Roche cobas® HIV PCR Testing: A Payer’s Perspective Budget Impact Analysis Frank Chen*, Tri Do, Robert Luo, Beverly Goede, Dirk Schick, Joice Huang, Nick Poulios Roche Molecular Diagnostics LLC, Pleasanton, CA, USA 1 – Background 2 – Methods & Inputs 3 – Algorithm The objective of the HIV budget impact model is to provide a scenario-based analysis of the financial and clinical implications of using different HIV differentiation tests in adults who are at-risk with an acute HIV-infection or with a confirmed HIV diagnosis. The intervention utilized in this model is the Roche cobas® HIV PCR test, which is being compared to the current FDA-approved Bio-Rad Multispot test. The hypothetical test population includes individuals with positive or indeterminate HIV statuses as well as at-risk patients for acute HIV infection and needlestick exposure. The recommended time horizon for high-risk HIV testing is once every three to six months, viral load testing every three to four months if unstable, and every six to twelve months if stable. The model is designed for payers in the United States. In order to determine the prevalence of HIV within the general population, it was assumed that 10% of the 2014 U.S population would obtain an initial HIV test. After initial testing using a 4th generation immunoassay, it was assumed that 1% of the initial tests would undergo confirmatory testing using current FDA standards (Bio-Rad Multispot) or the cobas® PCR test. The general HIV population is inclusive of current HIV infected individuals, MSM (men who have sex with men), IDU (injectable drug users), pregnant women, and acute asymptomatic HIV individuals (which includes needlestick / high-risk exposed individuals). Acute asymptomatic HIV individuals are part of a unique population category. They enter a different decision branch, as individuals who initially test negative on an immunoassay only have cobas® PCR for confirmatory testing, as it is the only test able to differentiate asymptomatic acute HIV infection. Therefore, there is no comparator. HIV Inclusion Criteria: 1. General HIV positive 2. Acute HIV positive 3. MSM 4. IDU 5. Pregnant women 6. High-risk / Needlestick Differentiation test: 4th Generation Immunoassay negatives: 1. Roche cobas PCR 2. No test 4th Generation Immunoassay positives: 2. FDA-approved Bio-Rad Multispot 4 – Budget Model 5 – Markov Modeling 6 – Discussion The budget model was created utilizing assumed costs, resulting in a decision tree representing the HIV algorithm. (right). The cost of individuals who have initial CD4 counts in Stages I, II, III, IV, and death include ARV costs, OI Rx costs, inpatient costs, outpatient costs, CD4 test costs, HIV-1 RNA test costs, ED costs, non-HIV medication costs, genotype test costs, and phenotype test costs. The HIV budget impact model successfully displays estimated enrollee and overall HIV population costs based on up to date clinical trials and current healthcare costs. The ultimate impact of the model disseminates the need for accurate testing in order to provide appropriate care. Decreased transmission rates, lowered chance of HIV transmission, and additional survival months are all enhanced health outcomes from sensitive PCR testing. Further decision algorithms utilizing machine learning which are adaptable to shifting patient conditions are a possibility in the future. This would increase not only the utility of the patient, but drive the need for increasingly sensitive testing. The transition table (above) and corresponding Markov model (left) depicts the lifecycle of one patient with a median life expectancy 70 years, given that on average, the patient contracts HIV at age 20.