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.

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.

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.

The Predicted Long-Term Benefits of Ensuring Timely Treatment and Medication Adherence in Early Schizophrenia.

The impact of initiatives aimed at reducing time in untreated psychosis during early-stage schizophrenia will be unknown for many years. Thus, we simulate the effect of earlier treatment entry and better antipsychotic drug adherence on schizophrenia-related hospitalizations, receipt of disability benefits, competitive employment, and independent/family living over a ten-year horizon. We predict that earlier treatment entry reduces hospitalizations by 12.6-14.4% and benefit receipt by 7.0-8.5%, while increasing independent/family living by 41.5-46% and employment by 42-58%. We predict larger gains if a pro-adherence intervention is also used. Our findings suggest substantial benefits of timely and consistent early schizophrenia care.

Predictors of Receipt of Physical Health Services in Mental Health Clinics.

To inform efforts to improve physical health care for adults with serious mental illness, this study examines predictors of provision and receipt of physical health services in freestanding mental health clinics in New York state. The number of services provided over the initial 12-months of implementation varied across clinics from 0 to 1407. Receipt of services was associated with a diagnosis of schizophrenia, frequent mental and physical health visits in the prior year, and prescription of antipsychotic medications. Additional support may also be needed to enable clinics to target patients without established patterns of frequent mental health or medical visits.

Impact of a Mental Health Based Primary Care Program on Quality of Physical Health Care.

We examine the impact of mental health based primary care on physical health treatment among community mental health center patients in New York State using propensity score adjusted difference in difference models. Outcomes are quality indicators related to outpatient medical visits, diabetes HbA1c monitoring, and metabolic monitoring of antipsychotic treatment. Results suggest the program improved metabolic monitoring for patients on antipsychotics in one of two waves, but did not impact other quality indicators. Ceiling effects may have limited program impacts. More structured clinical programs to may be required to achieve improvements in quality of physical health care for this population.

Regional Variation in Physician Adoption of Antipsychotics: Impact on US Medicare Expenditures.

BACKGROUND: Regional variation in US Medicare prescription drug spending is driven by higher prescribing of costly brand-name drugs in some regions. This variation likely arises from differences in the speed of diffusion of newly-approved medications. Second-generation antipsychotics were widely adopted for treatment of severe mental illness and for several off-label uses. Rapid diffusion of new psychiatric drugs likely increases drug spending but its relationship to non-drug spending is unclear. The impact of antipsychotic diffusion on drug and medical spending is of great interest to public payers like Medicare, which finance a majority of mental health spending in the US. AIMS: We examine the association between physician adoption of new antipsychotics and antipsychotic spending and non-drug medical spending among disabled and elderly Medicare enrollees. METHODS: We linked physician-level data on antipsychotic prescribing from an all-payer dataset (IMS Health's XponentTM) to patient-level data from Medicare. Our physician sample included 16,932 US. psychiatrists and primary care providers with > 10 antipsychotic prescriptions per year from 1997-2011. We constructed a measure of physician adoption of 3 antipsychotics introduced during this period (quetiapine, ziprasidone and aripiprazole) by estimating a shared frailty model of the time to first prescription for each drug. We then assigned physicians to one of 306 U.S. hospital referral regions (HRRs) and measured the average propensity to adopt per region. Using 2010 data for a random sample of 1.6 million Medicare beneficiaries, we identified 138,680 antipsychotic users. A generalized linear model with gamma distribution and log link was used to estimate the effect of region-level adoption propensity on beneficiary-level antipsychotic spending and non-drug medical spending adjusting for patient demographic and socioeconomic characteristics, health status, eligibility category, and whether the antipsychotic was for an on- vs. off-label use. RESULTS: In our sample, mean patient age was 62 years, 42% were male, and 86% had low-income. Half of antipsychotic users in Medicare had an on-label indication. The weighted average propensity to adopt the three new antipsychotics varied four-fold across HRRs. For every one standard deviation increase in the propensity to adopt there was a 5% increase in antipsychotic spending after adjusting for covariates (adjusted ratio of spending 1.05, 95% CI 1.01-1.08, p = 0.005). Physician propensity to adopt new antipsychotics was not associated with non-drug medical spending (adjusted ratio 0.96, 95% CI 0.91-1.01, p < 0.117). DISCUSSION: These findings suggest wide regional variation in physicians' propensity to adopt new antipsychotic medications. While physician adoption of new antipsychotics was positively associated with antipsychotic expenditures, it was not associated with non-drug spending. Our analysis is limited to Medicare and may not generalize to other payers. Also, claims data do not allow for the measurement of health outcomes, which would be important to evaluate when calculating the value of rapid vs. slow technology adoption.

Antipsychotic prescribing: do conflict of interest policies make a difference?

BACKGROUND: Academic medical centers (AMCs) have increasingly adopted conflict of interest policies governing physician-industry relationships; it is unclear how policies impact prescribing. OBJECTIVES: To determine whether 9 American Association of Medical Colleges (AAMC)-recommended policies influence psychiatrists' antipsychotic prescribing and compare prescribing between academic and nonacademic psychiatrists. RESEARCH DESIGN: We measured number of prescriptions for 10 heavily promoted and 9 newly introduced/reformulated antipsychotics between 2008 and 2011 among 2464 academic psychiatrists at 101 AMCs and 11,201 nonacademic psychiatrists. We measured AMC compliance with 9 AAMC recommendations. Difference-in-difference analyses compared changes in antipsychotic prescribing between 2008 and 2011 among psychiatrists in AMCs compliant with ≥ 7/9 recommendations, those whose institutions had lesser compliance, and nonacademic psychiatrists. RESULTS: Ten centers were AAMC compliant in 2008, 30 attained compliance by 2011, and 61 were never compliant. Share of prescriptions for heavily promoted antipsychotics was stable and comparable between academic and nonacademic psychiatrists (63.0%-65.8% in 2008 and 62.7%-64.4% in 2011). Psychiatrists in AAMC-compliant centers were slightly less likely to prescribe these antipsychotics compared with those in never-compliant centers (relative odds ratio, 0.95; 95% CI, 0.94-0.97; P < 0.0001). Share of prescriptions for new/reformulated antipsychotics grew from 5.3% in 2008 to 11.1% in 2011. Psychiatrists in AAMC-compliant centers actually increased prescribing of new/reformulated antipsychotics relative to those in never-compliant centers (relative odds ratio, 1.39; 95% CI, 1.35-1.44; P < 0.0001), a relative increase of 1.1% in probability. CONCLUSIONS: Psychiatrists exposed to strict conflict of interest policies prescribed heavily promoted antipsychotics at rates similar to academic psychiatrists and nonacademic psychiatrists exposed to less strict or no policies.

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.

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.

Revisiting diabetes risk of olanzapine versus aripiprazole in serious mental illness care.

BACKGROUND: Exposure to second-generation antipsychotics (SGAs) carries a risk of type 2 diabetes, but questions remain about the diabetogenic effects of SGAs. AIMS: To assess the diabetes risk associated with two frequently used SGAs. METHOD: This was a retrospective cohort study of adults with schizophrenia, bipolar I disorder or severe major depressive disorder (MDD) exposed during 2008-2013 to continuous monotherapy with aripiprazole or olanzapine for up to 24 months, with no pre-period exposure to other antipsychotics. Newly diagnosed type 2 diabetes was quantified with targeted minimum loss-based estimation; risk was summarised as the restricted mean survival time (RMST), the average number of diabetes-free months. Sensitivity analyses were used to evaluate potential confounding by indication. RESULTS: Aripiprazole-treated patients had fewer diabetes-free months compared with olanzapine-treated patients. RMSTs were longer in olanzapine-treated patients, by 0.25 months [95% CI: 0.14, 0.36], 0.16 months [0.02, 0.31] and 0.22 months [0.01, 0.44] among patients with schizophrenia, bipolar I disorder and severe MDD, respectively. Although some sensitivity analyses suggest a risk of unobserved confounding, E-values indicate that this risk is not severe. CONCLUSIONS: Using robust methods and accounting for exposure duration effects, we found a slightly higher risk of type 2 diabetes associated with aripiprazole compared with olanzapine monotherapy regardless of diagnosis. If this result was subject to unmeasured selection despite our methods, it would suggest clinician success in identifying olanzapine candidates with low diabetes risk. Confirmatory research is needed, but this insight suggests a potentially larger role for olanzapine in the treatment of well-selected patients, particularly for those with schizophrenia, given the drug's effectiveness advantage among them.

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.

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.