Christina M Andrews1, Colleen M Grogan2, Melissa A Westlake3, Amanda J Abraham4, Harold A Pollack5, Thomas A D'Aunno6, Peter D Friedmann7. 1. College of Social Work, University of South Carolina, 1512 Pendleton Street, Hamilton 309, Columbia, SC 29208, United States. Electronic address: candrews@mailbox.sc.edu. 2. School of Social Service Administration, University of Chicago, 969 E. Sixtieth Street, Chicago, IL 60637, United States. Electronic address: cgrogan@uchicago.edu. 3. College of Social Work, University of South Carolina, 1512 Pendleton Street, Hamilton 101, Columbia, SC 29208, United States. Electronic address: mull@mailbox.sc.edu. 4. School of Public and International Affairs, University of Georgia, Baldwin 202A, 204 Hall Street, Athens, GA 30602, United States. Electronic address: aabraham@uga.edu. 5. School of Social Service Administration, University of Chicago, 969 E. Sixtieth Street, Chicago, IL 60637, United States. Electronic address: haroldp@uchicago.edu. 6. Robert F. Wagner Graduate School of Public Service, New York University, 295 Lafayette Street, Room 3062, New York, NY 10012, United States. Electronic address: tdaunno@nyu.edu. 7. University of Massachusetts Medical School Baystate, 280 Chestnut Street, Springfield, MA 01199, United States. Electronic address: peter.friedmannmd@baystatehealth.org.
Abstract
OBJECTIVE: To assess the relationship of restrictions on Medicaid benefits for addiction treatment to Medicaid acceptance among addiction treatment programs. DATA SOURCES: We collected primary data from the 2013-2014 wave of the National Drug Abuse Treatment System Survey. STUDY DESIGN: We created two measures of benefits restrictiveness. In the first, we calculated the number of addiction treatment services covered by each state Medicaid program. In the second, we calculated the total number of utilization controls imposed on each service. Using a mixed-effects logistic regression model, we estimated the relationship between state Medicaid benefit restrictiveness for addiction treatment and adjusted odds of Medicaid acceptance among addiction treatment programs. DATA COLLECTION: Study data come from a nationally-representative sample of 695 addiction treatment programs (85.5% response rate), representatives from Medicaid programs in forty-seven states and the District of Columbia (response rate 92%), and data collected by the American Society for Addiction Medicine. PRINCIPAL FINDINGS: Addiction treatment programs in states with more restrictive Medicaid benefits for addiction treatment had lower odds of accepting Medicaid enrollees (AOR = 0.65; CI = 0.43, 0.97). The predicted probability of Medicaid acceptance was 35.4% in highly restrictive states, 48.3% in moderately restrictive states, and 61.2% in the least restrictive states. CONCLUSIONS: Addiction treatment programs are more likely to accept Medicaid in states with less restrictive benefits for addiction treatment. Program ownership and technological infrastructure also play an important role in increasing Medicaid acceptance.
OBJECTIVE: To assess the relationship of restrictions on Medicaid benefits for addiction treatment to Medicaid acceptance among addiction treatment programs. DATA SOURCES: We collected primary data from the 2013-2014 wave of the National Drug Abuse Treatment System Survey. STUDY DESIGN: We created two measures of benefits restrictiveness. In the first, we calculated the number of addiction treatment services covered by each state Medicaid program. In the second, we calculated the total number of utilization controls imposed on each service. Using a mixed-effects logistic regression model, we estimated the relationship between state Medicaid benefit restrictiveness for addiction treatment and adjusted odds of Medicaid acceptance among addiction treatment programs. DATA COLLECTION: Study data come from a nationally-representative sample of 695 addiction treatment programs (85.5% response rate), representatives from Medicaid programs in forty-seven states and the District of Columbia (response rate 92%), and data collected by the American Society for Addiction Medicine. PRINCIPAL FINDINGS: Addiction treatment programs in states with more restrictive Medicaid benefits for addiction treatment had lower odds of accepting Medicaid enrollees (AOR = 0.65; CI = 0.43, 0.97). The predicted probability of Medicaid acceptance was 35.4% in highly restrictive states, 48.3% in moderately restrictive states, and 61.2% in the least restrictive states. CONCLUSIONS: Addiction treatment programs are more likely to accept Medicaid in states with less restrictive benefits for addiction treatment. Program ownership and technological infrastructure also play an important role in increasing Medicaid acceptance.
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