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Published Online: 1 September 2015

The Role of Clinical Setting and Management Approach in Metabolic Testing Among Youths and Adults Treated With Antipsychotics

Abstract

Objective:

This study compared metabolic screening among patients who received antipsychotic treatment at community mental health centers (CMHCs), with or without case management, and patients treated elsewhere.

Methods:

Rates of glucose and lipid testing among youths and adults in Missouri Medicaid (N=9,473) who received antipsychotic treatment at CMHCs, with and without case management, were evaluated. Multivariable logistic regressions determined which characteristics were independently associated with metabolic testing.

Results:

A total of 37.0% and 17.3% of youths and 68.7% and 34.9% of adults had glucose and lipid testing, respectively. Compared with treatment elsewhere, treatment at CMHCs, with or without case management, respectively, was associated with higher odds of glucose testing (youths, adjusted odds ratio [AOR]=1.68 and 1.89; adults, AOR=1.43 and 1.44) and lipid testing (youths, AOR=2.40 and 2.35; adults, AOR=1.97 and 1.48).

Conclusions:

CMHCs had higher rates of metabolic testing, possibly reflecting Missouri’s efforts to promote testing in these settings.
Cardiovascular disease is a leading cause of mortality among persons with severe mental illnesses (1,2). Persons receiving second-generation antipsychotics (referred to as antipsychotics in this report) are at risk of weight gain, leading to elevated cardiometabolic risk (3). In 2004, the U.S. Food and Drug Administration (FDA) issued a warning about hyperglycemia and metabolic dysregulation in connection with antipsychotic treatment. In the preceding year, the American Diabetes Association and several other prominent medical associations convened a consensus development conference on the subject of antipsychotic drugs and diabetes, leading to the joint development in 2004 of recommendations for increased metabolic monitoring during antipsychotic treatment (4). However, after the warning, rates of metabolic testing did not significantly increase (5) and were lowest among youths under the age of 18 (6).
In the state of Missouri, following the FDA warning and consensus guideline development, the Department of Mental Health (DMH) and MO HealthNet (Medicaid) made efforts to improve the quality of medical care for individuals with mental illness. These efforts included a multisite educational intervention to improve glucose monitoring rates (7), continuing medical education events targeting physicians (8) and community mental health center (CMHC) administrators (9) about implementation of best-practices procedures for screening and monitoring, a pilot initiative to enroll patients with psychiatric and comorbid general medical diagnoses in an enhanced care coordination program (10), and providing CMHCs with hand-held devices for finger-stick testing of lipids, glucose, and glycated hemoglobin (Hgb A1c). Finally, Missouri Medicaid instituted a registry to track metabolic screening and monitoring rates within CMHCs statewide (11).
Although several studies have evaluated metabolic testing in Medicaid populations, there has been little to no study of whether care setting has any impact on testing practices. In Missouri, federally qualified health care homes offer colocated behavioral health and primary care, which may occur within a CMHC setting. In such settings, care coordination and advocacy for adopting new best practices are enhanced (12). Given the state’s focus on improving metabolic testing among persons with mental illness, we hypothesized that receiving care at a CMHC would enhance the odds of metabolic testing.

Methods

This naturalistic retrospective cohort study evaluated individuals enrolled in the fee-for-service Medicaid program in the state of Missouri from August 2008 to April 2011. Administrative health care claims data were obtained for individuals receiving an oral antipsychotic during this time frame (N=110,406). All medical and pharmacy claims during the study period were identified by using a single unique identifier for each participant. The Colorado Multiple Institution Review Board and Washington University Institutional Review Board approved this study.
A new-user cohort (N=20,980) of patients with an index prescription from August 2009 thru April 2010 was identified. New use was defined as having not received oral antipsychotic medication in the year before the index prescription. Antipsychotics included were aripiprazole, asenapine, clozapine, iloperidone, lurasidone, olanzapine, paliperidone, quetiapine, risperidone, and ziprasidone. Patients who were not Medicaid eligible for 12 months before and after their index prescription (N=5,281) or were Medicare dual eligible (N=6,226) were excluded, leaving a total sample of 9,473 patients. Patients were divided into two cohorts for analysis on the basis of their age at the time of the index prescription: youths (ages 0–18 years, N=4,271, 45%) and adults (ages 19 and older, N=5,202, 55%).
Metabolic testing was defined as any glucose or lipid test, including nonfasting tests, in the 11 months following the month of the index prescription (31 days to 365 days from baseline). Testing was indicated by a code from the Current Procedural Terminology, fourth revision, or the International Classification of Diseases, ninth revision, clinical modification.
The primary independent variable of interest, having received any care at a CMHC during the study period, was defined by claims data indicating location of provider. To evaluate whether type of care (case management or not) or setting of care (CMHC or not) affected testing rates, we created a three-level “care environment” variable. Demographic variables included age, sex, and race. Medical comorbidity, health care utilization, and medication use were ascertained from the medical and pharmacy claims data for the 12 months preceding the index prescription. Days supplied for all prescriptions for oral antipsychotics were calculated for each patient. [Additional information about the coding for type of care and other variables of interest is available as an online supplement to this report.]
Descriptive statistics were computed for each cohort overall as well as for patients with a glucose test and patients with a lipid test. Multivariable logistic regression was used to determine characteristics that were independently associated with metabolic testing. Variables with sparse distributions or those that were highly correlated with key variables were not entered into the model. Testing rates were adjusted for care environment, sex, age, race, risk conditions for cardiovascular disease (diabetes, dyslipidemia, and hypertension or heart disease for adults and only hypertension and heart disease for youths, given that diabetes or dyslipidemia affected <2% of youths), psychiatric diagnoses, concurrent psychotropic drug use, length of antipsychotic treatment (<120 days, 120–239 days, and ≥240 days), and health care utilization, as described elsewhere by our group (12). [A list of the unique mental health categories defined by the Clinical Classifications Software can be found in the online supplement.]
Analyses were run with and without the individuals who did not have a claim with a primary psychiatric diagnosis during the study period (youths, N=151, 4%; adults, N=299, 6%).

Results

Table 1 summarizes the characteristics of the study cohorts (youths and adults) and reports glucose and lipid testing by age group, care environment, and other variables. CMHC users made up 1,539 (36.0%) of the youth sample and 1,894 (36.4%) of the adult sample. Testing rates were lower among youths than among adults. Youths and adults who received care within a CMHC setting were more likely than those who did not receive care at a CMHC to receive glucose and lipid testing. Case management did not appear to have an impact on testing rates, with the exception of lipid testing for adults—the percentage of adults who received lipid testing in a CMHC setting was eight percentage points higher among those who received case management. These results did not notably change when individuals without a primary psychiatric diagnosis were removed from the analysis.
TABLE 1. Adjusted odds of glucose and lipid testing among youths and adults after receipt of a prescription for a second-generation antipsychotica
 Testing rateRegression analysis
 TotalGlucose testLipid testGlucose testLipid test
CharacteristicN%N%bN%bAOR95% CIAOR95% CI
Youths4,271100.01,58237.074117.3    
 Care environment          
  CMHC plus case management57813.527046.716528.51.681.37–2.042.401.91–3.02
  CMHC only96122.547249.126027.11.891.61–2.222.351.94–2.85
  Neither (reference)2,73264.084030.731611.6  
 Female1,66539.071342.830618.41.331.15–1.521.13.94–1.34
 Age at receipt of index prescription          
  <6 (reference)49711.615330.86312.7  
  6–121,75841.256031.931517.91.04.83–1.311.35.99–1.84
  13–182,01647.286943.136318.01.801.42–2.281.581.15–2.19
 Race          
  White3,26376.41,26038.655717.11.191.01–1.40.78.64–.95
  Other or unknown (reference)1,00823.632231.918418.3  
 Mental health diagnoses          
  0 (reference)44210.312327.84710.6  
  11,15427.037732.715213.2.99.76–1.27.94.66–1.36
  21,14626.843437.919416.91.00.77–1.291.04.73–1.51
  ≥31,52935.864842.434822.8.88.67–1.151.21.84–1.76
 Diabetes831.95465.12833.7nana
 Dyslipidemia31.72064.51341.9nana
 Hypertension66115.525839.012719.21.08.90–1.301.07.85–1.34
 Heart disease3698.618249.37420.11.341.06–1.701.14.85–1.53
 Antipsychotic days supplied          
  <120 (reference)1,64838.645027.31267.6  
  120–23994322.136638.816917.91.781.49–2.132.602.02–3.35
  ≥2401,68039.376645.644626.52.552.18–3.004.283.44–5.37
 Emergency department claims          
  0 (reference)2,02047.368333.835617.6  
  1–31,21628.545437.321317.51.11.95–1.301.01.83–1.23
  ≥41,03524.244543.017216.61.18.99–1.40.88.70–1.09
 Outpatient claims          
  0 (reference)99423.330530.716016.1  
  1–31,64138.457535.028417.31.16.97–1.391.06.85–1.34
  ≥41,63638.370242.929718.21.521.27–1.831.12.88–1.41
 Inpatient claim1,23028.858547.628323.01.631.39–1.921.291.05–1.57
 Antidepressant claim1,28330.055243.026720.81.01.86–1.171.11.91–1.34
 Mood stabilizer claim62914.731750.414222.61.501.24–1.801.15.92–1.44
 Benzodiazepine claim1683.97846.42011.9nana
 Other psychotropic claim651.53249.21218.5nana
Adults5,202100.03,57268.7181734.9    
 Care environment          
  CMHC plus case management78115.059275.837748.31.431.18–1.741.971.64–2.36
  CMHC only1,11321.483274.844439.91.441.22–1.701.481.27–1.74
  Neither (reference)3,30863.62,14864.999630.1  
 Female3,75872.22,56868.31,26233.61.09.93–1.26.98.84–1.13
 Age at receipt of index prescription          
  19–29 (reference)1,77234.11,04659.033719.0  
  30–391,37826.588764.445633.11.06.91–1.251.591.33–1.90
  40–491,16422.491178.355547.71.691.40–2.052.091.73–2.53
  ≥5088817.172882.046952.81.851.46–2.342.111.70–2.61
 Race          
  White4,10378.92,82768.91,39334.01.09.93–1.29.85.73–1.00
  Other or unknown (reference)1,09921.174567.842438.6  
 Mental health diagnoses          
  0 (reference)4869.328157.812024.7  
  11,22023.580065.642334.71.05.83–1.331.21.93–1.58
  21,57030.21,05867.456135.7.99.78–1.251.23.95–1.61
  ≥31,92637.01,43374.471337.01.17.91–1.501.27.97–1.66
 Diabetes1,00119.284083.955155.01.511.23–1.851.421.20–1.68
 Dyslipidemia1,28524.71,06482.878661.21.411.17–1.712.582.20–3.02
 Hypertension2,19242.11,73679.21,06048.41.301.12–1.521.441.24–1.67
 Heart disease1,86735.91,47479.079542.61.251.07–1.471.06.91–1.24
 Antipsychotic days supplied          
  <120 (reference)2,63950.71,59860.667925.7  
  120–2391,08120.877271.439736.71.561.33–1.841.561.32–1.84
  ≥2401,48228.51,20281.174150.02.522.15–2.972.442.11–2.83
 Emergency department claims          
  0 (reference)1,43427.692764.653937.6  
  1–41,48328.593963.346531.4.97.83–1.15.85.71–1.01
  5–91,07620.775570.238035.31.261.04–1.521.01.83–1.22
  ≥101,20923.295178.743335.81.681.36–2.07.96.78–1.18
 Outpatient claims          
  0 (reference)83116.046656.122727.3  
  1–41,75433.71,12664.253530.51.301.09–1.561.09.89–1.33
  5–91,31225.294572.050038.11.661.35–2.041.351.09–1.68
  ≥101,30525.1103579.355542.51.891.51–2.381.311.04–1.65
 Inpatient claims          
  0 (reference)3,14760.52,05965.41,10035.0  
  11,23323.786370.041133.31.11.95–1.30.92.78–1.09
  ≥282215.865079.130637.21.261.02–1.57.80.65–.98
 Antidepressant claim3,62769.72,59571.51,36437.61.01.87–1.18.98.83–1.14
 Mood stabilizer claim1,18722.887373.546739.31.171.00–1.371.12.96–1.31
 Benzodiazepine claim2,49848.01,79271.791736.7.81.70-.94.80.69–.92
 Other psychotropic claim54610.540574.222541.2.96.77–1.201.03.84–1.27
a
Testing occurred between 31 and 365 days after receipt of the index prescription. Abbreviations: na, not available because the variable distribution was too sparse to be included in multivariable model; AOR, adjusted odds ratio; CMHC, community mental health center
b
Percentage of participants with a given characteristic
Because the composition of the patient populations in CMHC versus non-CMHC settings may differ, we adjusted for differences in patient demographic characteristics, clinical conditions, and overall health care utilization. After this adjustment, the odds of receiving testing were higher among youths who received case management in CMHC settings (glucose, adjusted odds ratio [AOR]=1.68; lipids, AOR=2.40) and among youths who received care at a CMHC but did not receive case management (glucose, AOR=1.89; lipids, AOR=2.35), compared with youths who received no care at a CMHC. The adjusted odds of receiving testing were higher among adults who received case management in CMHC settings (glucose, AOR=1.43; lipids, AOR=1.97) and for adults who received care in a CMHC setting but did not receive case management (glucose, AOR=1.44; lipids, AOR=1.48), compared with adults who received no care at a CMHC.
Among both youths and adults, the odds of testing increased with increasing age, although the increase was not always statistically significant. The odds of testing also increased with increasing length of antipsychotic treatment.

Discussion and Conclusions

We found that receiving care in a CMHC setting was associated with increased odds of metabolic testing among both youths and adults. There is good news overall, too, in that rates of testing were higher than those reported for an earlier time period (5,13). Nonetheless, it is important to note that significant undertesting remains, particularly among youths, even though a decade has passed since the first drug warnings and consensus recommendations were published. These results should be interpreted with caution. Specifically, adjustment for care setting and type of care received cannot fully eliminate the bias that individuals who receive care in a CMHC setting may be more likely to participate in follow-up care, including testing. To fully address the question of whether care setting and type of care affect testing rates, further randomized controlled study is necessary.
The increased odds of metabolic testing observed within the CMHC setting suggest an increased awareness of the need to test, which may be associated with the fact that Missouri DMH and Medicaid programs place greater emphasis on screening compared with other organizations. In 2012 (after the study period), the state implemented a “Health Homes” initiative for Medicaid-eligible residents with chronic diseases, including mental illness. Care managers use data analytic tracking to find and address care gaps, such as gaps in metabolic testing. Preliminary data suggest that testing rates have improved; in addition, clinical indicators and laboratory values suggest that there have also been improvements in the chronic conditions (14). Outcomes related to these specific initiatives are the subject of further investigation.
These results are subject to limitations. We defined follow-up testing as testing performed within the 11 months following the month of antipsychotic treatment initiation. This could have included testing done for reasons other than for screening related to antipsychotic treatment screening. Increased testing rates for glucose, in particular, could have been affected by the recommendation to use Hgb A1c as a diabetes-screening tool during the period of study. Fasting or random plasma blood glucose values are considered diabetes screening tests; because finger-stick glucose values could have been included in this sample, the results here do not represent true diabetes screening. Medicaid claims data can miss testing that is part of contracted bundled services, as well as finger-stick testing done by handheld devices in the office setting; in addition, results may be missed because of human error. Finally, the cohorts studied were limited to individuals with 12 months of Medicaid eligibility before and after their index antipsychotic prescription, and individuals with dual Medicaid and Medicare eligibility were excluded from the analysis, which could limit the generalizability of results.

Acknowledgments

The authors thank Michael Yingling, M.S., and Vincent Huang, B.A., for administrative assistance in development of the manuscript.

Supplementary Material

File (appi.ps.201400428.ds001.pdf)

References

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Colton CW, Manderscheid RW: Congruencies in increased mortality rates, years of potential life lost, and causes of death among public mental health clients in eight states. Preventing Chronic Disease 3:A42, 2006
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Druss BG, Zhao L, Von Esenwein S, et al: Understanding excess mortality in persons with mental illness: 17-year follow up of a nationally representative US survey. Medical Care 49:599–604, 2011
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Newcomer JW, Haupt D, Flavin KS, et al: Atypical antipsychotic treatment effects on metabolic outcome. Schizophrenia Bulletin 31:566, 2005
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American Diabetes Association, American Psychiatric Association, American Association of Clinical Endocrinologists, et al: Consensus development conference on antipsychotic drugs and obesity and diabetes. Diabetes Care 27:596–601, 2004
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Morrato EH, Druss B, Hartung DM, et al: Metabolic testing rates in 3 state Medicaid programs after FDA warnings and ADA/APA recommendations for second-generation antipsychotic drugs. Archives of General Psychiatry 67:17–24, 2010
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Haupt DW, Rosenblatt LC, Kim E, et al: Prevalence and predictors of lipid and glucose monitoring in commercially insured patients treated with second-generation antipsychotic agents. American Journal of Psychiatry 166:345–353, 2009
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Nicol GE, Morrato EH, Johnson MC, et al: Implementation of a glucose screening program based on diffusion of innovation theory methods. Psychiatric Services 62:12–14, 2011
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Parks J, Nicol G, Newcomer J: Improving Metabolic Screening for Patients on Antipsychotic Therapy (Medscape CME Activity), 2011. Available at www.medscape.org/viewarticle/751957
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Parks J, Nicol G, Newcomer J: Clinic Management and Leadership to Improve Treatment With Antipsychotics (Medscape CME Activity), 2011. Available at www.medscape.org/viewarticle/751859
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Morrato EH, Druss BG, Hartung DM, et al: Small area variation and geographic and patient-specific determinants of metabolic testing in antipsychotic users. Pharmacoepidemiology and Drug Safety 20:66–75, 2011
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Morrato EH, Nicol GE, Maahs D, et al: Metabolic screening in children receiving antipsychotic drug treatment. Archives of Pediatrics and Adolescent Medicine 164:344–351, 2010
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Morrato EH, Campagna E, Brewer S, et al: After a decade of risk communication on diabetes risks associated with antipsychotic drugs: where do we stand on prescriber attitudes and behaviors? Pharmacoepidemiology and Drug Safety 24(S1):1142, Aug 2015

Information & Authors

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Cover: Landscape, by Louis Comfort Tiffany, ca. 1892. Stained glass. Private Collection. Photo credit: Art Resource, New York City.

Psychiatric Services
Pages: 128 - 132
PubMed: 26325456

History

Received: 22 September 2014
Revision received: 17 March 2015
Accepted: 30 March 2015
Published online: 1 September 2015
Published in print: January 01, 2016

Authors

Details

Ginger E. Nicol, M.D.
Dr. Nicol is with the Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri (e-mail: [email protected]). Ms. Campagna and Dr. Morrato are with the Adult and Child Center for Health Outcomes Research and Delivery Science, University of Colorado Anschutz Medical Campus, Denver. Dr. Garfield is with Mercy Virtual Care Center, St. Louis. Dr. Newcomer is with the Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton. Dr. Parks is with MO HealthNet, Missouri Department of Social Services, Jefferson City, and with the Missouri Institute of Mental Health, University of Missouri–St. Louis.
Elizabeth J. Campagna, M.S., P.Stat.
Dr. Nicol is with the Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri (e-mail: [email protected]). Ms. Campagna and Dr. Morrato are with the Adult and Child Center for Health Outcomes Research and Delivery Science, University of Colorado Anschutz Medical Campus, Denver. Dr. Garfield is with Mercy Virtual Care Center, St. Louis. Dr. Newcomer is with the Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton. Dr. Parks is with MO HealthNet, Missouri Department of Social Services, Jefferson City, and with the Missouri Institute of Mental Health, University of Missouri–St. Louis.
Lauren D. Garfield, M.P.H., Ph.D.
Dr. Nicol is with the Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri (e-mail: [email protected]). Ms. Campagna and Dr. Morrato are with the Adult and Child Center for Health Outcomes Research and Delivery Science, University of Colorado Anschutz Medical Campus, Denver. Dr. Garfield is with Mercy Virtual Care Center, St. Louis. Dr. Newcomer is with the Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton. Dr. Parks is with MO HealthNet, Missouri Department of Social Services, Jefferson City, and with the Missouri Institute of Mental Health, University of Missouri–St. Louis.
John W. Newcomer, M.D.
Dr. Nicol is with the Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri (e-mail: [email protected]). Ms. Campagna and Dr. Morrato are with the Adult and Child Center for Health Outcomes Research and Delivery Science, University of Colorado Anschutz Medical Campus, Denver. Dr. Garfield is with Mercy Virtual Care Center, St. Louis. Dr. Newcomer is with the Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton. Dr. Parks is with MO HealthNet, Missouri Department of Social Services, Jefferson City, and with the Missouri Institute of Mental Health, University of Missouri–St. Louis.
Joseph J. Parks, M.D.
Dr. Nicol is with the Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri (e-mail: [email protected]). Ms. Campagna and Dr. Morrato are with the Adult and Child Center for Health Outcomes Research and Delivery Science, University of Colorado Anschutz Medical Campus, Denver. Dr. Garfield is with Mercy Virtual Care Center, St. Louis. Dr. Newcomer is with the Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton. Dr. Parks is with MO HealthNet, Missouri Department of Social Services, Jefferson City, and with the Missouri Institute of Mental Health, University of Missouri–St. Louis.
Elaine H. Morrato, Dr.P.H.
Dr. Nicol is with the Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri (e-mail: [email protected]). Ms. Campagna and Dr. Morrato are with the Adult and Child Center for Health Outcomes Research and Delivery Science, University of Colorado Anschutz Medical Campus, Denver. Dr. Garfield is with Mercy Virtual Care Center, St. Louis. Dr. Newcomer is with the Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton. Dr. Parks is with MO HealthNet, Missouri Department of Social Services, Jefferson City, and with the Missouri Institute of Mental Health, University of Missouri–St. Louis.

Competing Interests

Dr. Nicol has received research funding from, served as a consultant to, or served on an advisory board for Lundbeck, MedScape, NARSAD, Otsuka America Pharmaceuticals, Inc., Pfizer, Inc., and the Sidney R. Baer, Jr., Foundation. Ms. Campagna has received research grant support from Janssen Pharmaceuticals. Dr. Newcomer has received research funding from or served as a consultant to Otsuka America Pharmaceuticals, Inc., Found2Recovery, and Reviva Pharmaceuticals and has been a member of a data safety monitoring committee for Amgen. Dr. Parks has been a consultant for Otsuka America Pharmaceuticals, Inc. Dr. Morrato has received consulting fees, travel support, or research grant support from Amgen, the Consumer Healthcare Products Association, Janssen Pharmaceuticals, and Merck & Co., Inc. The other authors report no financial relationships with commercial interests.

Funding Information

National Heart and Lung Institute10.13039/501100000850: T32 HL 007456
National Institutes of Health10.13039/100000002: K23 MH 092435, R21 MH 097045
US National Institute of Health: R21 MH 097045
This work was supported by the Missouri Institute for Mental Health, affiliated with the University of Missouri–St. Louis; MO HealthNet (Medicaid); the Missouri Department of Mental Health; and National Institutes of Health grants R21 MH 097045 and K23 MH 092435.

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