2020 OPIOID USE DISORDER AND TREATMENT NEEDS +488V 17 8 +578V District of Columbia Current Estimate Projection* 3.9 % (DC Total) ℞ (DC Total) of DC residents have Opioid Use Disorder 20,623 18,424 0% |||| 5% patients patients without withoutaccess to treatment if existing access to providers treat ℞ ℞ treatment more patients 23,503 patients 1,972 receiving buprenorphine 3,944patients receiving buprenorphine total district residents ℞ 908 patients receiving methadone 1,135 patients receiving methadone with Opioid Use Disorder total patients 2,880 5,079 with access to treatment total patients with access to treatment ℞ * Projection assumes buprenorphine prescribers double their number of patients and opioid treatment programs operate at full capacity Driving Time to Nearest Treatment ℞ ℞ overdose 1,143 total deaths in DC; 47 per 100K (2016-2019) Buprenorphine: 1 minute district average 886 opioid-related overdose deaths in DC; 37 per 100K (2016-2019) car 0 30 mins. ℞ 4% of the population in DC speaks limited English; 9% of the population in DC speaks Spanish; Methadone: 11 minute distric average ℞ 2% of population the in DC speaks another language car 0 ℞ 30 mins. 4 opioid ℞ 908 treatment methadone programs in the (OTPs) district with patients; 149 per 100K residents in the district Prescribers in District of Columbia, 2020 9,601 100 active 35 buprenorphine 6 total prescribers in the district; 3% have a buprenorphine waiver ℞ prescribers active* buprenorphine prescribers with a with a * active* buprenorphine prescribers with a (2% in 2018) 30-patient limit 100-patient limit 275-patient limit *An active prescriber is defined as the primary buprenorphine prescriber for at least one patient episode during the year. Strategies to Meet Demand for Treatment in DC Increase prescribers: Adding 141 new waivered prescribers would double the active prescribers in DC and fill 3% of the current treatment gap of 20,623 people in DC, if new prescribers treat 4.9 patients each (the state average for 30-waivers). One potential source of new prescribers is the 172 inactive prescribers in DC that already have a waiver to prescribe buprenorphine. Increase prescribers and treat more patients: Active prescribers would have to treat more than 10 times as many patients to fill the treatment gap. If active prescribers doubled their number of patients, adding 141 new waivered prescribers in DC would fill 8% of the projected treatment gap of 18,424 people in DC, if new prescribers treat 9.8 patients each (twice the state average for 30-waivers). Other promising strategies: Engage health plans in prescriber outreach; expand medication for OUD (MOUD) in health centers, jails, EDs, hospitals, primary care, and addiction treatment programs, expand telehealth; coordinate with community partners, community health workers and peer recovery workers; remove state regulatory barriers to MOUD prescribing; ensure pharmacies stock MOUD. SUMMARY OF METHODS See the methodological appendix for more details Data sources. We used 2016–19 county drug overdose death data (for people ages 12 and older) from all drugs and from opioids from the CDC WONDER Multiple Cause of Death data. Data on languages spoken are from the Agency for Healthcare Research and Quality's Social Determinants of Health database. Driving estimates show the estimated driving time from DC ward centroids (estimated from DC block centroids from Open Data DC) to the nearest opioid treatment program (OTP) and buprenorphine-waivered prescriber from the Drug Enforcement Administration (DEA) Active Controlled Substances Act Registrants Database. Opioid use disorder (OUD) estimates. To estimate the demand for treatment, we calculated ward OUD rates by averaging two estimates based on different methodological approaches. For the first, we started with substate estimates of past-year pain reliever use disorder (PUD) and heroin use for people 12 and older from the combined 2016 to 2018 National Survey on Drug Use and Health (NSDUH) substate data. We adjusted these estimates for recent trends and the share of people who have heroin use only but not PUD. We then used regression models to predict ward-level rates as a function of explanatory variables that have an empirical relationship with OUD (Alzeer et al. 2017; Paulozzi et al. 2017). For the second OUD estimates, we multiplied the estimated NSDUH-based ward estimates by a scalar representing the relationship between an NSDUH-based OUD rate, known to be biased downward, and a more accurate OUD rate based on a capture-recapture analysis of seven linked Massachusetts administrative databases (Barocas et al. 2018). We averaged these two estimates to compute ward OUD rates and counts. Treatment capacity and gap estimates. To estimate buprenorphine treatment capacity, we drew on buprenorphine patient and prescriber counts from 2018 IQVIA Real-World Longitudinal Prescription data, analyzed and published by the RAND Corporation's Opioid Policy Tools and Information Center. These data contain information on active buprenorphine prescribers, defined as the primary buprenorphine prescriber for at least one patient episode during the year, and buprenorphine patients by prescriber county. We also use the Drug Enforcement Administration's Active Controlled Substances Act Registrants Database, which includes information on all prescribers with a waiver to prescribe buprenorphine and their patient limit (30, 100, or 275). We calculated a lower bound of treatment capacity in DC as the number of patients currently receiving any buprenorphine treatment in DC in the past year plus the current number of methadone patients at OTPs in DC. We computed an upper- bound estimate based on a projected increase if all buprenorphine prescribers doubled their number of patients and OTPs operated at full capacity, assuming they currently operate at 80 percent capacity. To compute the number of people with OUD who do not have access to buprenorphine or methadone treatment in DC, we subtracted the treatment capacity in DC from the estimated number of people with OUD in DC, with separate estimates for low and high treatment capacity. We assumed that all people with OUD seek treatment. Strategies to meet demand for treatment. We computed the estimated number of additional 30-waivered buprenorphine prescribers needed in DC to achieve capacity to fill the lower- and upper-bound estimates of the treatment gap, assuming new prescribers treat the estimated average number of patients per 30-waivered prescriber in DC for the lower bound and twice that for the upper bound. We present strategies to meet demand for treatment, showing a range using the lower and upper estimates of the treatment gap and the treatment capacity. In cases where the number of new prescribers needed would be more than double the number of current buprenorphine prescribers, we present an alternative, more feasible strategy of doubling the number of active prescribers or adding 10 new prescribers. In these cases, we present the share of the treatment gap that would be filled. Authors. Lisa Clemans-Cope, Douglas A. Wissoker, and Marni Epstein. Corresponding author: Lisa Clemans-Cope, lclemans@urban.org. This fact sheet builds on previous work for California in 2019. This report was written for Johns Hopkins Bloomberg School of Public Health, with funding from Bloomberg Philanthropies. The views expressed are those of the authors and should not be attributed to the Urban Institute, its trustees, or its funders. Further information on the Urban Institute's funding principles is available at urban.org/fundingprinciples. Copyright © July 2021. Urban Institute. 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