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Development and validation of HIV-ASSIST, an online, educational, clinical decision support tool to guide patient-centered ARV regimen selection
Journal of Acquired Immune Deficiency Syndromes
Multiple antiretroviral (ARV) regimens are effective at achieving HIV viral suppression but differ in pill burden, side effects, barriers to resistance, and impact on comorbidities. Current guidelines advocate for an individualized approach to ARV regimen selection, but synthesizing these modifying factors is complex and time-consuming.
We describe the development of HIV-ASSIST (https://www.hivassist.com), a free, online decision support tool for ARV selection and HIV education. HIV-ASSIST ranks potential ARV options for any given patient scenario using a composite objective of achieving viral suppression while maximizing tolerability and adherence. We utilized a multiple-criteria decision analysis framework to construct mathematical algorithms and synthesize various patient-specific (e.g., comorbidities, treatment history) and virus-specific (e.g., HIV mutations) attributes. We then conducted a validation study to evaluate HIV-ASSIST with prescribing practices of experienced HIV providers at four large academic centers. We report on concordance of provider ARV selections with the five top-ranked HIV-ASSIST regimens for ten diverse hypothetical patient-case scenarios.
In the validation cohort of 17 experienced HIV providers, we found 99% concordance between HIV-ASSIST recommendations and provider ARV selections for four case-scenarios of ARV-naïve patients. Among six cases of ARV-experienced patients (three with and three without viremia), there was 84% and 88% concordance, respectively. Among three cases of ARV-experienced patients with viremia, providers reported 20 different ARV selections, suggesting substantial heterogeneity in ARV preferences in clinical practice.
HIV-ASSIST is a novel patient-centric educational decision support tool that provides ARV recommendations concordant with experienced HIV providers for a diverse set of patient scenarios.
Maddali M, Mehtani N, Converse C, Kapoor S, Pham P, Li J, Shah M. Development and validation of HIV-ASSIST, an online, educational, clinical decision support tool to guide patient-centered ARV regimen selection. JAIDS. 2019 Jul. [Epub ahead of print] doi: 10.1097/QAI.0000000000002118.