Public Health Insurance and Prescription Medications for Mental Illness

Johanna Catherine Maclean; Benjamin Cook; Nicholas Carson; Michael F Pesko

doi:10.1515/bejeap-2018-0067

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Public Health Insurance and Prescription Medications for Mental Illness

Johanna Catherine Maclean , Benjamin Cook , Nicholas Carson und Michael F Pesko

Veröffentlicht/Copyright: 29. September 2018

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Aus der Zeitschrift The B.E. Journal of Economic Analysis & Policy Band 19 Heft 1

Abstract

Mental illnesses are prevalent in the United States and globally. Cost is a critical barrier to treatment receipt. We study the effects of the Affordable Care Act's recent expansion of Medicaid, a public insurance system for the poor in the U.S., on psychotropic prescription medications for mental illness. We estimate differences-in-differences models using administrative data on medications for which Medicaid was a third-party payer over the period 2011–2017. Our findings suggest that these expansions increased psychotropic prescriptions by 21.0%. We show that Medicaid, and not patients, financed these prescriptions. For states expanding Medicaid, the total cost of these prescriptions was $28.0 M by the second quarter of 2017. Expansion effects were experienced across most major mental illness categories and across states with different levels of patient need, system capacity, and expansion scope. We find no statistically significant evidence that Medicaid expansion reduced mental illness.

Keywords: mental illness; prescription medications; healthcare; insurance

JEL Classification: I1; I13; I18

Funding statement: This work was funded by American Cancer Society, Funder Id: 10.13039/100000048, Grant Number: Research Scholar Grant – Insurance, RSGI-16-019-

Appendix

Table 9:

Heterogeneity in Medicaid expansion effects on psychotropic medication prescriptions per 100,000 non-elderly by need for mental illness healthcare using differences-in-differences models: SDUD 2011–2017.

Outcome:	Prescriptions
Sample: High mental illness care need states
Mean value in expansion states, pre-expansion	10,505
Expansion	2,228***
	(616)
Relative effect size┼	21.2%
Observations	650
Sample: Low mental illness care need states
Mean value in expansion states, pre-expansion	9,101
Expansion	1,607***
	(467)
Relative effect size┼	17.7%
Observations	620

Notes: Unit of observation is the state-year-quarter. All outcomes are converted to a rate per 100,000 persons 18 to 64 years. All models are estimated with OLS and control for state demographics, state and period fixed effects, and state-specific linear time trends. Standard errors that account for within-state clustering are reported in parentheses. Need for mental illness treatment calculated using National Survey of Drug Use and Health 2009/2010 state-level data.
┼Relative effect size calculated as follows: (estimated beta/mean value in expansion states, pre-expansion)*100%.
***,**,* = statistically different from zero at the 1%,5%, 10% level.

Table 10:

Heterogeneity in Medicaid expansion effects on psychotropic medication prescriptions per 100,000 non-elderly by uninsurance rate using differences-in-differences models: SDUD 2011–2017.

Outcome:	Prescriptions
Sample: High uninsurance rate states
Mean value in expansion states, pre-expansion	8,869
Expansion	2,323***
	(446)
Relative effect size┼	26.2%
Observations	620
Sample: Low uninsurance rate states
Mean value in expansion states, pre-expansion	11,325
Expansion	1,749**
	(680)
Relative effect size┼	15.4%
Observations	650

Notes: Unit of observation is the state-year-quarter. All outcomes are converted to a rate per 100,000 persons 18 to 64 years. All models are estimated with OLS and control for state demographics, state and period fixed effects, and state-specific linear time trends. Standard errors that account for within-state clustering are reported in parentheses. Uninsurance rates calculated using the American Community Survey 2010 data.
┼Relative effect size calculated as follows: (estimated beta/mean value in expansion states, pre-expansion)*100%.
***,**,* = statistically different from zero at the 1%,5%,10% level.

Table 11:

Heterogeneity in Medicaid expansion effects on psychotropic medication prescriptions per 100,000 non-elderly by access to primary care using differences-in-differences models: SDUD 2011–2017.

Outcome:	Prescriptions
Sample: High primary care access states
Mean value in expansion states, pre-expansion	9,701
Expansion	2,473***
	(566)
Relative effect size┼	25.5%
Observations	676
Sample: Low primary care access states
Mean value in expansion states, pre-expansion	10,186
Expansion	1,634***
	(572)
Relative effect size┼	16.0%
Observations	594

Notes: Unit of observation is the state-year-quarter. All outcomes are converted to a rate per 100,000 persons 18 to 64 years. All models are estimated with OLS and control for state demographics, state and period fixed effects, and state-specific linear time trends. Standard errors that account for within-state clustering are reported in parentheses. Access to primary care calculated using CMS and Area Resource File 2010 data.
┼Relative effect size calculated as follows: (estimated beta/mean value in expansion states, pre-expansion)*100%.
***,**,* = statistically different from zero at the 1%,5%, 10% level.

Table 12:

Heterogeneity in Medicaid expansion effects on psychotropic medication prescriptions per 100,000 non-elderly by smoking status using differences-in-differences models: SDUD 2011–2017.

Outcome:	Prescriptions
Sample: High smoking rate states
Mean value in expansion states, pre-expansion	10,966
Expansion	2,319***
	(507)
Relative effect size┼	21.1%
Observations	676
Sample: Low smoking rate states
Mean value in expansion states, pre-expansion	8,850
Expansion	1,445***
	(500)
Relative effect size┼	16.3%
Observations	594

Notes: Unit of observation is the state-year-quarter. All outcomes are converted to a rate per 100,000 persons 18 to 64 years. All models are estimated with OLS and control for state demographics, state and period fixed effects, and state-specific linear time trends. Standard errors that account for within-state clustering are reported in parentheses. Smoking rates calculated using Behavioral Risk Factor Surveillance Survey 2010 data.
┼Relative effect size calculated as follows: (estimated beta/mean value in expansion states, pre-expansion)*100%.
***,**,* = statistically different from zero at the 1%,5%,10% level.

Table 13:

Effect of Medicaid expansion on psychotropic medication prescriptions per 100,000 non-elderly using differences-in-differences models using population weights: SDUD 2011–2017.

Outcome:	Prescriptions
Weighted mean value in expansion states, pre-expansion	9,381
Expansion	1,456***
	(407)
Relative effect size┼	15.5%
Observations	1,270

Notes: State populations ages 18 to 64 years serve as the weights. Unit of observation is the state-year-quarter. All outcomes are converted to a rate per 100,000 persons 18 to 64 years. All models are estimated with OLS and control for state demographics, state and period fixed effects, and state-specific linear time trends. Standard errors that account for within-state clustering are reported in parentheses.
┼Relative effect size calculated as follows: (estimated beta/mean value in expansion states, pre-expansion)*100%.
***,**,* = statistically different from zero at the 1%,5%,10% level.

Table 14:

Effect of Medicaid expansion on psychotropic medication prescriptions per 100,000 non-elderly using differences-in-differences models with different controls for between-state differences: SDUD 2011–2017.

Outcome:	Prescriptions
Mean value in expansion states, pre-expansion	9,922
Model (1)	3,184***
	(506)
Relative effect size┼	32.1%
Model (2)	1,774***
	(442)
Relative effect size┼	17.9%
Model (3)	1,651*
	(965)
Relative effect size┼	16.6%
Model (4)	1,845***
	(421)
Relative effect size┼	18.6%
Observations	1,270

Notes: The outcome variable in each regression is the number of prescription fills and refills. Unit of observation is the state-year-quarter. All outcomes are converted to a rate per 100,000 persons 18 to 64 years. All models estimated with OLS. Standard errors that account for within-state clustering are reported in parentheses. Model (1) controls for state demographics, and state and period fixed effects. Model (2) controls for state demographics, state and period fixed effects, and state-specific quadratic time trends. Model (3) controls for state demographics, quarter fixed effects, and state-by-year fixed effects. Model (4) controls for an extended set of state demographics (see text), state and period fixed effects, and state-specific linear time trends.
┼Relative effect size calculated as follows: (estimated beta/mean value in expansion states, pre-expansion)*100%.
***,**,* = statistically different from zero at the 1%,5%,10% level.

Table 15:

Effect of Medicaid expansion on psychotropic medication prescriptions per 100,000 non-elderly using differences-in-differences models using alternative Medicaid expansion coding schemes: SDUD 2011–2017.

Outcome:	Prescriptions
Alternative Medicaid coding scheme: Wherry & Miller exclusions
Mean value in expansion states, pre-expansion	9,922
Expansion	2,102***
	(410)
Relative effect size┼	21.2%
Observations	1,140
Alternative Medicaid coding scheme:Maclean and Saloner (2017)
Mean value in expansion states, pre-expansion	10,975
Expansion	1,681***
	(433)
Relative effect size┼	15.3%
Observations	1,270
Alternative Medicaid coding scheme: Exclude California
Mean value in expansion states, pre-expansion	10,095
Expansion	2,105***
	(421)
Relative effect size┼	20.9%
Observations	1,244

Notes: Unit of observation is the state-year-quarter. See text for a discussion of the alternative Medicaid expansion coding schemes. All outcomes are converted to a rate per 100,000 persons 18 to 64 years. All models are estimated with OLS and control for state demographics, state and period fixed effects, and state-specific linear time trends. Standard errors that account for within-state clustering are reported in parentheses.
┼Relative effect size calculated as follows: (estimated beta/mean value in expansion states, pre-expansion)*100%.
***,**;* = statistically different from zero at the 1%, 5%, 10% level.

Table 16:

Effect of Medicaid expansion on psychotropic medication prescriptions per 100,000 non-elderly using a triple difference-style estimator: 2011–2016.

Outcome:	Prescriptions
Mean value in expansion states, pre-expansion	9,964
Expansion * post	1,107*
	(594)
Expansion * post * percent	11**
	(5)
Mean percent, treatment group, post-expansion period:	74.27
Relative effect size┼	8.2%
Observations	1,052

Notes: Unit of observation is the state-year-quarter. All outcomes are converted to a rate per 100,000 persons 18 to 64 years. All models are estimated with OLS and control for state demographics, state and period fixed effects, and state-specific linear time trends. Standard errors that account for within-state clustering are reported in parentheses. Expansion = an indicator for expansion in state. Post = an indicator for the period after expansion. Percent = newly eligible enrollees as a percent of Medicaid enrollment increase between 2013 in state s and period t. States with substantial expansions before 2011 excluded from the analysis (see Table 2).
┼Relative effect size calculated as follows: (estimated beta/mean value in expansion states, pre-expansion)*100%.
***,**,* = statistically different from zero at the 1%,5%,10% level.

Table 17:

Effect of Medicaid expansion on psychotropic medication prescriptions per 100,000 non-elderly using differences-in-differences and allowing and heterogeneity by Medicaid program type: 2011–2017.

Outcome:	Prescriptions
Mean value in expansion states, pre-expansion	6,063
Expansion	−573
	(778)
Expansion * managed care program	4,233***
	(1,486)
Managed care program	−2,452*
	(1,249)
Relative effect size┼	29.4%
Observations	2,115

Notes: Unit of observation is a state-year-quarter-Medicaid program (managed care vs. fee-for-service). Only observations with both managed care and fee-for-service included in the analysis sample. All outcomes are converted to a rate per 100,000 persons 18 to 64 years. All models are estimated with OLS and control for state demographics, state and period fixed effects, and state-specific linear time trends. Standard errors that account for within-state clustering are reported in parentheses.
┼Relative effect size calculated as follows: ([estimated beta on the expansion * managed care program variable – estimated beta on the managed care program variable]/mean value in expansion states, pre-expansion)*100%.
***, **, and * = statistically different from zero at the 1%, 5%, and 10% level.

Table 18:

Effect of Medicaid expansion on psychotropic medication prescriptions per 100,000 non-elderly using differences-in-differences models using alternative imputation methods for suppressed data points: SDUD 2011–2017.

Outcome:	Prescriptions
Impute suppressed data points with a value of zero
Mean value in expansion states, pre-expansion	9,731
Expansion	2,059***
	(413)
Relative effect size┼	21.2%
Observations	1,270
Impute suppressed data points with a value of ten
Mean value in expansion states, pre-expansion	10,112
Expansion	2,108***
	(408)
Relative effect size┼	20.8%
Observations	1,270

Notes: Unit of observation is the state-year-quarter. All outcomes are converted to a rate per 100,000 persons 18 to 64 years. All models are estimated with OLS and control for state demographics, state and period fixed effects, and state-specific linear time trends. Standard errors that account for within-state clustering are reported in parentheses.
┼Relative effect size calculated as follows: (estimated beta/mean value in expansion states, pre-expansion)*100%.
***,**;* = statistically different from zero at the 1%, 5%, 10% level.

Table 19:

Effect of Medicaid expansion on suicides per 100,000 non-elderly using differences-in-differences models: NVSS 2011–2016.

Outcome:	Suicides
Mean value in expansion states, pre-expansion	4.753
Parallel trends test	−0.02
	(0.02)
Relative effect size┼	0.42%
Observations	552
Differences-in-differences	0.15
	(0.11)
Relative effect size┼	3.2%
Observations	1,224

Notes: Unit of observation is the state-year-quarter. All outcomes are converted to a rate per 100,000 persons 18 to 64 years. All models are estimated with OLS and control for state demographics, state and period fixed effects, and state-specific linear time trends. Standard errors that account for within-state clustering are reported in parentheses.
┼Relative effect size calculated as follows: (estimated beta/mean value in expansion states, pre-expansion)*100%.
***,**;* = statistically different from zero at the 1%, 5%, 10% level.

Table 20:

Effect of Medicaid expansion on days in poor mental health and self-assessed fair or poor health using differences-in-differences models: BRFSS 2011–2016.

Outcome:	Days in poor mental health	Fair or poor health
Mean value in expansion states, pre-expansion	5.441	0.226
Parallel trends test	−0.001	−0.000
	(0.016)	(0.001)
Relative effect size┼	−0.02%	−0.13%
Observations	552	552
Differences-in-differences	−0.113	−0.003
	(0.125)	(0.008)
Relative effect size┼	−2.1%	1.3%
Observations	1,224	1,224

Notes: Unit of observation is the state-year-quarter. All models are estimated with OLS and control for state demographics, state population ages 18 to 64 years, state and period fixed effects, and state-specific linear time trends. Standard errors that account for within-state clustering are reported in parentheses.
┼Relative effect size calculated as follows: (estimated beta/mean value in expansion states, pre-expansion)*100%.
***,**;* = statistically different from zero at the 1%, 5%, 10% level.

References

Abdelgawad, T., and L. Egbuonu-Davis. 2006. “Preferred Drug Lists and Medicaid Prescriptions.” Pharmacoeconomics 24 (3): 55–63.10.2165/00019053-200624003-00005Suche in Google Scholar

Adelmann, P. K. 2003. “Mental and Substance Use Disorders among Medicaid Recipients: Prevalence Estimates from Two National Surveys.” Administration and Policy in Mental Health and Mental Health Services Research 31 (2): 111–29.10.1023/B:APIH.0000003017.78877.56Suche in Google Scholar

American Psychiatric Association. 2006. American Psychiatric Association Practice Guidelines for the Treatment of Psychiatric Disorders: Compendium 2006: Washington DC: American Psychiatric Publications.Suche in Google Scholar

American Psychiatric Association. 2015. “What Is Mental Illness?”, Accessed September 2017. https://www.psychiatry.org/patients-families/what-is-mental-illness.Suche in Google Scholar

American Psychiatric Association. 2017. “American Psychiatric Association Practice Guidelines.” Accessed August 8. http://psychiatryonline.org/guidelines.Suche in Google Scholar

Angrist, J. D., and J. Pischke. 2009. Mostly Harmless Econometrics: An Empiricist's Companion. Princeton, NJ: Princeton University Press. Book. Original edition, Princeton University Press.10.1515/9781400829828Suche in Google Scholar

Autor, D. H. 2003. “Outsourcing at Will: The Contribution of Unjust Dismissal Doctrine to the Growth of Employment Outsourcing.” Journal of Labor Economics 21 (1): 1–42.10.1086/344122Suche in Google Scholar

Baicker, K., H. L. Allen, B. J. Wright, and A. N. Finkelstein. 2017. “The Effect of Medicaid on Medication Use among Poor Adults: Evidence from Oregon.” Health Affairs 36 (12): 2110–14.10.1377/hlthaff.2017.0925Suche in Google Scholar

Biener, A. I., S. H. Zuvekas, and S. C. Hill. 2017. “Impact of Recent Medicaid Expansions on Office‐Based Primary Care and Specialty Care among the Newly Eligible.” Health Services Research 53 (4). Part I (August 2018).10.1111/1475-6773.12793Suche in Google Scholar

Bishop, T. F., M. J. Press, S. Keyhani, and H. Pincus. 2014. “Acceptance of Insurance by Psychiatrists and the Implications for Access to Mental Health Care.” JAMA Psychiatry 71 (2): 176–81.10.1001/jamapsychiatry.2013.2862Suche in Google Scholar

Bradford, W. D., and W. D. Lastrapes. 2014. “A Prescription for Unemployment? Recessions and the Demand for Mental Health Drugs.” Health Economics 23 (11): 1301–25.10.1002/hec.2983Suche in Google Scholar

Center for Behavioral Health Statistics and Quality. 2016. 2015 National Survey on Drug Use and Health: Detailed Tables. Rockville, MD: Substance Abuse and Mental Health Services Administration.Suche in Google Scholar

Center for Behavioral Health Statistics and Quality. 2017. Results from the 2016 National Survey on Drug Use and Health: Detailed Tables. Rockville, MD: Substance Abuse and Mental Health Services Administration.Suche in Google Scholar

Center for Behavioral Health Statistics Quality. 2016. 2015 National Survey on Drug Use and Health: Methodological Summary and Definitions. Rockville, MD: Substance Abuse and Mental Health Services Administration.Suche in Google Scholar

Cohen, R., M. Martinez, and B. Ward. 2010. Health Insurance Coverage: Early Release of Estimates from the National Health Interview Survey, 2009. National Center for Health Statistics.10.1037/e565212009-001Suche in Google Scholar

Cook, B. L., N.-H. Trinh, Z. Li, S. S.-Y. Hou, and A. M. Progovac. 2016. “Trends in Racial-Ethnic Disparities in Access to Mental Health Care, 2004–2012.” Psychiatric Services 68 (1): 9–16.10.1176/appi.ps.201500453Suche in Google Scholar

Cotti, C. D., E. Nesson, and N. Tefft. 2017. Impacts of the Aca Medicaid Expansion on Health Behaviors: Evidence from Household Panel Data. In SSRN Working Paper Series Social Science Research Network. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2989323. It is just a working paper on SSRN.10.2139/ssrn.2989323Suche in Google Scholar

Courtemanche, C., J. Marton, B. Ukert, A. Yelowitz, and D. Zapata. 2017a. “Early Effects of the Affordable Care Act on Healthcare Access, Risky Health Behaviors, and Self-Assessed Health.” Southern Economic Journal 84 (3): 660–91. 2018. National Bureau of Economic Research Working Paper Series. Cambridge, MA: National Bureau of Economic Research.10.1002/soej.12245Suche in Google Scholar

Courtemanche, C., J. Marton, B. Ukert, A. Yelowitz, and D. Zapata. 2017b. “Early Impacts of the Affordable Care Act on Health Insurance Coverage in Medicaid Expansion and Non-Expansion States.” Journal of Policy Analysis and Management 36 (1): 178–210.10.1002/pam.21961Suche in Google Scholar

Cutler, D. M., and J. Gruber. 1996. “Does Public Insurance Crowd Out Private Insurance?” Quarterly Journal of Economics 111 (2): 391–430.10.2307/2946683Suche in Google Scholar

Czajka, J. L., and R. Rosso. 2015. Redesign of the Income Questions in the Current Population Survey Annual Social and Economic Supplement: Further Analysis of the 2014 Split-Sample Test. Mathematica Policy Research.Suche in Google Scholar

Decker, S. L. 2012. “In 2011 Nearly One-Third of Physicians Said They Would Not Accept New Medicaid Patients, but Rising Fees May Help.” Health Affairs 31 (8): 1673–79.10.1377/hlthaff.2012.0294Suche in Google Scholar

Flood, S., M. King, S. Ruggles, and J. R. Warren. 2017. Integrated Public Use Microdata Series, Current Population Survey. Minneapolis, MN: University of Minnesota.Suche in Google Scholar

Frank, R. G., and T. G. McGuire. 2000. “Economics and Mental Health.” In Handbook of Health Economics, edited by A.J. Culyer and J.P. Newhouse, 893–954. Amsterdam, Netherlands: Elsevier.10.1016/S1574-0064(00)80029-3Suche in Google Scholar

Frean, M., J. Gruber, and B. D. Sommers. 2017. “Premium Subsidies, the Mandate, and Medicaid Expansion: Coverage Effects of the Affordable Care Act.” Journal of Health Economics 53: 72–86.10.1016/j.jhealeco.2017.02.004Suche in Google Scholar

Fredriksen, M., A. Halmøy, S. V. Faraone, and J. Haavik. 2013. “Long-Term Efficacy and Safety of Treatment with Stimulants and Atomoxetine in Adult Adhd: A Review of Controlled and Naturalistic Studies.” European Neuropsychopharmacology 23 (6): 508–27.10.1016/j.euroneuro.2012.07.016Suche in Google Scholar

Garfield, R. L., J. R. Lave, and J. M. Donohue. 2010. “Health Reform and the Scope of Benefits for Mental Health and Substance Use Disorder Services.” Psychiatric Services 61 (11): 1081–86.10.1176/ps.2010.61.11.1081Suche in Google Scholar

Garfield, R. L., S. H. Zuvekas, J. R. Lave, and J. M. Donohue. 2011. “The Impact of National Health Care Reform on Adults with Severe Mental Disorders.” American Journal of Psychiatry 168 (5): 486–94.10.1176/appi.ajp.2010.10060792Suche in Google Scholar

Gaynes, B. N., D. Warden, M. H. Trivedi, S. R. Wisniewski, M. Fava, and A. J. Rush. 2009. “What Did Star* D Teach Us? Results from a Large-Scale, Practical, Clinical Trial for Patients with Depression.” Psychiatric Services 60 (11): 1439–45.10.1176/ps.2009.60.11.1439Suche in Google Scholar

Ghosh, A., K. Simon, and B. D. Sommers. 2017. “The Effect of State Medicaid Expansions on Prescription Drug Use: Evidence from the Affordable Care Act.” Journal of Public Economics 163: 99–112. July 2018. National Bureau of Economic Research Working Paper Series. Cambridge, MA: National Bureau of Economic Research.10.3386/w23044Suche in Google Scholar

Golberstein, E., and G. Gonzales. 2015. “The Effects of Medicaid Eligibility on Mental Health Services and out-Of-Pocket Spending for Mental Health Services.” Health Services Research 50 (6): 1734–50.10.1111/1475-6773.12399Suche in Google Scholar

Goodman, L. 2017. “The Effect of the Affordable Care Act Medicaid Expansion on Migration.” Journal of Policy Analysis and Management 36 (1): 211–38.10.1002/pam.21952Suche in Google Scholar

Grossman, M. 1972. “On the Concept of Health Capital and the Demand for Health.” Journal of Political Economy 80 (2): 223–55.10.1086/259880Suche in Google Scholar

Hamersma, S., and M. Kim. 2013. “Participation and Crowd Out: Assessing the Effects of Parental Medicaid Expansions.” Journal of Health Economics 32 (1): 160–71.10.1016/j.jhealeco.2012.09.003Suche in Google Scholar

Horn, B. P., J. C. Maclean, and M. R. Strain. 2017. “Do Minimum Wage Increases Influence Worker Health?” Economic Inquiry 55 (4): 1986–2007.10.1111/ecin.12453Suche in Google Scholar

Hu, L., R. Kaestner, B. Mazumder, S. Miller, and A. Wong. 2016. The Effect of the Patient Protection and Affordable Care Act Medicaid Expansions on Financial Well-Being. In “Journal of Public Economics 163: 99–112. July 2018. Nationa Bureau of Economic Research. Cambridge, MA: National Bureau of Economic Research.10.1016/j.jpubeco.2018.04.009Suche in Google Scholar

Hurley, R. E., and S. A. Somers. 2003. “Medicaid and Managed Care: A Lasting Relationship?” Health Affairs 22 (1): 77–88.10.1377/hlthaff.22.1.77Suche in Google Scholar

Insel, T. R. 2008. “Assessing the Economic Costs of Serious Mental Illness.” American Journal of Psychiatry 165 (6): 663–65.10.1176/appi.ajp.2008.08030366Suche in Google Scholar

Insel, T. R. 2015. Mental Health Awareness Month: By the Numbers. National Institute of Mental Health.Suche in Google Scholar

Kaestner, R., B. Garrett, J. Chen, A. Gangopadhyaya, and C. Fleming. 2017. “Effects of Aca Medicaid Expansions on Health Insurance Coverage and Labor Supply.” Journal of Policy Analysis and Management 36 (3): 608–42.10.1002/pam.21993Suche in Google Scholar

Kaiser Commission on Medicaid and the Uninsured. 2016a. Implementing Coverage and Payment Initiatives: Results from a 50-State Medicaid Budget Survey for State Fiscal Years 2016 and 2017. Kaiser Commisson on Medicaid and the Uninsured. Washington DC.Suche in Google Scholar

Kaiser Commission on Medicaid and the Uninsured. 2016b. Medicaid and Chip Eligibility, Enrollment, Renewal, and Cost-Sharing Policies as of January 2016: Findings from a 50-State Survey. Washington, DC: Kaiser Family Foundation.Suche in Google Scholar

Kaiser Family Foundation. 2017. Medicaid's Role in Behavioral Health.Suche in Google Scholar

Kaiser Family Foundation. 2018. Total Monthly Medicaid and Chip Enrollment. Washington, DC: Kaiser Family Foundation.Suche in Google Scholar

Koma, J. W., J. M. Donohue, C. L. Barry, H. A. Huskamp, and M. Jarlenski. 2017. “Medicaid Coverage Expansions and Cigarette Smoking Cessation among Low-Income Adults.” Medical Care 55 (12): 1023–29.10.1097/MLR.0000000000000821Suche in Google Scholar

Lehmann, A., P. Aslani, R. Ahmed, J. Celio, A. Gauchet, P. Bedouch, O. Bugnon, B. Allenet, and M. P. Schneider. 2014. “Assessing Medication Adherence: Options to Consider.” International Journal of Clinical Pharmacy 36 (1): 55–69.10.1007/s11096-013-9865-xSuche in Google Scholar

Levinson, D. 2011. Higher Rebates for Brand-Name Drugs Result in Lower Costs for Medicaid Compared to Medicare Part D. Washington, DC: Department of Health and Human Services Office of the Inspector General.Suche in Google Scholar

Lieberman, J. A. 2007. “Effectiveness of Antipsychotic Drugs in Patients with Chronic Schizophrenia: Efficacy, Safety and Cost Outcomes of Catie and Other Trials.” The Journal of Clinical Psychiatry 68 (2): e04–e04.10.4088/JCP.0207e04Suche in Google Scholar

Ling, W., C. Charuvastra, J. F. Collins, S. Batki, L. S. Brown, P. Kintaudi, D. R. Wesson, et al. 1998. “Buprenorphine Maintenance Treatment of Opiate Dependence: A Multicenter, Randomized Clinical Trial.” Addiction 93 (4): 475–86.10.1046/j.1360-0443.1998.9344753.xSuche in Google Scholar

Lovenheim, M. F. 2009. “The Effect of Teachers’ Unions on Education Production: Evidence from Union Election Certifications in Three Midwestern States.” Journal of Labor Economics 27 (4): 525–87.10.1086/605653Suche in Google Scholar

Maclean, J. C., M. F. Pesko, and S. C. Hill. 2017. The Effect of Insurance Expansions on Smoking Cessation Medication Use: Evidence from Recent Medicaid Expansions. Journal of Policy Analysis and Managment, 2018. National Bureau of Economic Research Working Paper Series. Cambridge, MA: National Bureau of Economic Research.10.3386/w23450Suche in Google Scholar

Maclean, J.C., and B. Saloner. 2018 “The Effect of Public Insurance Expansions on Substance Use Disorder Treatment: Evidence from the Affordable Care Act.” Journal of Policy Analysis and Managment. Accepted.10.3386/w23342Suche in Google Scholar

Manning, W. G., and J. Mullahy. 2001. “Estimating Log Models: To Transform or Not to Transform?” Journal of Health Economics 20 (4): 461–94.10.1016/S0167-6296(01)00086-8Suche in Google Scholar

Mark, T. L., W. Olesiuk, M. M. Ali, L. J. Sherman, R. Mutter, and J. L. Teich. 2017. “Differential Reimbursement of Psychiatric Services by Psychiatrists and Other Medical Providers.” Psychiatric Services Forthcoming 3: 281–85.10.1176/appi.ps.201700271Suche in Google Scholar

Miller, S., and L. R. Wherry. 2017. “Health and Access to Care during the First 2 Years of the Aca Medicaid Expansions.” New England Journal of Medicine 376 (10): 947–56.10.1056/NEJMsa1612890Suche in Google Scholar

Moffitt, R. 1992. “Incentive Effects of the Us Welfare System: A Review.” Journal of Economic Literature 30 (1): 1–61.Suche in Google Scholar

Morrill, M. I. 2009. “Issues in the Diagnosis and Treatment of Adult Adhd by Primary Care Physicians.” Primary Psychiatry 16 (5): 57–63.Suche in Google Scholar

Olfson, M. 2016. “The Rise of Primary Care Physicians in the Provision of Us Mental Health Care.” Journal of Health Politics, Policy and Law 41 (4): 559–83.10.1215/03616878-3620821Suche in Google Scholar

Paradise, J. 2017. Data Note: Medicaid Managed Care Growth and Implications of the Medicaid Expansion, edited by K. F. Foundation. Washington, DC: Kaiser Family Foundation.Suche in Google Scholar

Porter, M. E. 2010. “What Is Value in Health Care?” New England Journal of Medicine 363 (26): 2477–81.10.1056/NEJMp1011024Suche in Google Scholar

Richards, M. R., J. Marti, J. C. Maclean, J. Fletcher, and D. Kenkel. 2017. “Tobacco Control, Medicaid Coverage, and the Demand for Smoking Cessation Drugs.” American Journal of Health Economics 3 (4): 528–49.10.1162/ajhe_a_00087Suche in Google Scholar

Ridley, D. B., and K. J. Axelsen. 2006. “Impact of Medicaid Preferred Drug Lists on Therapeutic Adherence.” Pharmacoeconomics 24 (3): 65–78.10.2165/00019053-200624003-00006Suche in Google Scholar

Rosenbaum, S., D. Mehta, M. Dorley, C. Hurt, S. Rothenberg, N. Lopez, and S. Ely. 2015. Medicaid Benefit Designs for Newly Eligible Adults: State Approaches. In Commonwealth Fund Issue Brief. New York: Commonwealth Fund10.15868/socialsector.25032Suche in Google Scholar

Roth, J. 2017. Ndc Data – National Drug Code Data.Suche in Google Scholar

Ruggles, S., K. Genadek, R. Goeken, J. Grover, and M. Sobek. 2017. Integrated Public Use Microdata Series: Version 6.0 [Dataset]. Minneapolis, MN: University of Minnesota.Suche in Google Scholar

Simon, K., A. Soni, and J. Cawley. 2017. “The Impact of Health Insurance on Preventive Care and Health Behaviors: Evidence from the First Two Years of the Aca Medicaid Expansions.” Journal of Policy Analysis and Management 36 (2): 390–417.10.1002/pam.21972Suche in Google Scholar

Solon, G., S. J. Haider, and J. M. Wooldridge. 2015. “What Are We Weighting For?” Journal of Human Resources 50 (2): 301–16.10.3368/jhr.50.2.301Suche in Google Scholar

Sommers, B. D., R. J. Blendon, E. Orav, and A. M. Epstein. 2016. “Changes in Utilization and Health among Low-Income Adults after Medicaid Expansion or Expanded Private Insurance.” JAMA Internal Medicine 176 (10): 1501–09.10.1001/jamainternmed.2016.4419Suche in Google Scholar

Sommers, B. D., and D. C. Grabowski. 2017. “What Is Medicaid? More than Meets the Eye.” Jama 318 (8): 695–96.10.1001/jama.2017.10304Suche in Google Scholar

Sommers, B. D., M. Z. Gunja, K. Finegold, and T. Musco. 2015. “Changes in Self-Reported Insurance Coverage, Access to Care, and Health under the Affordable Care Act.” Jama 314 (4): 366–74.10.1001/jama.2015.8421Suche in Google Scholar

Sommers, B. D., B. Maylone, R. J. Blendon, E. J. Orav, and A. M. Epstein. 2017. “Three-Year Impacts of the Affordable Care Act: Improved Medical Care and Health among Low-Income Adults.” Health Affairs 36 (6): 1119–28.10.1377/hlthaff.2017.0293Suche in Google Scholar

Soumerai, S. B., J. Avorn, D. Ross-Degnan, and S. Gortmaker. 1987. “Payment Restrictions for Prescription Drugs under Medicaid.” New England Journal of Medicine 317 (9): 550–56.10.1056/NEJM198708273170906Suche in Google Scholar

Soumerai, S. B., D. Ross-Degnan, J. Avorn, T. J. McLaughlin, and I. Choodnovskiy. 1991. “Effects of Medicaid Drug-Payment Limits on Admission to Hospitals and Nursing Homes.” New England Journal of Medicine 325 (15): 1072–77.10.1056/NEJM199110103251505Suche in Google Scholar

Stein, D. J., J. C. Ipser, S. Seedat, C. Sager, and T. Amos. 2006. “Pharmacotherapy for Post Traumatic Stress Disorder (Ptsd).” The Cochrane Library. Cochrane Database Syst Rev. 2000 (4): CD002795.10.1002/14651858.CD002795Suche in Google Scholar

Substance Abuse and Mental Health Services Administration. 2013. Adults with Mental Illness or Substance Use Disorder Account for 40 Percent of All Cigarettes Smoked. In The NSDUH report. Rockville, MD: Substance Abuse and Mental Health Services Administration. 1–2.Suche in Google Scholar

Thomas, K. C., A. R. Ellis, T. R. Konrad, C. E. Holzer, and J. P. Morrissey. 2009. “County-Level Estimates of Mental Health Professional Shortage in the United States.” Psychiatric Services 60 (10): 1323–28.10.1176/ps.2009.60.10.1323Suche in Google Scholar

U.S. Department of Health and Human Services. 2012. States’ Collection of Rebates for Drugs Paid through Medicaid Managed Care Organizations. Washington, DC: U.S Department of Health and Human Services, Office of Inspector General.Suche in Google Scholar

Wen, H., B. G. Druss, and J. R. Cummings. 2015. “Effect of Medicaid Expansions on Health Insurance Coverage and Access to Care among Low-Income Adults with Behavioral Health Conditions.” Health Services Research 50 (6): 1787–809.10.1111/1475-6773.12411Suche in Google Scholar

Wen, H., J. M. Hockenberry, T. F. Borders, and B. G. Druss. 2017. “Impact of Medicaid Expansion on Medicaid-Covered Utilization of Buprenorphine for Opioid Use Disorder Treatment.” Medical Care 55 (4): 336–41.10.1097/MLR.0000000000000703Suche in Google Scholar

Wherry, L. R., and S. Miller. 2016. “Early Coverage, Access, Utilization, and Health Effects Associated with the Affordable Care Act Medicaid Expansions: A Quasi-Experimental Study.” Annals of Internal Medicine 164 (12): 795–803.10.7326/M15-2234Suche in Google Scholar

Winkelman, T. N. A., and V. W. Chang. 2017. “Medicaid Expansion, Mental Health, and Access to Care among Childless Adults with and without Chronic Conditions.” Journal of General Internal Medicine 33 (3): 376–383.10.1007/s11606-017-4217-5Suche in Google Scholar

Wolfers, J. 2006. “Did Unilateral Divorce Laws Raise Divorce Rates? A Reconciliation and New Results.” American Economic Review 96 (5): 1802–20.10.1257/aer.96.5.1802Suche in Google Scholar

World Health Organization. 2017. Mental Disorders Fact Sheet. World Health Organization.Suche in Google Scholar

Wright, B. M., E. H. Eiland, and R. Lorenz. 2013. “Augmentation with Atypical Antipsychotics for Depression: A Review of Evidence‐Based Support from the Medical Literature.” Pharmacotherapy: the Journal of Human Pharmacology and Drug Therapy 33 (3): 344–59.10.1002/phar.1204Suche in Google Scholar

Zammitti, E., R. Cohen, and M. Martinez. 2017. “Health Insurance Coverage: Early Release of Estimates from the National Health Interview Survey." In National Health Interview Survey Early Release Program. Atlanta, GA: National Center for Health Statistics.Suche in Google Scholar

Published Online: 2018-09-29

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Artikel in diesem Heft

https://doi.org/10.1515/bejeap-2018-0067

Schlagwörter für diesen Artikel

mental illness; prescription medications; healthcare; insurance