INCREASING ACCESS TO MEDICATIONS FOR OPIOID USE DISORDERS THROUGH - PowerPoint PPT Presentation

INCREASING ACCESS TO MEDICATIONS FOR OPIOID USE DISORDERS THROUGH STATE POLICY Amanda J. Abraham, PhD 1 ; Christina Andrews, PhD 2 ; Colleen Grogan, PhD 3 ; Harold Pollack, PhD 3 ; Keith Humphreys, PhD 4 ; Thomas D’Aunno, PhD 5 ; Peter Friedmann, PhD 6 1 University of Georgia; 2 University of South Carolina; 3 University of Chicago; 4 Stanford University; 5 New York University; 6 University of Massachusetts & Baystate Health Supported by NIDA Grant No. R01DA034634 (PI: Friedmann)

Opioid Epidemic ¨ 15 year increase in overdose deaths involving prescription opioid pain relievers (MMWR, 2016) ¨ Since 2000 there has been a 200% increase in the rate of overdose deaths involving opioids (MMWR, 2016) ¨ Heroin overdose deaths more than tripled in 4 years (2011-2014) (MMWR, 2016) ¨ In 2014, opioids were involved in 28,647 deaths

Opioid Sales, Admissions for Opioid-Abuse Treatment, and Deaths Due to Overdose in the US, 1999-2010 (Volkow, Frieden, Hyde, & Cha, 2014)

Policy Response ¨ Three major strategies (HHS, 2015; Rudd et al., 2016) ¤ 1. Improve the safety of prescribing practices related to opioid analgesics (e.g., PDMPs) ¤ 2. Expand access to and use of naloxone ¤ 3. Increase access to medications for the treatment of opioid use disorders n Medicaid and CHIP , NIDA, NIAAA, CDC, and SAMHSA

Medications for Opioid Use Disorders ¨ Medications are recommended for the treatment of OUDs in conjunction with psychosocial treatment ¤ Oral naltrexone, injectable naltrexone, & buprenorphine ¨ Efficacy of these medications is well-established and they are a safe and cost-effective way to reduce the risk of overdose ¤ Amass et al., 2004; Amato et al., 2011a, 2011b Krupitsky et al., 2010; Volkow et al., 2014 ¨ However, data indicate that less than half of specialty treatment programs offer any single SUD medication ( Abraham et al., 2013) ¤ Buprenorphine is the most widely prescribed medication in non-OTPs (32.5%)

SUD Treatment System ¨ SUD treatment system operates under a state- driven model ¨ Primarily funded through SAPT block grant and contracts administered through Single State Agencies (SSAs) with limited funding from Medicaid ¤ About half of treatment programs do not accept Medicaid insurance

Role of SSAs and Medicaid ¨ SSAs act relatively autonomously to organize and administer SUD treatment services ¤ Determine treatment provider qualifications, payment methods and rates, and reporting requirements ¨ In states where Medicaid covers SUD treatment, state Medicaid agencies play a similar role

SUD Treatment Services ¨ Wide state variation in organization and delivery of SUD treatment services ¨ System is characterized by limited adoption of evidence based practices (EPBs), particularly medications

Gaps in Literature ¨ Scant research has examined impact of state policy on availability of SUD medications ¤ Treatment program’s perceptions of the state policy environment (Knudsen and Abraham, 2012) ¤ Research relied on data from SSAs that was not linked with program-level data n Rieckmann et al., 2011; Rieckmann et al., 2015 ¤ Focused on adoption of buprenorphine in Opioid Treatment Programs (OTPs) n Andrews et al., 2013 ¤ Examined the impact of Medicaid policy on adoption of buprenorphine n Ducharme and Abraham, 2008

Objective ¨ To examine the impact of state policy on the adoption of OUD medications in specialty treatment programs

Conceptual Framework ¨ Framework integrates 4 models of innovation adoption in organizations ¤ 1. Government policy n Government rules and regulations ¤ 2. Market factors n Dynamics of supply, demand, and competition ¤ 3. Organizational and management characteristics n Organizational infrastructure and capacity ¤ 4. Sociotechnical factors n Fit between innovation and work needs and characteristics of staff and clients ¤ Control variables

Data ¨ Sixth wave of the National Drug Abuse Treatment System Survey (NDATSS) (2013/2014) ¤ NDATSS is a longitudinal study of SUD treatment programs conducted since 1988 ¤ Split panel design with replacement sampling to replace programs that exit the sample over time & refresh the sample to ensure a nationally representative sample at each wave

Program-Level Data ¨ Interviews were completed with program directors and clinical services supervisors of 695 treatment programs ¤ Response rate = 85.5% ¨ Constructed survey weights to account for possible nonresponse bias and ensure sample representative of population

State-Level Data ¨ To measure the state policy environment, surveys were conducted with state representatives from three state agencies: ¤ SSAs ¤ State Medicaid Agencies ¤ State Departments of Insurance ¨ SSA and Medicaid surveys ¤ Response rate for the SSA survey = 98% ¤ Response rate for the Medicaid survey = 92%

Methods ¨ Multivariate mixed effects logistic regression models ¨ Missing data on the program-level independent variables were imputed ¨ Analyses conducted using Stata 14.1

Measures: Dependent Variables ¨ 3 dichotomous dependent variables ¤ Oral naltrexone ¤ Injectable naltrexone ¤ Buprenorphine ¤ ‘1’ if program currently offered medication ¤ ‘0’ if program did not currently offer medication

Independent Variables ¨ Government policy ¤ SSA survey n SSA allocates funding for each medication (1/0) n SSA level of technical assistance provided to treatment programs (0 to 7 scale) n e.g., obtain Medicaid certification, collaborate with FQHCs and mental health providers, become approved in-network providers within private insurance plans, create electronic health records infrastructure ¤ Medicaid survey n Current Medicaid plan covers oral naltrexone, injectable naltrexone, buprenorphine (pre-Medicaid expansion plan) (1/0)

Independent Variables ¨ Market factors ¤ Increase in competition in local labor market (1/0) ¤ Number of treatment program in the county ¤ Percentage of clients abusing heroin, prescription opioids (demand for OUD treatment) ¨ Organizational and Management Characteristics ¤ Program ownership (3 dichotomous variables: private for- profit, private non-profit, public) ¤ Accredited by JC/CARF (1/0) ¤ Program size (number of clients served), log transformed ¤ Percentage of revenues from private insurance & Medicaid

Independent Variables ¨ Sociotechnical factors ¤ Staff professionalism (% staff with Master’s degree) ¤ Program director’s external networks and connections (1 to 5 sum scale) n e.g., to what extent do you rely on the following as a way of finding out about developments in the field? journals and professional publications, memberships in professional associations, etc. ¨ Control variables ¤ High risk clients (% Black, Hispanic, female clients) ¤ Program type (1/0) (Inpatient/Residential; Outpatient)

Results u Descriptive Statistics u Mixed Effects Logistic Regression Models

Descriptive Statistics Percentage of Treatment Providers Offering OUD Medications % (n) Oral naltrexone 12.3% (79 of 640) Injectable naltrexone 11.0% (70 of 639) Buprenorphine 28.7% (187 of 652) Government Policy % (n) or Mean (SD) SSA funding for oral naltrexone 12.8% (6 of 47) SSA funding for injectable naltrexone 14.9% (7 of 47) SSA funding for buprenorphine 17.0% (8 of 47) SSA level of technical assistance 4.62 (1.68) Medicaid coverage of oral naltrexone 70.8% (34 of 48) Medicaid coverage of injectable naltrexone 96.0% (48 of 50) Medicaid coverage of buprenorphine 100.0% (51)

Descriptive Statistics % (N) or Mean (SD) Market Factors Increase in competition 34.87% (234) % heroin clients 36.75 (33.05) % prescription opioid clients 31.33 (25.78) Organizational-Management Factors Program ownership Private for-profit 23.35% (152) Private non-profit 63.75% (415) Public 12.90% (84) Accredited by JC/CARF 62.0% (384) Program size (number of clients served, log) 5.75 (1.14) % private insurance revenues 11.22 (19.70) % Medicaid revenues 27.30 (30.46) Sociotechnical Factors Staff professionalism (% Master’s level staff) 37.74 (26.57) Director external networks and connections 3.07 (0.61) Control Variables High risk clients % Black 19.36 (23.26) % Hispanic 13.26 (18.61) % women 38.61 (24.19) Program type Outpatient 75.8% (527) Inpatient/residential 24.2% (168)