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.

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.

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.

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.

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.

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.

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.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06798-2.

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.

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.

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.

Simulated long-term outcomes of early use of long-acting injectable antipsychotics in early schizophrenia

AIM

Duration of untreated psychosis in early schizophrenia impacts long-term outcomes. Because long-acting injectable (LAI) antipsychotic drugs improve adherence in early-stage patients, they could reduce additional time in uncontrolled psychosis (TUP) during the critical period of the illness. However, the long-term benefit of early LAI use over oral formulations has not been quantified. This study explores the potential magnitude of the benefit with a simulation approach.

METHODS

A microsimulation models the effects of 11 treatment pathways reflecting alternative decisions on whether and when LAI agents are used during a "calibration phase" that starts at treatment entry and lasts until the end of the 3-year critical period. Treatment failure prolongs time in psychosis. Long-term outcomes are predicted over the ensuing 7-year period as a function of TUP.

RESULTS

An "early LAI" pathway where LAI treatment follows the second oral treatment failure is compared to an oral-only pathway. Under these pathways, 69% and 46% of patients, respectively, are estimated to exit the calibration phase with adequate symptom control (total positive and negative syndrome scale score below 68). Relative to the oral-only pathway, the early LAI pathway is predicted to increase competitive employment by 39% (25% vs 18%) and independent or family living by 22% (71% vs 58%), and to decrease receipt of disability benefits by 36% (42% vs 66%) and hospital admissions per 1000 patient-years by 15% (249% vs 294%).

CONCLUSIONS

While these simulation results need to be confirmed empirically, they suggest that earlier use of LAI antipsychotics can meaningfully improve patient outcomes.

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.

Bayesian Meta-analysis of Multiple Continuous Treatments with Individual Participant-Level Data: An Application to Antipsychotic Drugs

Modeling dose-response relationships of drugs is essential to understanding their safety effects on patients under realistic circumstances. While intention-to-treat analyses of clinical trials provide the effect of assignment to a particular drug and dose, they do not capture observed exposure after factoring in nonadherence and dropout. We develop a Bayesian method to flexibly model the dose-response relationships of binary outcomes with continuous treatment, permitting multiple evidence sources, treatment effect heterogeneity, and nonlinear dose-response curves. In an application, we examine the risk of excessive weight gain for patients with schizophrenia treated with the second-generation antipsychotics paliperidone, risperidone, or olanzapine in 14 clinical trials. We define exposure as total cumulative dose (daily dose × duration) and convert to units equivalent to 100 mg of olanzapine (OLZ doses). Averaging over the sample population of 5891 subjects, the median dose ranged from 0 (placebo randomized participants) to 6.4 OLZ doses (paliperidone randomized participants). We found paliperidone to be least likely to cause excessive weight gain across a range of doses. Compared with 0 OLZ doses, at 5.0 OLZ doses, olanzapine subjects had a 15.6% (95% credible interval: 6.7, 27.1) excess risk of weight gain; corresponding estimates for paliperidone and risperidone were 3.2% (1.5, 5.2) and 14.9% (0.0, 38.7), respectively. Moreover, compared with nonblack participants, black participants had a 6.8% (1.0, 12.4) greater risk of excessive weight gain at 10.0 OLZ doses of paliperidone. Nevertheless, our findings suggest that paliperidone is safer in terms of weight gain risk than risperidone or olanzapine for all participants at low to moderate cumulative OLZ doses.

Racial And Ethnic Differences In The Attainment Of Behavioral Health Quality Measures In Medicare Advantage Plans

As the Medicare population becomes more diverse and its demand for behavioral health care grows, a better understanding of racial/ethnic disparities in the quality of behavioral health care is crucial. Medicare Advantage (MA) plans are accountable through the public reporting of quality performance on measures, including the Healthcare Effectiveness Data and Information Set (HEDIS). We examined HEDIS data on eight MA behavioral health care quality measures, using mixed-effects logistic regressions to distinguish racial/ethnic differences within and between MA health plans. We found that performance differed across racial/ethnic groups by more than 10 percentage points on most quality measures. Significant within-plan disparities were found in twenty of twenty-four comparisons of racial/ethnic minority groups with whites. Within-plan disparities varied widely across plans, with performance being equivalent across racial/ethnic groups in some plans and widely divergent in others. Unlike other types of medical care, in behavioral health within-plan quality disparities are prominent in MA plans, which suggests a role for stratified reporting by racial/ethnic group.

The American Psychiatric Association Practice Guideline for the Pharmacological Treatment of Patients With Alcohol Use Disorder

(Reprinted with permission from Am J Psychiatry 2018; 175:86-90).

Potential Benefits to Patients and Payers From Increased Measurement of Antipsychotic Plasma Levels in the Management of Schizophrenia

Approximately 40% of patients with schizophrenia either do not respond to the prescribed antipsychotic drug or cannot tolerate it because of side effects, resulting in poor disease control and negative health and economic outcomes. Identifying the root cause of such complicated courses of treatment is a critical step in the treatment of these patients. Although measurement of antipsychotic plasma levels can be used to discern potential root causes, this tool is not routinely used in the United States. The authors of this column discuss the potential effects on patient outcomes and on the value of care from greater use of this diagnostic tool, especially under emerging payment models and delivery system reform efforts.

Impact of a mental health based primary care program on emergency department visits and inpatient stays

OBJECTIVE

Integrating primary care services into specialty mental health clinics has been proposed as a method for improving health care utilization for medical conditions by adults with serious mental illness. This paper examines the impact of a mental health based primary care program on emergency department (ED) visits and hospitalizations.

METHOD

The program was implemented in seven New York City outpatient mental health clinics in two waves. Medicaid claims were used to identify patients treated in intervention clinics and a control group of patients treated in otherwise similar clinics in New York City. Impacts of the program were estimated using propensity score adjusted difference-in-differences models on a longitudinally followed cohort.

RESULTS

Hospital stays for medical conditions increased significantly in intervention clinics relative to control clinics in both waves (ORs = 1.21 (Wave 1) and 1.33 (Wave 2)). ED visits for behavioral health conditions decreased significantly relative to controls in Wave 1 (OR = 0.89), but not in Wave 2. No other significant differences in utilization trends between the intervention and control clinics were found.

CONCLUSION

Introducing primary care services into mental health clinics may increase utilization of inpatient services, perhaps due to newly identified unmet medical need in this population.

Simulated Effects of Policies to Reduce Diabetes Risk Among Adults With Schizophrenia Receiving Antipsychotics

OBJECTIVE

Second-generation antipsychotics increase the risk of diabetes and other metabolic conditions among individuals with schizophrenia. Although metabolic testing is recommended to reduce this risk, low testing rates have prompted concerns about negative health consequences and downstream medical costs. This study simulated the effect of increasing metabolic testing rates on ten-year prevalence rates of prediabetes and diabetes (diabetes conditions) and their associated health care costs.

METHODS

A microsimulation model (N=21,491 beneficiaries) with a ten-year time horizon was used to quantify the impacts of policies that increased annual testing rates in a Medicaid population with schizophrenia. Data sources included California Medicaid data, National Health and Nutrition Examination Survey data, and the literature. In the model, metabolic testing increased diagnosis of diabetes conditions and diagnosis prompted prescribers to switch patients to lower-risk antipsychotics. Key inputs included observed diagnoses, prescribing rates, annual testing rates, imputed rates of undiagnosed diabetes conditions, and literature-based estimates of policy effectiveness.

RESULTS

Compared with 2009 annual testing rates, ten-year outcomes for policies that achieved universal testing reduced exposure to higher-risk antipsychotics by 14%, time to diabetes diagnosis by 57%, and diabetes prevalence by .6%. These policies were associated with higher spending because of testing and earlier treatment.

CONCLUSIONS

The model showed that policies promoting metabolic testing provided an effective approach to improve the safety of second-generation antipsychotic prescribing in a Medicaid population with schizophrenia; however, the policies led to additional costs at ten years. Simulation studies are a useful source of information on the potential impacts of these policies.

Prescribing of Clozapine and Antipsychotic Polypharmacy for Schizophrenia in a Large Medicaid Program

OBJECTIVE

Underuse of clozapine and overuse of antipsychotic polypharmacy are both indicators of poor quality of care. This study examined variation in prescribing clozapine and antipsychotic polypharmacy across providers, as well as factors associated with these practices.

METHODS

Using 2010-2012 Pennsylvania Medicaid data, prescribers were identified if they wrote antipsychotic prescriptions for ten or more nonelderly adult patients with schizophrenia annually. Generalized linear mixed models with a binomial distribution and a logit link were used to examine prescriber-level annual percentages of patients with clozapine use and with long-term (≥90 days) antipsychotic polypharmacy and associated characteristics of prescribers' patient caseloads, prescriber characteristics, and Medicaid payer (fee-for-service versus managed care plans).

RESULTS

The study cohort included 645 prescribers in 2010, 632 in 2011, and 650 in 2012. In 2012, the mean prescriber-level annual percentage of patients with any clozapine use was 7% (range 0%-89%), and the mean percentage of patients with any long-term antipsychotic polypharmacy was 7% (range 0%-45%) (similar rates were found during 2010-2012). Prescribers with high prescription volume, a smaller percentage of patients from racial or ethnic minority groups, and a larger percentage of patients eligible for Supplemental Security Income were more likely to use both clozapine and antipsychotic polypharmacy for treating schizophrenia. Prescriber specialty and Medicaid payer were also associated with prescribers' practices.

CONCLUSIONS

Considerable variation was found in clozapine and antipsychotic polypharmacy practices across prescribers in their treatment of schizophrenia. Targeting efforts to selected prescribers holds promise as an approach to promote evidence-based antipsychotic prescribing.

The American Psychiatric Association Practice Guideline on the Use of Antipsychotics to Treat Agitation or Psychosis in Patients With Dementia

(Reprinted with permission from American Journal of Psychiatry 2016; 173:543-546).

Enrollment of Specialty Mental Health Clinics in a State Medicaid Program to Promote General Medical Services

OBJECTIVE

To promote integrated general medical care for individuals with serious mental illness, the New York State Office of Mental Health (OMH) established regulations allowing specialty mental health clinics to provide Medicaid-reimbursable health monitoring (HM) and health physicals (HP). This study examined clinics' enrollment in this program to understand its potential to reach individuals with serious mental illness.

METHODS

Information on enrollment and characteristics of clinics (N=500) was obtained from OMH administrative databases. Clinic enrollment in the HM/HP program was examined for the program's first five years (2010-2015). Logistic regression models accounting for the clustering of multiple clinics within agencies were used to examine characteristics associated with enrollment.

RESULTS

A total of 291 of 500 (58%) licensed clinics in New York State in 2015 enrolled in the HM/HP program, potentially reaching 62% of all Medicaid enrollees with serious mental illness seen in specialty mental health clinics in the state. State-operated clinics were required to participate, and had 91% enrollment. Over half of hospital-affiliated and freestanding mental health clinics elected to enroll (53% and 54%, respectively). In adjusted models, enrollment was higher among freestanding clinics compared with hospital-affiliated clinics, higher in larger than smaller clinics, and higher in county-operated than in private nonprofit clinics.

CONCLUSIONS

The high level of enrollment in the HM/HP program indicates strong interest among mental health clinics in providing general medical care services. However, supplemental policies may be needed to extend the program to areas of the mental health system where barriers to general medical care services are highest.

Patterns of Antipsychotic Prescribing by Physicians to Young Children

OBJECTIVE

Antipsychotic use among young children has grown rapidly despite a lack of approval by the U.S. Food and Drug Administration (FDA) for broad use in this age group. Characteristics of physicians who prescribed antipsychotics to young children were identified, and prescribing patterns involving young children and adults were compared.

METHODS

Physician-level prescribing data from IMS Health's Xponent database were linked with American Medical Association Masterfile data and analyzed. The sample included all U.S. psychiatrists and a random sample of 5% of family medicine physicians who wrote at least ten antipsychotic prescriptions per year from 2008 to 2011 (N=31,713). Logistic and hierarchical binomial regression models were estimated to examine physician prescribing for children ages zero to nine, and the types and numbers of ingredients used for children versus adults ages 20 to 64 were compared.

RESULTS

Among antipsychotic prescribers, 42.2% had written at least one antipsychotic prescription for young children. Such prescribing was more likely among physicians age ≤39 versus ≥60 (odds ratio [OR]=1.70) and physicians in rural versus nonrural areas (OR=1.11) and was less likely among males (OR=.93) and graduates of a top-25 versus a lower-ranked U.S. medical school (OR=.87). Among physicians who prescribed antipsychotics to young children and adults, 75.0% of prescriptions for children and 35.7% of those for adults were for drugs with an FDA-approved indication for that age. Fewer antipsychotic agents were prescribed for young children (median=2) versus adults (median=7).

CONCLUSIONS

Prescribing antipsychotics for young children was relatively common, but prescribing patterns differed between young children and adults.

General Medical Outcomes From the Primary and Behavioral Health Care Integration Grant Program

OBJECTIVE

Primary and Behavioral Health Care Integration (PBHCI) grants aim to improve the health of people with serious mental illness by integrating primary and preventive general medical services into behavioral health settings. This report describes the general medical outcomes of persons served by early cohorts of programs, funded in 2009 or 2010, that participated in this national demonstration project.

METHODS

A quasi-experimental, difference-in-differences design was used to compare changes in general medical health among consumers served at three PBHCI clinics (N=322) and three clinics that were selected as matched control sites (N=469). Propensity-score weighting was used to adjust for baseline differences between PBHCI and control clinic populations. Baseline data were collected between 2010 and 2012; follow-up data were collected approximately one year later. General medical outcomes included blood pressure; body mass index; cholesterol, triglyceride, and blood glucose or HbA1c levels; and self-reported tobacco smoking.

RESULTS

Compared with consumers served at control clinics, PBHCI consumers had better outcomes for cholesterol: mean reductions in total cholesterol were greater by 36 mg/dL (p<.01), mean reductions in low-density lipoprotein cholesterol were greater by 35 mg/dL (p<.001), and mean increases in high-density lipoprotein cholesterol were greater by 3 mg/dL (p<.05). No significant PBHCI effects were observed for the other health indicators.

CONCLUSIONS

Approximately one year of PBHCI treatment resulted in statistically and potentially clinically significant improvements in cholesterol but not in other general medical outcomes examined. More rigorous implementation of integrated care in community behavioral health settings may be needed to further improve the health of adults with serious mental illness.

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.

Improving antipsychotic adherence among patients with schizophrenia: savings for states

This column presents findings of an analysis conducted to quantify the potential net savings to state budgets from interventions to improve adherence to antipsychotic drugs among patients with schizophrenia. Using a financial model based on published data, the authors estimated costs of direct medical care and criminal justice system involvement at state and national levels and validated it against findings from other cost studies. The model estimated an annual cost of $21.4 billion (in 2013 dollars) to Medicaid programs and other state agencies for people with schizophrenia. On the basis of data on the effect on outcomes of increased medication adherence, better adherence could yield annual net savings of $3.28 billion to states or $1,580 per patient per year. Innovations to improve adherence to antipsychotic drugs among schizophrenia patients can yield substantial savings in state budgets. States should consider interventions shown to increase medication adherence in this patient group.

Where You Live Matters: Quality and Racial/Ethnic Disparities in Schizophrenia Care in Four State Medicaid Programs

OBJECTIVE

To determine whether (a) quality in schizophrenia care varies by race/ethnicity and over time and (b) these patterns differ across counties within states.

DATA SOURCES

Medicaid claims data from California, Florida, New York, and North Carolina during 2002-2008.

STUDY DESIGN

We studied black, Latino, and white Medicaid beneficiaries with schizophrenia. Hierarchical regression models, by state, quantified person and county effects of race/ethnicity and year on a composite quality measure, adjusting for person-level characteristics.

PRINCIPAL FINDINGS

Overall, our cohort included 164,014 person-years (41-61 percent non-whites), corresponding to 98,400 beneficiaries. Relative to whites, quality was lower for blacks in every state and also lower for Latinos except in North Carolina. Temporal improvements were observed in California and North Carolina only. Within each state, counties differed in quality and disparities. Between-county variation in the black disparity was larger than between-county variation in the Latino disparity in California, and smaller in North Carolina; Latino disparities did not vary by county in Florida. In every state, counties differed in annual changes in quality; by 2008, no county had narrowed the initial disparities.

CONCLUSIONS

For Medicaid beneficiaries living in the same state, quality and disparities in schizophrenia care are influenced by county of residence for reasons beyond patients' characteristics.

Evaluation of the SAMHSA Primary and Behavioral Health Care Integration (PBHCI) Grant Program: Final Report

Excess morbidity and mortality in persons with serious mental illness is a public health crisis. Numerous factors contribute to this health disparity, including illness and treatment-related factors, socioeconomic and lifestyle-related factors, and limited access to and poor quality of general medical care. Primary and Behavioral Health Care Integration (PBHCI), one of the Substance Abuse and Mental Health Services Administration's service grant programs, is intended to improve the overall wellness and physical health status of people with serious mental illness, including individuals with co-occurring substance use disorders, by making available an array of coordinated primary care services in community mental health and other community-based behavioral health settings where the population already receives care. This article describes the results of a RAND Corporation evaluation of the PBHCI grants program. The evaluation was designed to understand PBHCI implementation strategies and processes, whether the program leads to improvements in outcomes, and which program models and/or model features lead to better program processes and consumer outcomes. Results of the evaluation showed that PBHCI grantee programs were diverse, varying in their structures, procedures, and the extent to which primary and behavioral health care was integrated at the program level. Overall, PBHCI programs also served many consumers with high rates of physical health care needs, although total program enrollment was lower than expected. The results of a small, comparative effectiveness study showed that consumers served at PBHCI clinics (compared to those served at matched control clinics) showed improvements on some (e.g., markers of dyslipidemia, hypertension, diabetes) but not all of the physical health indicators studied (e.g., smoking, weight). Finally, we found that program features, such as clinic hours, regular staff meetings, and the degree of service integration, increased consumer access to integrated care, but that access to integrated care was not directly associated with improvements in physical health. Implications of the study results for programs and the broader field, plus options for future PBHCI-related research are discussed.

Disparities in quality of care among publicly insured adults with schizophrenia in four large U.S. states, 2002-2008

OBJECTIVE

To examine racial/ethnic disparities in quality of schizophrenia care and assess the size of observed disparities across states and over time.

DATA SOURCES

Medicaid claims data from CA, FL, NY, and NC.

STUDY DESIGN

Observational repeated cross-sectional panel cohort study of white, black, and Latino fee-for-service adult beneficiaries with schizophrenia. Main outcome was the relationship of race/ethnicity and year with a composite measure of quality of schizophrenia care derived from 14 evidence-based quality indicators.

PRINCIPAL FINDINGS

Quality was assessed for 325,373 twelve-month person-episodes between 2002 and 2008, corresponding to 123,496 Medicaid beneficiaries. In 2002, quality was lowest for blacks in all states. With the exception of FL, quality was lower for Latinos than whites. In CA, blacks had about 43 percent of the individual indicators met compared to 58 percent for whites. Quality improved annually for all groups in CA, NY, and NC. While in CA the improvement was slightly larger for Latinos, in FL quality improved for blacks but declined for Latinos and whites.

CONCLUSIONS

Quality of schizophrenia care is poor and racial/ethnic disparities exist among Medicaid beneficiaries from four states. The size of the disparities varied across the states, and most of the initial disparities were unchanged by 2008.

Mental Health Retrosight: Understanding the Returns From Research (Lessons From Schizophrenia): Policy Report

This study examines the impacts arising from neuroscience and mental health research going back 20-25 years, and identifies attributes of the research, researchers or research setting that are associated with translation into patient benefit, in the particular case of schizophrenia. The study combined two methods: forward-tracing case studies to examine where scientific advances of 20 years ago have led to impact today; and backward-tracing perspectives to identify the research antecedents of today's interventions in schizophrenia. These research and impact trails are followed principally in Canada, the UK and the USA. The headline findings are as follows: The case studies and perspectives support the view that mental health research has led to a diverse and beneficial range of academic, health, social and economic impacts over the 20 years since the research was undertaken.Clinical research has had a larger impact on patient care than basic research has over the 20 years since the research was undertaken.Those involved in mental health research who work across boundaries are associated with wider health and social benefits.Committed individuals, motivated by patient need, who effectively champion research agendas and/or translation into practice are key in driving the development and implementation of interventions.This study provides an overview of the methods and presents the full set of findings, with the policy provocations they raise, and an emerging research agenda. It has been written for funders of biomedical and health research and health services, health researchers, and policymakers in those fields. It will also be of interest to those involved in research and impact evaluation.

Changes in physician antipsychotic prescribing preferences, 2002-2007

OBJECTIVE

Physician antipsychotic prescribing behavior may be influenced by comparative effectiveness evidence, regulatory warnings, and formulary and other restrictions on these drugs. This study measured changes in the degree to which physicians are able to customize treatment choices and changes in physician preferences for specific agents after these events.

METHODS

The study used 2002-2007 prescribing data from the IMS Health Xponent database and data on physician characteristics from the American Medical Association for a longitudinal cohort of 7,399 physicians. Descriptive and multivariable regression analyses were conducted of the concentration of prescribing (physician-level Herfindahl index) and preferences for and likelihood of prescribing two first-generation antipsychotics and six second-generation antipsychotics. Analyses adjusted for prescribing volume, specialty, demographic characteristics, practice setting, and education.

RESULTS

Antipsychotic prescribing was highly concentrated at the physician level, with a mean unadjusted Herfindahl index of .33 in 2002 and .29 in 2007. Psychiatrists reduced the concentration of their prescribing more over time than did other physicians. High-volume psychiatrists had a Herfindahl index that was half that of low-volume physicians in other specialties (.18 versus .36), a difference that remained significant (p<.001) after adjustment for physician characteristics. The share of physicians preferring olanzapine dropped from 29.9% in 2002 to 10.3% in 2007 (p<.001) while the share favoring quetiapine increased from 9.4% to 44.5% (p<.001). Few physicians (<5%) preferred a first-generation antipsychotic in 2002 or 2007.

CONCLUSIONS

Preferences for specific antipsychotics changed dramatically during this period. Although physician prescribing remained heavily concentrated, the concentration decreased over time, particularly among psychiatrists.

How quickly do physicians adopt new drugs? The case of second-generation antipsychotics

OBJECTIVE

The authors examined physician adoption of second-generation antipsychotic medications and identified physician-level factors associated with early adoption.

METHODS

The authors estimated Cox proportional-hazards models of time to adoption of nine second-generation antipsychotics by 30,369 physicians who prescribed antipsychotics between 1996 and 2008, when the drugs were first introduced, and analyzed the total number of agents prescribed during that time. The models were adjusted for physicians' specialty, demographic characteristics, education and training, practice setting, and prescribing volume. Data were from IMS Xponent, which captures over 70% of all prescriptions filled in the United States, and the American Medical Association Physician Masterfile.

RESULTS

On average, physicians waited two or more years before prescribing new second-generation antipsychotics, but there was substantial heterogeneity across products in time to adoption. General practitioners were much slower than psychiatrists to adopt second-generation antipsychotics (hazard ratios (HRs) range .10-.35), and solo practitioners were slower than group practitioners to adopt most products (HR range .77-.89). Physicians with the highest antipsychotic-prescribing volume adopted second-generation antipsychotics much faster than physicians with the lowest volume (HR range .15-.39). Psychiatrists tended to prescribe a broader set of antipsychotics (median=6) than general practitioners and neurologists (median=2) and pediatricians (median=1).

CONCLUSIONS

As policy makers search for ways to control rapid health spending growth, understanding the factors that influence physician adoption of new medications will be crucial in the efforts to maximize the value of care received by individuals with mental disorders as well as to improve medication safety.

The effect of race-ethnicity on the comparative effectiveness of clozapine among Medicaid beneficiaries

OBJECTIVE

Effectiveness trials have confirmed the superiority of clozapine in schizophrenia treatment, but little is known about whether the drug's superiority holds across racial-ethnic groups. This study examined the effectiveness by race-ethnicity of clozapine relative to other antipsychotics among adult patients in maintenance antipsychotic treatment.

METHODS

Black, Latino, and white Florida Medicaid beneficiaries with schizophrenia receiving maintenance treatment with clozapine or other antipsychotics between July 1, 2000, and June 30, 2005, were identified. Cox proportional hazard regression models were used to estimate associations between clozapine and race-ethnicity and their interaction; time to discontinuation for any cause was the primary measure of effectiveness.

RESULTS

The 20,122 members of the study cohort accounted for 20,122 antipsychotic treatment episodes; 3.7% were treated with clozapine and 96.3% with other antipsychotics. Blacks accounted for 23% of episodes and Latinos for 36%. Unadjusted analyses suggested that Latinos continued on clozapine longer than whites and that Latinos and blacks discontinued other antipsychotics sooner than whites. Adjusted analyses of 749 propensity score-matched sets of clozapine users and other antipsychotic users indicated that risk of discontinuation was lower for clozapine users (risk ratio [RR]=.45, 95% confidence interval [CI]=.39-.52), an effect that was not moderated by race-ethnicity. Times to discontinuation were longer for clozapine users. Overall risk of antipsychotic discontinuation was higher for blacks (RR=1.56, CI=1.27-1.91) and Latinos (RR=1.23, CI=1.02-1.48).

CONCLUSIONS

The study confirmed clozapine's superior effectiveness and did not find evidence that race-ethnicity modified this effect. The findings highlight the need for efforts to increase clozapine use, particularly among minority groups.

The effect of race-ethnicity and geography on adoption of innovations in the treatment of schizophrenia

OBJECTIVE

This study evaluated the effect of race-ethnicity and geography on the adoption of a pharmacological innovation (long-acting injectable risperidone [LAIR]) among Medicaid beneficiaries with schizophrenia as well as the contribution of geographic location to observed racial-ethnic disparities.

METHODS

The data source was a claims data set from the Florida Medicaid program for the 2.5-year period that followed the launch of LAIR in the U.S. market. Study participants were beneficiaries with schizophrenia who had filled at least one antipsychotic prescription during the study period. The outcome variable was any use of LAIR; model variables were need indicators and random effects for 11 Medicaid areas, which are multicounty units used by the Medicaid program to administer benefits. Adjusted probability of use of LAIR for blacks and Latinos versus whites was estimated with logistic regression models.

RESULTS

The study cohort included 13,992 Medicaid beneficiaries: 25% of the cohort was black, 37% Latino, and 38% white. Unadjusted probability of LAIR use was lower for Latinos than whites, and use varied across the state's geographic areas. Adjustment for need confirmed the unadjusted finding of a disparity between Latinos and whites (odds ratio=.58, 95% confidence interval=.49-.70). The inclusion of geographic location in the model eliminated the Latino-white disparity but confirmed the unadjusted finding of geographic variation in adoption.

CONCLUSIONS

Within a state Medicaid program, the initial finding of a disparity between Latinos and whites in adopting LAIR was driven by geographic disparities in adoption rates and the geographic concentration of Latinos in a low-adoption area. Possible contributors and implications of these results are discussed.