiaries with schizophrenia in the immediate post-pandemic surge period, with a focus on equity of access to critical healthcare. We compared changes in utilization of key behavioral health outpatient services and inpatient services for life-threatening conditions between the pre-pandemic and surge periods for White and non-White beneficiaries. We found racial and ethnic differences across all outcomes, with most differences stable over time. The exception was pneumonia admissions-while no differences existed in the pre-pandemic period, Black and Latinx beneficiaries were less likely than Whites to be hospitalized in the surge period despite minorities' heavier COVID-19 disease burden. The emergence of racial and ethnic differences in access to scarce life-preserving healthcare may hold lessons for future crises.

Antipsychotics and the risk of diabetes and death among adults with serious mental illnesses.

BACKGROUND: Individuals with schizophrenia exposed to second-generation antipsychotics (SGA) have an increased risk for diabetes, with aripiprazole purportedly a safer drug. Less is known about the drugs' mortality risk or whether serious mental illness (SMI) diagnosis or race/ethnicity modify these effects. METHODS: Authors created a retrospective cohort of non-elderly adults with SMI initiating monotherapy with an SGA (olanzapine, quetiapine, risperidone, and ziprasidone, aripiprazole) or haloperidol during 2008-2013. Three-year diabetes incidence or all-cause death risk differences were estimated between each drug and aripiprazole, the comparator, as well as effects within SMI diagnosis and race/ethnicity. Sensitivity analyses evaluated potential confounding by indication. RESULTS: 38 762 adults, 65% White and 55% with schizophrenia, initiated monotherapy, with haloperidol least (6%) and quetiapine most (26·5%) frequent. Three-year mortality was 5% and diabetes incidence 9.3%. Compared with aripiprazole, haloperidol and olanzapine reduced diabetes risk by 1.9 (95% CI 1.2-2.6) percentage points, or a 18.6 percentage point reduction relative to aripiprazole users' unadjusted risk (10.2%), with risperidone having a smaller advantage. Relative to aripiprazole users' unadjusted risk (3.4%), all antipsychotics increased mortality risk by 1.1-2.2 percentage points, representing 32.4-64.7 percentage point increases. Findings within diagnosis and race/ethnicity were generally consistent with overall findings. Only quetiapine's higher mortality risk held in sensitivity analyses. CONCLUSIONS: Haloperidol's, olanzapine's, and risperidone's lower diabetes risks relative to aripiprazole were not robust in sensitivity analyses but quetiapine's higher mortality risk proved robust. Findings expand the evidence on antipsychotics' risks, suggesting a need for caution in the use of quetiapine among individuals with SMI.

Statistical Approaches for Quantifying the Quality of Neurosurgical Care.

BACKGROUND: Quantifying quality of health care can provide valuable information to patients, providers, and policy makers. However, the observational nature of measuring quality complicates assessments. METHODS: We describe a conceptual model for defining quality and its implications about the data collected, how to make inferences about quality, and the assumptions required to provide statistically valid estimates. Twenty-one binary or polytomous quality measures collected from 101,051 adult Medicaid beneficiaries aged 18-64 years with schizophrenia from 5 U.S. states show methodology. A categorical principal components analysis establishes dimensionality of quality, and item response theory models characterize the relationship between each quality measure and a unidimensional quality construct. Latent regression models estimate racial/ethnic and geographic quality disparities. RESULTS: More than 90% of beneficiaries filled at least 1 antipsychotic prescription and 19% were hospitalized for schizophrenia during a 12-month observational period in our multistate cohort with approximately 2/3 nonwhite beneficiaries. Four quality constructs emerged: inpatient, emergency room, pharmacologic/ambulatory, and ambulatory only. Using a 2-parameter logistic model, pharmacologic/ambulatory care quality varied from -2.35 to 1.26 (higher = better quality). Black and Latinx beneficiaries had lower pharmacologic/ambulatory quality compared with whites. Race/ethnicity modified the association of state and pharmacologic/ambulatory care quality in latent regression modeling. Average quality ranged from -0.28 (95% confidence interval, -2.15 to 1.04) for blacks in New Jersey to 0.46 [95% confidence interval, -0.89 to 1.40] for whites in Michigan. CONCLUSIONS: By combining multiple quality measures using item response theory models, a composite measure can be estimated that has more statistical power to detect differences among subjects than the observed mean per subject.

Building Bridges Between Evidence and Policy in Mental Health Services Research: Introducing the Policy Review Article Type.

Although it is widely accepted that patients do better when evidence-based health care practices are used, there is less acknowledgment of the positive outcomes associated with evidence-based policy making. To address the need for high-quality evidence to inform mental health policies, Psychiatric Services has recently launched a new article format: the Policy Review. This review type defines a specific policy-relevant issue affecting behavioral health systems, describes current knowledge and limitations, and discusses policy implications. Reviews can focus on mental health policies or examine how other health or social policies affect people with mental illness or substance use disorders. This brief overview of the need for a policy review article type describes differences between evidence-based policy making and practices and looks at research approaches focused on evidence-based policy making, as well as legislative and other efforts to support it. Broad guidelines for potential submissions are also provided.

Significance and Factors Associated with Antipsychotic Polypharmacy Utilization Among Publicly Insured US Adults.

Antipsychotic polypharmacy (APP) lacks evidence of effectiveness in the care of schizophrenia or other disorders for which antipsychotic drugs are indicated, also exposing patients to more risks. Authors assessed APP prevalence and APP association with beneficiary race/ethnicity and payer among publicly-insured adults regardless of diagnosis. Retrospective repeated panel study of fee-for-service (FFS) Medicare, Medicaid, and dually-eligible white, black, and Latino adults residing in California, Georgia, Iowa, Mississippi, Oklahoma, South Dakota, or West Virginia, filling antipsychotic prescriptions between July 2008 and June 2013. Primary outcome was any monthly APP utilization. Across states and payers, 11% to 21% of 397,533 antipsychotic users and 12% to 19% of 9,396,741 person-months had some APP utilization. Less than 50% of person-months had a schizophrenia diagnosis and up to 19% had no diagnosed mental illness. Payer modified race/ethnicity effects on APP utilization only in CA; however, the odds of APP utilization remained lower for minorities than for whites. Elsewhere, the odds varied by race/ethnicity only in OK, with Latinos having lower odds than whites (odds ratio 0.76; 95% confidence interval 0.60-0.96). The odds of APP utilization varied by payer in several study states, with odds generally higher for Dual eligibles, although the differences were generally small; the odds also varied by year (lower at study end). APP was frequently utilized but mostly declined over time. APP utilization patterns varied across states, with no consistent association with race/ethnicity and small payer effects. Greater use of APP-reducing strategies are needed, particularly among non-schizophrenia populations.

Empirically identified networks of healthcare providers for adults with mental illness.

BACKGROUND: Policies target networks of providers who treat people with mental illnesses, but little is known about the empirical structures of these networks and related variation in patient care. The goal of this paper is to describe networks of providers who treat adults with mental illness in a multi-payer database based medical claims data in a U.S. state. METHODS: Provider networks were identified and characterized using paid inpatient, outpatient and pharmacy claims related to care for people with a mental health diagnosis from an all-payer claims dataset that covers both public and private payers. RESULTS: Three nested levels of network structures were identified: an overall network, which included 21% of providers (N = 8256) and 97% of patients (N = 476,802), five communities and 24 sub-communities. Sub-communities were characterized by size, provider composition, continuity-of-care (CoC), and network structure measures including mean number of connections per provider (degree) and average number of connections who were connected to each other (transitivity). Sub-community size was positively associated with number of connections (r = .37) and the proportion of psychiatrists (r = .41) and uncorrelated with network transitivity (r = -.02) and continuity of care (r = .00). Network transitivity was not associated with CoC after adjustment for provider type, number of patients, and average connection CoC (p = .85). CONCLUSIONS: These exploratory analyses suggest that network analysis can provide information about the networks of providers that treat people with mental illness that is not captured in traditional measures and may be useful in designing, implementing, and studying interventions to improve systems of care. Though initial results are promising, additional empirical work is needed to develop network-based measures and tools for policymakers.

Use of behavioral health care in Medicaid managed care carve-out versus carve-in arrangements.

OBJECTIVE: To evaluate differences in access to behavioral health services for Medicaid enrollees covered by a Medicaid entity that integrated the financing of behavioral and physical health care ("carve-in group") versus a Medicaid entity that separated this financing ("carve-out group"). DATA SOURCES/STUDY SETTING: Medicaid claims data from two Medicaid entities in the Portland, Oregon tri-county area in 2016. STUDY DESIGN: In this cross-sectional study, we compared differences across enrollees in the carve-in versus carve-out group, using a machine learning approach to incorporate a large set of covariates and minimize potential selection bias. Our primary outcomes included behavioral health visits for a variety of different provider types. Secondary outcomes included inpatient, emergency department, and primary care visits. DATA COLLECTION: We used Medicaid claims, including adults with at least 9 months of enrollment. PRINCIPAL FINDINGS: The study population included 45,786 adults with mental health conditions. Relative to the carve-out group, individuals in the carve-in group were more likely to access outpatient behavioral health (2.39 percentage points, p < 0.0001, with a baseline rate of approximately 73%). The carve-in group was also more likely to access primary care physicians, psychologists, and social workers and less likely to access psychiatrists and behavioral health specialists. Access to outpatient behavioral health visits was more likely in the carve-in arrangement among individuals with mild or moderate mental health conditions (compared to individuals with severe mental illness) and among black enrollees (compared to white enrollees). CONCLUSIONS: Financial integration of physical and behavioral health in Medicaid managed care was associated with greater access to behavioral health services, particularly for individuals with mild or moderate mental health conditions and for black enrollees. Recent changes to incentivize financial integration should be monitored to assess differential impacts by illness severity, race and ethnicity, provider types, and other factors.

Factors Associated With Off-Label Utilization of Second-Generation Antipsychotics Among Publicly Insured Adults.

OBJECTIVE: Off-label utilization of second-generation antipsychotic medications may expose patients to significant risks. The authors examined the prevalence, temporal trends, and factors associated with off-label utilization of second-generation antipsychotics among publicly insured adults. METHODS: A retrospective repeated panel was used to examine monthly off-label utilization of second-generation antipsychotics among fee-for-service Medicare, Medicaid, and dually eligible White, Black, and Latino adult beneficiaries filling prescriptions for second-generation antipsychotics in California, Georgia, Mississippi, and Oklahoma from July 2008 through June 2013. RESULTS: Among 301,367 users of second-generation antipsychotics, between 36.5% and 41.9% had utilization that was always off-label. Payer did not modify effects of race-ethnicity on off-label utilization. Compared with Whites, Blacks had lower monthly odds of off-label utilization in all four states, and Latinos had lower odds of utilization in California and Georgia. Payer was associated with off-label utilization in California, Mississippi, and Oklahoma. California Medicaid beneficiaries were 1.12 (95% confidence interval=1.10-1.13) times as likely as dually eligible beneficiaries to have off-label utilization. Off-label utilization increased relative to the baseline year in all states, but a downward trend followed in three states. CONCLUSIONS: Off-label utilization of second-generation antipsychotics was prevalent despite the drugs' cardiometabolic risks and little evidence of their effectiveness. The lower likelihood of off-label utilization among patients from racial-ethnic minority groups might stem from prescribers' efforts to minimize risks, given a higher baseline risk for these groups, or from disparities-associated factors. Variation among payers suggests that payer policies can affect off-label utilization.

Improving Physical Health Among People With Serious Mental Illness: The Role of the Specialty Mental Health Sector.

People with serious mental illness die 10-20 years earlier, compared with the overall population, and the excess mortality is driven by undertreated physical health conditions. In the United States, there is growing interest in models integrating physical health care delivery, management, or coordination into specialty mental health programs, sometimes called "reverse integration." In November 2019, the Johns Hopkins ALACRITY Center for Health and Longevity in Mental Illness convened a forum of 25 experts to discuss the current state of the evidence on integrated care models based in the specialty mental health system and to identify priorities for future research, policy, and practice. This article summarizes the group's conclusions. Key research priorities include identifying the active ingredients in multicomponent integrated care models and developing and validating integration performance metrics. Key policy and practice recommendations include developing new financing mechanisms and implementing strategies to build workforce and data capacity. Forum participants also highlighted an overarching need to address socioeconomic risks contributing to excess mortality among adults with serious mental illness.

Providing Health Physicals and/or Health Monitoring Services in Mental Health Clinics: Impact on Laboratory Screening and Monitoring for High Risk Populations.

Providing physical health care in specialty mental health clinics is a promising approach to improving the health status of adults with serious mental illness, but most programs examined in prior studies are not financially sustainable. This study assessed the impact on quality of care of a low-cost program implemented in New York State that allowed mental health clinics to be reimbursed by Medicaid for provision of health monitoring and health physicals (HM/HP). Medicaid claims data were analyzed with generalized linear multilevel models to examine change over time in quality of physical health care associated with HM/HP services. Recipients of HM/HP services were compared to control clinic patients [Per protocol (PP)] and with non-recipients of HM/HP services from both intervention and control clinics [As-Treated (AT)]. HM/HP clinic patients, regardless of receipt of HM/HP services, were compared with control clinic patients [Intent-to-Treat (ITT)]. Analyses were conducted with adjustment for patient demographic and clinical characteristics and prior year service use. The PP and AT analyses found significant improvement in measure of blood glucose screening for patients on antipsychotic medication and HbA1C testing for patients with diabetes (AOR range 1.26-1.33) and the AT analysis found significant improvement in cholesterol screening for patients on antipsychotic medication (AOR 1.24). However, ITT analysis found no significant changes in quality of care in HM/HP clinic caseloads relative to control clinics. The low-cost HM/HP program has the potential to benefit patients who receive supported services, but its impact is limited by remaining barriers to service implementation.

Mental Health Policy in the Era of COVID-19.

The response to the global COVID-19 pandemic has important ramifications for mental health systems and the patients they serve. This article describes significant changes in mental health policy prompted by the COVID-19 crisis across five major areas: legislation, regulation, financing, accountability, and workforce development. Special considerations for mental health policy are discussed, including social determinants of health, innovative technologies, and research and evaluation. These extraordinary advances provide an unprecedented opportunity to evaluate the effects of mental health policies that may be adopted in the post-COVID-19 era in the United States.