CROI 2020 Abstract eBook

Abstract eBook

Poster Abstracts

1.37-2.02, p<0.001), and clients who paid for PrEP (aOR:2.48; 95%CI 2.06-3.0, p<0.001). Factors associated with loss to follow at month 12 were clients aged less than 20 years (aOR:2.02; 95%CI 1.1-3.67, p<0.05), and clients who paid for PrEP (aOR:1.47; 95%CI 1.18-1.84, p<0.05). Conclusion: Retention rates in free PrEP programwhere higher than in fee- based PrEP. PrEP should be available under universal health coverage to retain clients in care. Interventions tailored to support adolescents and clients with education less than bachelor's degree should be concise and promote PrEP as a health empowering tool should also be proritized to address this finding. Ram K. Shrestha 1 , Nicholas Davis 2 , Megan Coleman 3 , Laura Rusie 2 , Dawn K. Smith 1 1 CDC, Atlanta, GA, USA, 2 Howard Brown Health Center, Chicago, IL, USA, 3 Whitman- Walker Health, Washington, DC, USA Background: Pre-exposure prophylaxis (PrEP) with daily tenofovir disoproxil fumarate/emtricitabine is effective in preventing HIV acquisition, and is a major component of the new initiative to End the HIV Epidemic in the United States. The Centers for Disease Control and Prevention (CDC) recommends health care providers consider offering PrEP for people at substantial risk of acquiring HIV, but information on the costs associated with PrEP implementation is limited. We assess health care utilization and costs of PrEP implementation at two federally qualified health centers. Methods: The Sustainable Health Center Implementation PrEP Pilot (SHIPP) Study is an observational cohort of persons receiving daily oral PrEP at five participating health centers. We assessed health care utilization and costs of providing PrEP from the health care provider’s perspective for one year for a subset of patients in each of two centers, Howard Brown Health, Chicago, IL (2016-2018) and Whitman-Walker Health, Washington, DC (2015-2017). The clinics followed CDC guidelines for PrEP provision, including regular visits with providers and ongoing laboratory monitoring. Using clinic billing records and Current Procedural Terminology (CPT) coding, we retrospectively extracted the frequency and costs (in 2017 $US) of PrEP clinic visits and frequency of laboratory screening. We used the Centers for Medicare and Medicaid Services national payment rates to estimate the costs of laboratory services. Incorporating the differences in medical record keeping and available databases between the two sites, we abstracted PrEP-related health care utilization and cost data electronically in Chicago (n=482) and manually in Washington, DC (n=56). Results: The average annual number of PrEP clinic visits and associated laboratory screens per patient was 5.1 visits and 22.3 screens in Chicago, and 5.4 visits and 25.5 screens in Washington, DC (Table). The average annual cost per patient was $607 for clinic visits and $986 for laboratory screens in Chicago; and $923 for clinic visits and $1,033 for laboratory screens in Washington, DC. The average total cost per patient was $1,593 (95% CI: $1,552–$1,634) and $1,956 (95% CI: $1,444–$2,469) in Chicago and Washington, DC, respectively. Conclusion: Our analysis provides the first estimates of the implementation costs of PrEP provision in the United States, and the results inform health care providers in planning and scaling up PrEP implementation.

(OOP) costs of PrEP by third-party payer type using a national pharmacy database. Methods: Using a previously validated algorithm to distinguish TDF/FTC prescription as PrEP prescriptions in the IQVIA Longitudinal Prescriptions database, we compiled nationwide PrEP prescriptions from the year 2017. We further excluded prescriptions paid for by AIDS Drug Assistance Programs since these prescriptions were for HIV-positive patients. We classified third-party payers as commercial, Medicaid, Medicare, Gilead’s Medication Assistance Program (MAP), or other. We compared the mean cost for 30 pills and total number of pills prescribed for each third-party payer by state. Results: In 2017, 28.0 million pills of TDF/FTC for PrEP were prescribed to 146,064 patients in the United States. The total annual cost of PrEP was $1.59 billion of which $1.51 billion (94.8%) were paid by third party payers and $83 million (5.2%) were OOP costs paid by patients. Among the $1.51 billion paid by third party payers, $1.21 billion (80.2%) were paid by commercial insurance, $0.15 billion (9.9%) by Medicaid, $35 million (2.3%) by Medicare, and $68 million (4.5%) by Gilead’s MAP. Mean third-party payer costs were $1,622 for 30 pills for commercial insurance, $1,653 for Medicare, and $1,596 for Medicaid (p<0.001). The mean cost for Medicaid per 30 pills varied by state (range $1,411 to $1,795 for 30 pills, p<0.001 for mean state costs being equal) (Table 1). Mean OOP costs were $101 for 30 pills for commercial insurance compared to $72 for Medicare and $4 for Medicaid (p<0.001). Conclusion: Commercial insurers cover most PrEP prescriptions costs. The mean cost to Medicaid for 30 pills varied by state. OOP costs were lower for public insurance programs compared to commercial insurance. The pharmacy database could not account for 340B, Medicare, or Medicaid rebates and may overestimate the overall cost of TDF/FTC for PrEP to the healthcare system. 1013 SOCIAL MEDIA INFLUENCERS ENHANCE RECRUITMENT OF YOUNG THAI MSM INTO PrEP INTERVENTION Chris Beyrer 1 , Brian Weir 1 , Andrea L.Wirtz 1 , Hsu Hnin Mon 1 , Midnight Poonsaketwattana 2 , Patrick S. Sullivan 3 , Stefan Baral 1 , Chen Dun 1 , for the COPE4YMSM Study Team 1 Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA, 2 Asia Pacific Community of MSM Organizations, Bangkok, Thailand, 3 Emory University, Atlanta, GA, USA Background: Engagement of HIV at-risk young persons who might benefit from PrEP is an urgent prevention priority. Young male sex workers (MSW) aged 18-26 in Bangkok, and Pattaya, Thailand, are at very high risk for HIV acquisition and have had low rates of PrEP use. COPE is an NIH funded Thai-US collaborative effectiveness and cost effectiveness intervention for young Thai MSW recruited through venue, street, and community outreach; HIV VCT referral; and a web- based portal Methods: Eligible Thai MSW selected a prevention package with or without daily oral Truvada for PrEP and could stop or start PrEP at any time. SMS messaging was used to support adherence and collect weekly PrEP use data. Enrollment in the first 12 mos averaged 17/month—too slow to meet study aims. Of these recruits, 23.0% reported learning of the project through social media. We then implemented a social media influencers (SMI) campaign with a community partner, APCOM. Short, (< 1 minute) scenario-based videos were developed with MSW-specific content and were promoted by hired SMI with combined reach to over 5 million Thai LGBTQ followers. We also expanded recruitment sites to 3 community partner locations convenient for MSW. We used a Poisson interrupted time-series analysis (ITSA) to estimate the impact of SMI on monthly recruitment, including coefficients to capture change in intercept and change in slope. We excluded the last 2 months of recruitment due to high enrollment prior to cessation Results: SMI intervention was implemented in September 2018, with serial boosts across multiple social media platforms through August 2019 and led to 17,393 website views. The impact SMI on study recruitment and initiation of PrEP was immediate and sustained.(Figure). From campaign launch to close of enrollment in August, 2019, we enrolled 63.3 men/month, for a total N =

1011 COSTS OF PROVIDING PREEXPOSURE PROPHYLAXIS FOR HIV PREVENTION IN US HEALTH CENTERS

Poster Abstracts

1012 THIRD-PARTY PAYER AND PATIENT OUT-OF-POCKET COSTS FOR PrEP: UNITED STATES, 2017 Nathan W. Furukawa 1 , Weiming Zhu 1 , Ya-Lin A.Huang 1 , Ram K. Shrestha 1 , Karen W. Hoover 1 1 CDC, Atlanta, GA, USA Background: Pre-exposure prophylaxis (PrEP) with daily tenofovir disoproxil fumarate/emtricitabine (TDF/FTC) is an effective HIV prevention tool. While the cost of PrEP is high, information about how the costs are distributed across payers is limited. We estimated average third-party payer and out-of-pocket

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