A facilitation model for implementing quality improvement practices to enhance outpatient substance use disorder treatment outcomes: a stepped-wedge randomized controlled trial study protocol

Megan A O'Grady, Patricia Lincourt, Belinda Greenfield, Marc W Manseau, Shazia Hussain, Kamala Greene Genece, Charles J Neighbors, Megan A O'Grady, Patricia Lincourt, Belinda Greenfield, Marc W Manseau, Shazia Hussain, Kamala Greene Genece, Charles J Neighbors

Abstract

Background: The misuse of and addiction to opioids is a national crisis that affects public health as well as social and economic welfare. There is an urgent need for strategies to improve opioid use disorder treatment quality (e.g., 6-month retention). Substance use disorder treatment programs are challenged by limited resources and a workforce that does not have the requisite experience or education in quality improvement methods. The purpose of this study is to test a multicomponent clinic-level intervention designed to aid substance use disorder treatment clinics in implementing quality improvement processes to improve high-priority indicators of treatment quality for opioid use disorder.

Methods: A stepped-wedge randomized controlled trial with 30 outpatient treatment clinics serving approximately 2000 clients with opioid use disorder each year will test whether a clinic-level measurement-driven, quality improvement intervention, called Coaching for Addiction Recovery Enhancement (CARE), improves (a) treatment process quality measures (use of medications for opioid use disorder, in-treatment symptom and therapeutic progress, treatment retention) and (b) recovery outcomes (substance use, health, and healthcare utilization). The CARE intervention will have the following components: (1) staff clinical training and tools, (2) quality improvement and change management training, (3) external facilitation to support implementation and sustainability of quality improvement processes, and (4) an electronic client-reported treatment progress tool to support data-driven decision making and clinic-level quality measurement. The study will utilize multiple sources of data to test study aims, including state administrative data, client-reported survey and treatment progress data, and staff interview and survey data.

Discussion: This study will provide the field with a strong test of a multicomponent intervention to improve providers' capacity to make systematic changes tied to quality metrics. The study will also result in training and materials that can be shared widely to increase quality improvement implementation and enhance clinical practice in the substance use disorder treatment system.

Trial registration: Trial # NCT04632238NCT04632238 registered at clinicaltrials.gov on 17 November 2020.

Keywords: External facilitation; Implementation; Opioid use disorder; Quality improvement; Quality metrics; Stepped-wedge trial.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Intervention conceptual method
Fig. 2
Fig. 2
Stepped-wedge design

References

    1. SAMHSA. Key substance use and mental health indicators in the United States: Results from the 2018 National Survey on Drug Use and Health Rockville, MD: Center for Behavioral Statistics and Qaulity, Substance Abuse and Mental Health Services Administration 2019. Report No.: HHS Publication No. PEP19-5068, NSDUH Series H-54.
    1. AHRQ. HCUP Fast Stats-Opioid Related Hospital Use 2020 [Available from: .
    1. SAMHSA. Treatment Episode Data Set (TEDS) 2017: Admissions and Discharges from Publicly-Funded Substance Use Treatment Rockville, MD 2019.
    1. Czeisler M, Lane RI, Petrosky E, et al. Mental health, substance use, and suicidal ideation during the COVID-19 pandemic—United States, June 24–30, 2020. MMWR Morb Mortal Wkly Rep. 2020;69:1049–1057. doi: 10.15585/mmwr.mm6932a1.
    1. Volkow ND. Collision of the COVID-19 and addiction epidemics. Annals of Internal Medicine. 2020;173(1):61–62. doi: 10.7326/M20-1212.
    1. Slavova S, Rock P, Bush HM, Quesinberry D, Walsh SL. Signal of increased opioid overdose during COVID-19 from emergency medical services data. Drug and Alcohol Dependence. 2020;214:108176. doi: 10.1016/j.drugalcdep.2020.108176.
    1. Alexander GC, Stoller KB, Haffajee RL, Saloner B. An epidemic in the midst of a pandemic: opioid use disorder and COVID-19. Annals of Internal Medicine. 2020;173(1):57–58. doi: 10.7326/M20-1141.
    1. Murphy SM, Yoder J, Pathak J, Avery J. Healthcare utilization patterns among persons who use drugs during the COVID-19 pandemic. J Substance Abuse Treatment. 2020;108177.
    1. Linas BP, Savinkina A, Barbosa C, Mueller PP, Cerdá M, Keyes K, et al. A clash of epidemics: Impact of the COVID-19 pandemic response on opioid overdose. J Substance Abuse Treatment. 2021;120:108158. doi: 10.1016/j.jsat.2020.108158.
    1. Ahmad FBR, L.M., Sutton, P. . Provisional drug overdose death counts. National Center for Health Statistics; 2020.
    1. Institute of Medicine . Improving the quality of health care for mental and substance-use conditions. Washington, D.C.: National Academies Press; 2006.
    1. Office of Surgeon General. Facing addiction in America: the surgeon general's report on alcohol, drugs, and health. Reports of the Surgeon General. Washington (DC): US Department of Health and Human Services; 2016.
    1. Padwa H, Urada D, Gauthier P, Rieckmann T, Hurley B, Crevecouer-MacPhail D, et al. Organizing publicly funded substance use disorder treatment in the United States: moving toward a service system approach. J Subst Abuse Treat. 2016;69:9–18. doi: 10.1016/j.jsat.2016.06.010.
    1. National Center on Addiction and Substance Abuse at Columbia University. Addiction medicine: closing the gap between science and practice author; 2012 June 2012.
    1. England MJ, Butler AS, Gonzalez ML. Psychosocial interventions for mental and substance use disorders: a framework for establishing evidence-based standards: National Academy Press. 2015.
    1. McLellan AT, Lewis DC, O'Brien CP, Kleber HD. Drug dependence, a chronic medical illness: implications for treatment, insurance, and outcomes evaluation. Jama. 2000;284(13):1689–1695. doi: 10.1001/jama.284.13.1689.
    1. Carroll KM. new methods of treatment efficacy research: Bridging clinical research and clinical practice. Alcohol Health Research World. 1997;21(4):352–359.
    1. Stark MJJCpr. Dropping out of substance abuse treatment: A clinically oriented review. 1992;12(1):93-116.
    1. Mattson ME, Del Boca FK, Carroll KM, Cooney NL, DiClemente CC, Donovan D, et al. Compliance with treatment and follow-up protocols in project MATCH: predictors and relationship to outcome. 1998;22(6):1328-1339.
    1. Kelly SM, O’Grady KE, Mitchell SG, Brown BS, Schwartz RPJD, dependence a. Predictors of methadone treatment retention from a multi-site study: a survival analysis. 2011;117(2-3):170-175.
    1. Laudet AB, Stanick V, Sands B. What could the program have done differently? A qualitative examination of reasons for leaving outpatient treatment. J Substance Abuse Treatment. 2009;37(2):182–190. doi: 10.1016/j.jsat.2009.01.001.
    1. Teruya C, Schwartz RP, Mitchell SG, Hasson AL, Thomas C, Buoncristiani SH, et al. Patient perspectives on buprenorphine/naloxone: a qualitative study of retention during the starting treatment with agonist replacement therapies (START) study. J Psychoactive Drugs. 2014;46(5):412–426. doi: 10.1080/02791072.2014.921743.
    1. Thylstrup BJNSoA, Drugs. Numbers and narratives. Relations between patient satisfaction, retention, outcome and program factors in outpatient substance abuse treatment. 2011;28(5-6):471-86.
    1. Buck JA. The looming expansion and transformation of public substance abuse treatment under the Affordable Care Act. Health Affairs. 2011;30(8):1402–1410. doi: 10.1377/hlthaff.2011.0480.
    1. Roy AK, Miller MM. The Medicalization of Addiction Treatment Professionals. J Psychoactive Drugs. 2012;44(2):107–118. doi: 10.1080/02791072.2012.684618.
    1. Pating DR, Miller MM, Goplerud E, Martin J, Ziedonis DM. New systems of care for substance use disorders: treatment, finance, and technology under health care reform. Psychiatric Clinics of North America. 2012;35(2):327–356. doi: 10.1016/j.psc.2012.03.004.
    1. Soper MH, Matulis, R., Menschner, C. Moving Toward Value-Based Payment for Medicaid Behavioral Health Services Center for Health Care Strategies, Inc.; 2017.
    1. Andrews C, Abraham A, Grogan CM, Pollack HA, Bersamira C, Humphreys K, et al. Despite Resources From The ACA, Most states do little to help addiction treatment programs implement health care reform. Health Aff (Millwood). 2015;34(5):828–835. doi: 10.1377/hlthaff.2014.1330.
    1. O’Grady MA, Lincourt P, Gilmer E, Kwan M, Burke C, Lisio C, et al. How are substance use disorder treatment programs adjusting to value-based payment? A statewide qualitative study. Substance Abuse: Research and Treatment. 2020;14:1178221820924026.
    1. Hunter SB, Ober AJ, Paddock SM, Hunt PE, Levan D. Continuous quality improvement (CQI) in addiction treatment settings: design and intervention protocol of a group randomized pilot study. Addiction Science & Clinical Practice. 2014;9(1):4. doi: 10.1186/1940-0640-9-4.
    1. Hunter SB, Rutter CM, Ober AJ, Booth MS. Building capacity for continuous quality improvement (CQI): A pilot study. J Substance Abuse Treatment. 2017;81:44–52. doi: 10.1016/j.jsat.2017.07.014.
    1. Wisdom JP, Ford JH, II, Hayes RA, Edmundson E, Hoffman K, McCarty D. Addiction treatment agencies’ use of data: A qualitative assessment. J Behavioral Health Services Res. 2006;33(4):394–407. doi: 10.1007/s11414-006-9039-x.
    1. Ford JH, II, Wise M, Wisdom J. A peek inside the box: how information flows through substance abuse treatment agencies. J Technol Human Services. 2010;28(3):121–143. doi: 10.1080/15228835.2010.508254.
    1. Crèvecoeur-MacPhail D, Bellows A, Rutkowski BA, Ransom L, Myers AC, Rawson RA. “I've been NIATxed”: Participants' Experience with Process Improvement. J Psychoactive Drugs. 2010;42(sup6):249–259. doi: 10.1080/02791072.2010.10400548.
    1. Gustafson DH, Quanbeck AR, Robinson JM, Ford JH, 2nd, Pulvermacher A, French MT, et al. Which elements of improvement collaboratives are most effective? A cluster-randomized trial. Addiction. 2013;108(6):1145–1157. doi: 10.1111/add.12117.
    1. McCarty D, Gustafson DH, Wisdom JP, Ford J, Choi D, Molfenter T, et al. The Network for the Improvement of Addiction Treatment (NIATx): enhancing access and retention. Drug Alcohol Depend. 2007;88(2-3):138–145. doi: 10.1016/j.drugalcdep.2006.10.009.
    1. Fields D, Knudsen HK, Roman PM. Implementation of Network for the Improvement of Addiction Treatment (NIATx) processes in substance use disorder treatment centers. J Behavioral Health Services Res. 2016;43(3):354–365. doi: 10.1007/s11414-015-9466-7.
    1. Kitson A, Harvey G. Facilitating an evidence-based innovation into practice. Implementing Evidence-Based Practice In Healthcare: A Facilitation Guide. 2015:85.
    1. Harvey G, Kitson AJIS. PARIHS revisited: from heuristic to integrated framework for the successful implementation of knowledge into practice. 2016;11(1):33.
    1. Swindle T, Johnson SL, Whiteside-Mansell L, Curran GM. A mixed methods protocol for developing and testing implementation strategies for evidence-based obesity prevention in childcare: a cluster randomized hybrid type III trial. Implementation Science. 2017;12(1):90. doi: 10.1186/s13012-017-0624-6.
    1. Stetler CB, Damschroder LJ, Helfrich CD, Hagedorn HJ. A Guide for applying a revised version of the PARIHS framework for implementation. Implementation Science. 2011;6(1):99. doi: 10.1186/1748-5908-6-99.
    1. O’Grady MA, Lincourt P, Hussain S, Gilmer E, Neighbors CJ. An instrument for assessing progress in substance use disorder treatment: a pilot study of initial reliability and factor structure of the Treatment Progress Assessment-8. Journal of Addictive Diseases. 2020;38(1):49–54. doi: 10.1080/10550887.2019.1695512.
    1. Jaspers MWM, Steen T, Bos Cvd, Geenen M. The think aloud method: a guide to user interface design. Int J Med Informatics. 2004;73(11):781-795.
    1. Willis G. Cognitive interviewing: a tool for improving questionnaire design. Thousand Oaks: Sage Publications; 2004.
    1. Gill J. Alcohol problems in employment: epidemiology and responses. Alcohol Alcohol. 1994;29(3):233–248.
    1. Aarons GA, Hurlburt M, Horwitz SM. Advancing a conceptual model of evidence-based practice implementation in public service sectors. Administration and Policy in Mental Health and Mental Health Services Research. 2011;38(1):4–23. doi: 10.1007/s10488-010-0327-7.
    1. Neighbors CJ, Yerneni R, O'Grady MA, Sun Y, Morgenstern J. Recurrent use of inpatient withdrawal management services: characteristics, service use, and cost among Medicaid clients. J Subst Abuse Treat. 2018;92:77–84. doi: 10.1016/j.jsat.2018.06.013.
    1. Shelley DR, Ogedegbe G, Anane S, Wu WY, Goldfeld K, Gold HT, et al. Testing the use of practice facilitation in a cluster randomized stepped-wedge design trial to improve adherence to cardiovascular disease prevention guidelines: HealthyHearts NYC. Implement Sci. 2016;11(1):88. doi: 10.1186/s13012-016-0450-2.
    1. Drabble L, Trocki KF, Salcedo B, Walker PC, Korcha RA. Conducting qualitative interviews by telephone: Lessons learned from a study of alcohol use among sexual minority and heterosexual women. Qual Soc Work. 2016;15(1):118–133. doi: 10.1177/1473325015585613.
    1. Smith EM. Telephone interviewing in healthcare research: a summary of the evidence. Nurse Res. 2005;12(3):32–41. doi: 10.7748/nr2005.01.12.3.32.c5946.
    1. Ruetsch C, Tkacz J, Nadipelli VR, Brady BL, Ronquest N, Un H, et al. Heterogeneity of nonadherent buprenorphine patients: subgroup characteristics and outcomes. Am J Manag Care. 2017;23(6):e172–e1e9.
    1. Peterson AM, Nau DP, Cramer JA, Benner J, Gwadry-Sridhar F, Nichol M. A checklist for medication compliance and persistence studies using retrospective databases. Value Health. 2007;10(1):3–12. doi: 10.1111/j.1524-4733.2006.00139.x.
    1. National Quality Forum. Continuity of pharmacotherapy for opioid use disorder [Internet]. National Quality Forum; 2018 [Available from: .
    1. Center for the Application of Prevention Technologies. Using International Classification of Diseases (ICD) Codes to Assess Opioid-Related Overdose Deaths. Substance Abuse and Mental Health Services Administration; 2018 09/04/2018.
    1. Rudd RA, Seth P, David F, Scholl L. Increases in Drug and Opioid-Involved Overdose Deaths - United States, 2010-2015. MMWR Morb Mortal Wkly Rep. 2016;65(50-51):1445–1452. doi: 10.15585/mmwr.mm655051e1.
    1. Kabiri M, Chhatwal J, Donohue JM, Roberts MS, James AE, Dunn MA, et al. Long-term disease and economic outcomes of prior authorization criteria for Hepatitis C treatment in Pennsylvania Medicaid. Healthcare. 2017;5(3):105–111. doi: 10.1016/j.hjdsi.2016.11.001.
    1. Isenhour CJ, Hariri SH, Hales CM, Vellozzi CJ. Hepatitis C antibody testing in a commercially insured population, 2005-2014. Am J Prev Med. 2017;52(5):625–631. doi: 10.1016/j.amepre.2016.12.016.
    1. McLellan AT, Kushner H, Metzger D, Peters R, Smith I, Grissom G, et al. The Fifth Edition of the Addiction Severity Index. J Subst Abuse Treat. 1992;9(3):199–213. doi: 10.1016/0740-5472(92)90062-S.
    1. Alterman AI, Cacciola JS, Ivey MA, Habing B, Lynch KG. Reliability and validity of the alcohol short index of problems and a newly constructed drug short index of problems. Journal of studies on alcohol and drugs. 2009;70(2):304–307. doi: 10.15288/jsad.2009.70.304.
    1. Ware JE, Jr, Kosinski M, Keller SD. A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Medical care. 1996;34(3):220–233. doi: 10.1097/00005650-199603000-00003.
    1. Ling W, Farabee D, Liepa D, Wu LT. The Treatment Effectiveness Assessment (TEA): an efficient, patient-centered instrument for evaluating progress in recovery from addiction. Subst Abuse Rehabil. 2012;3(1):129–136. doi: 10.2147/SAR.S38902.
    1. Drobes DJ, Thomas SE. Assessing craving for alcohol. Alcohol Res Health. 1999;23(3):179–186.
    1. Nutting PA, Crabtree BF, Stewart EE, Miller WL, Palmer RF, Stange KC, et al. Effect of facilitation on practice outcomes in the National Demonstration Project model of the patient-centered medical home. Ann Fam Med. 2010;8(Suppl 1):S33–S44. doi: 10.1370/afm.1119.
    1. Solberg LI, Asche SE, Margolis KL, Whitebird RR. Measuring an organization's ability to manage change: the change process capability questionnaire and its use for improving depression care. Am J Med Qual. 2008;23(3):193–200. doi: 10.1177/1062860608314942.
    1. Friedmann PD, Wilson D, Knudsen HK, Ducharme LJ, Welsh WN, Frisman L, et al. Effect of an organizational linkage intervention on staff perceptions of medication-assisted treatment and referral intentions in community corrections. J Subst Abuse Treat. 2015;50:50–58. doi: 10.1016/j.jsat.2014.10.001.
    1. Green CA, McCarty D, Mertens J, Lynch FL, Hilde A, Firemark A, et al. A qualitative study of the adoption of buprenorphine for opioid addiction treatment. J Subst Abuse Treat. 2014;46(3):390–401. doi: 10.1016/j.jsat.2013.09.002.
    1. Gold MR, Siegel J, Russell LB, Weinstein MC, editors. Cost-effectiveness in health and medicine. New York: Oxford University Press; 1996.
    1. Drummond MF, O'Brien B, Stoddart GL, Torrance GW. Methods for the economic evaluation of health care programmes. New York: Oxford University Press; 1997.
    1. Muenning P. Designing and Conducting Cost-Effectiveness Analyses in Medicine and Health Care. San Francisco: Jossey-Bass; 2002.
    1. Chase RB, Aquilano NJ, Jacobs RF. Production and operations management: manufacturing and services. 8. Boston: Irwin McGraw-Hill; 1998. p. 889.
    1. Finkler SA, Ward DM. Essential of cost accounting for health care organizations. 2. Gaithersburg: Aspen Publication; 1999.
    1. Horngren CT, Sundem GL, Stratton WO. Introduction to management accounting. 11. Upper Saddle River: Prentice Hall; 1999.
    1. Horngren CT, Foster G, Datar SM. Cost Accounting: A Managerial Emphasis. 10. Upper Saddle River: Prentice Hall; 2000.
    1. Kaplan RS, Atkinson AA. Advanced Management Accounting. 3. Upper Saddle River: Prentice Hall; 1998.
    1. Hunt VD. Process mapping: how to reengineer your business process. New York: John Wiley and Sons; 1996.
    1. Coyle D, Lee KM. The problem of protocol driven costs in pharmacoeconomic analysis. Pharmacoeconomics. 1998;14(4):357–363. doi: 10.2165/00019053-199814040-00003.
    1. Little RA, Rubin DB. Statistical Analysis with Missing Data. New York: Wiley; 1987.
    1. Raghunathan TE. What do we do with missing data? Some options for analysis of incomplete data. Annu Rev Public Health. 2004;25:99–117. doi: 10.1146/annurev.publhealth.25.102802.124410.
    1. Robins JM, Rotnitzky A, Zhao LP. Estimation of regression-coefficients when some regressors are not always observed. Journal of the American Statistical Association. 1994;89(427):846–866. doi: 10.1080/01621459.1994.10476818.
    1. Hussey MA, Hughes JP. Design and analysis of stepped wedge cluster randomized trials. Contemp Clin Trials. 2007;28(2):182–191. doi: 10.1016/j.cct.2006.05.007.
    1. Baio G, Copas A, Ambler G, Hargreaves J, Beard E, Omar RZ. Sample size calculation for a stepped wedge trial. Trials. 2015;16:354. doi: 10.1186/s13063-015-0840-9.
    1. Hemming K, Lilford R, Girling AJ. Stepped-wedge cluster randomised controlled trials: a generic framework including parallel and multiple-level designs. Stat Med. 2015;34(2):181–196. doi: 10.1002/sim.6325.
    1. Hemming K, Taljaard M. Sample size calculations for stepped wedge and cluster randomised trials: a unified approach. J Clin Epidemiol. 2016;69:137–146. doi: 10.1016/j.jclinepi.2015.08.015.
    1. Hughes JP, Granston TS, Heagerty PJ. Current issues in the design and analysis of stepped wedge trials. Contemp Clin Trials. 2015;45(Pt A):55–60. doi: 10.1016/j.cct.2015.07.006.
    1. Martin J, Taljaard M, Girling A, Hemming K. Systematic review finds major deficiencies in sample size methodology and reporting for stepped-wedge cluster randomised trials. BMJ Open. 2016;6(2):e010166. doi: 10.1136/bmjopen-2015-010166.
    1. Cengiz D, Dube A, Lindner A, Zipperer B. The effect of minimum wage on low-wage jobs: Evidence from the United States using a bunching estimator. Cambridge, MA: National Bureau of Economic Research; 2019 January 2019. Contract No.: 25434.
    1. Goodman-Bacon A. Difference-in-difference with variation in treatment timing. Cambridge, MA: National Bureau of Economic Research; 2018 September 2018. Contract No.: 25018.
    1. Creswell J, Plano Clark, V.L., Gutmann, M.L., & Hanson, W.E. Advanced mixed methods research designs. In: Teddlie ATC, editor. Handbook of mixed methods research designs. Thousand Oaks: Sage; 2003.
    1. Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15(9):1277–1288. doi: 10.1177/1049732305276687.
    1. Erlingsson C, Brysiewicz P. A hands-on guide to doing content analysis. African J Emergency Med. 2017;7(3):93–99. doi: 10.1016/j.afjem.2017.08.001.
    1. Singer JW, J.B. Applied longitudinal data analysis: modeling change and event occurance New York: Oxford University Press. 2003.
    1. TreeAge Pro Healthcare Module. 2006 ed. Williamstown, MA: Treeage Software, Inc; 2008.
    1. Manning WG, Basu A, Mullahy J. Generalized modeling approaches to risk adjustment of skewed outcomes data. Journal of Health Economics. 2005;24(3):465–488. doi: 10.1016/j.jhealeco.2004.09.011.
    1. Mullahy J. Much ado about two: reconsidering retransformation and the two-part model in health econometrics. J Health Econ. 1998;17(3):247–281. doi: 10.1016/S0167-6296(98)00030-7.
    1. Duan N. Smearing Estimate:A non-parametric retransformation method. Journal of the American Statistical Association. 1983;78(383):605–610. doi: 10.1080/01621459.1983.10478017.
    1. Duan N, Manning WG, Morris CN, Newhouse JP. A comparison of alternative models for the demand for medical care. J Business Economic Statistics. 1983;1(2):115–126.
    1. Manning WG, Mullahy J. Estimating log models: to transform or not to transform? J Health Econ. 2001;20(4):461–494. doi: 10.1016/S0167-6296(01)00086-8.
    1. Hemming K, Girling A. A menu-driven facility for power and detectable-difference calculations in stepped-wedge cluster-randomized trials. Stata J. 2014;14(2):363–380. doi: 10.1177/1536867X1401400208.
    1. Bright RA, Avorn J, Everitt DE. Medicaid data as a resource for epidemiologic studies: strengths and limitations. J Clin Epidemiol. 1989;42(10):937–945. doi: 10.1016/0895-4356(89)90158-3.
    1. Garnick DW, Hodgkin D, Horgan CM. Selecting data sources for substance abuse services research. J Subst Abuse Treat. 2002;22(1):11–22. doi: 10.1016/S0740-5472(01)00208-2.
    1. Clark RE, Baxter JD, Aweh G, O'Connell E, Fisher WH, Barton BA. Risk factors for relapse and higher costs among medicaid members with opioid dependence or abuse: opioid agonists, comorbidities, and treatment history. J Subst Abuse Treat. 2015;57:75–80. doi: 10.1016/j.jsat.2015.05.001.
    1. Ganguly R, Kotzan JA, Miller LS, Kennedy K, Martin BC. Prevalence, trends, and factors associated with antipsychotic polypharmacy among Medicaid-eligible schizophrenia patients, 1998-2000. J Clin Psychiatry. 2004;65(10):1377–1388. doi: 10.4088/JCP.v65n1013.
    1. Bachhuber MA, Mehta PK, Faherty LJ, Saloner B. Medicaid coverage of methadone maintenance and the use of opioid agonist therapy among pregnant women in specialty treatment. Med Care. 2017;55(12):985–990. doi: 10.1097/MLR.0000000000000803.
    1. Clark RE, Samnaliev M, McGovern MP. Impact of substance disorders on medical expenditures for medicaid beneficiaries with behavioral health disorders. Psychiatr Serv. 2009;60(1):35–42. doi: 10.1176/ps.2009.60.1.35.
    1. Gordon AJ, Lo-Ciganic WH, Cochran G, Gellad WF, Cathers T, Kelley D, et al. Patterns and quality of buprenorphine opioid agonist treatment in a large medicaid program. J Addict Med. 2015;9(6):470–477. doi: 10.1097/ADM.0000000000000164.
    1. Neighbors CJ, Sun Y, Yerneni R, Tesiny E, Burke C, Bardsley L, et al. Medicaid care management: description of high-cost addictions treatment clients. J Subst Abuse Treat. 2013;45(3):280–286. doi: 10.1016/j.jsat.2013.02.009.
    1. Prost A, Binik A, Abubakar I, Roy A, De Allegri M, Mouchoux C, et al. Logistic, ethical, and political dimensions of stepped wedge trials: critical review and case studies. Trials. 2015;16:351. doi: 10.1186/s13063-015-0837-4.

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