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Articles   |    
Second-Generation Antipsychotic Use Among Stimulant-Using Children, by Organization of Medicaid Mental Health
Brendan Saloner, Ph.D.; Meredith Matone, M.H.S.; Amanda R. Kreider, B.S., B.A.; M. Samer Budeir, J.D.; Dorothy Miller, J.D., M.P.H.; Yuan-Shung Huang, M.S.; Ramesh Raghavan, M.D., Ph.D.; Benjamin French, Ph.D.; David Rubin, M.D., M.S.C.E.
Psychiatric Services 2014; doi: 10.1176/appi.ps.201300574
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Dr. Saloner is with the Department of Health Care Policy, Johns Hopkins University, Baltimore (e-mail: bsaloner@gmail.com). Ms. Matone, Ms. Kreider, Mr. Budeir, Ms. Miller, and Dr. Rubin are with PolicyLab, Children’s Hospital of Philadelphia, Philadelphia. Dr. Rubin is also with the Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia. Ms. Huang is with Division of General Pediatrics and Healthcare Analytics Unit, Children’s Hospital of Philadelphia. Dr. Raghavan is with the George Warren Brown School of Social Work, Washington University in St. Louis, St. Louis, Missouri. Dr. French is with the Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia.

Copyright © 2014 by the American Psychiatric Association


Objective  Reducing overuse of second-generation antipsychotics among Medicaid-enrolled children is a national priority, yet little is known about how service organization affects use. This study compared differences in second-generation antipsychotic utilization among Medicaid-enrolled children across fee-for-service, integrated managed care, and managed behavioral health carve-out organizational structures.

Methods  Organizational structures of Medicaid programs in 82 diverse counties in 34 states were categorized and linked to child-level cross-sectional claims data from the Medicaid Analytic Extract covering fiscal years 2004, 2006, and 2008. To approximate the population at risk of antipsychotic treatment, the sample was restricted to stimulant-using children ages three to 18 (N=419,226). The sample was stratified by Medicaid eligibility group, and logistic regression models were estimated for probability of second-generation antipsychotic use. Models included indicators of county-level organizational structure as main predictors, with sequential adjustment for personal and county-level covariates.

Results  With adjustment for person-level covariates, second-generation antipsychotic use was 31% higher among youths in foster care in fee-for-service counties than for youths in counties with carve-outs (odds ratio [OR]=1.69, 95% confidence interval [CI]=1.26–2.27). Foster care youths in integrated counties had the second highest adjusted odds (OR=1.31, CI=1.08–1.58). Similar patterns of use also were found for youths eligible for Supplemental Security Income but not for those eligible for Temporary Assistance for Needy Families. Differences persisted after adjustment for county-level characteristics.

Conclusions  Carve-outs, versus other arrangements, were associated with lower second-generation antipsychotic use. Future research should explore carve-out features (for example, tighter management of inpatient or restricted access, as well as care coordination) contributing to lower second-generation antipsychotic use.

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Figure 1 County-level behavioral health organizational structures

a Integrated managed care: a county Medicaid program administers a single per-member-per-month (PMPM) payment to a managed care organization (MCO). The MCO contracts with individual providers.

b The Medicaid program administers separate PMPM payments to an MCO and a managed behavioral health organization (MBHO). By definition, plans and providers in counties with integrated and carve-out structures receive payment on a capitated basis.

c The county directly contracts with providers or uses an administrative services organization (ASO) to manage providers, who are then paid on a fee-for-service basis.

Figure 2 Predicted probability of second-generation antipsychotic use among stimulant-using youths, by Medicaid eligibility group and county organizational structurea

a Vertical lines indicate confidence intervals. SSI, Supplemental Security Income; TANF, Temporary Assistance for Needy Families

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Table 1Characteristics of study counties, by organizational structure for delivery of Medicaid behavioral health carea
Table Footer Note

a Capitated or integrated pharmacy was determined via review of policy documents. Other measures were based on analysis of data from the Area Resource File for years 2002–2008. Data represent the average within each category across years and reflect the closest calendar year for measures such as physician supply that are not reported annually.

Table Footer Note

b p<.05, carve-out versus fee for service, by pairwise t test

Table Footer Note

c p<.05, carve-out versus integrated, by pairwise t test

Table Footer Note

d p<.001, carve-out versus integrated, by pairwise t test

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Table 2Characteristics of stimulant-using children, by organizational structure for delivery of Medicaid behavioral health carea
Table Footer Note

a Authors’ analysis of Medicaid Analytic Extract data, for fiscal years 2004, 2006, and 2008. Values are expressed as percentages. The study sample comprised youths ages three to 18 with any stimulant prescription and ten months of Medicaid enrollment in one of the study counties.

Table Footer Note

b p<.001, carve-out versus fee for service, by pairwise t test

Table Footer Note

c p<.05, carve-out versus fee for service, by pairwise t test

Table Footer Note

d p<.05, carve-out versus integrated, by pairwise t test

Table Footer Note

e p<.001, carve-out versus integrated, by pairwise t test

Anchor for Jump
Table 3Likelihood of second-generation antipsychotic use among stimulant-using youths, by eligibility group and county organizational structure for delivery of Medicaid behavioral health carea
Table Footer Note

a Child-level regression models adjusted for age, race-ethnicity, sex, year, and pharmacy structure; county-level models further adjusted for provider supply, urbanicity, poverty rate, uninsured rate, unemployment, and proportion of county that voted Democrat in the 2008 election. The study sample comprised youths ages three to 18 with any stimulant prescription and ten months of Medicaid enrollment in one of the study counties. The reference group for all eligibility categories was carve-out.



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