1324. Development of HIV-ASSIST, an Online, Educational, Clinical Decision Support Tool to Guide Patient-Centered ARV Regimen Selection. (26th November 2018)

• Record Type: Journal Article
• Authors: Maddali, Manoj; Li, Jonathan; Shah, Maunank
• Is Part Of: Open forum infectious diseases. Volume 5(2018)Supplement 1
• Page Start: S404
• Page End: S405
• Publication Date: 2018-11-26
• Subjects: Communicable diseases -- Periodicals; Medical microbiology -- Periodicals; Infection -- Periodicals; 616.9
• DOI: 10.1093/ofid/ofy210.1157
• Languages: English
• ISSNs: 2328-8957

Abstract

Abstract: Background: Multiple antiretroviral (ARV) regimens are effective at achieving HIV viral suppression but differ in pill burden, resistance profile, side effects, and impact on comorbidities. Current guidelines advocate for an individualized, patient-centric approach to ARV regimen selection, including simplification of ARV regimens in patients with stable viral suppression. Synthesizing these modifying factors is necessary for effective care but is a complex and time-consuming process for infectious disease and primary care practitioners. Methods: We sought to develop an online, interactive tool for ARV decision support that incorporates patient, viral, and therapeutic factors to provide evidence-based recommendations for individualized ARV regimen selection. We additionally incorporated educational materials within the tool to enhance provider learning while simultaneously improving real-time clinical care. Our goal is to optimize ARV regimen selection to provide personalized HIV care that improves patient outcomes, minimizes adverse effects, and enriches clinician knowledge of antiretrovirals. Results: We developed HIV-ASSIST (https://www.hivassist.com ) as a freely available, online resource to support clinicians caring for HIV patients. Our tool utilizes decision-analysis principles based on current guidelines, scientific literature, and expert opinions to deliver tailored recommendations on ARV regimen selection specific to each patient encounter. Decision algorithms were optimized in an iterative fashion using feedback on complex case scenarios from regional HIV experts. HIV-ASSIST evaluates and "ranks" all possible multi-drug ARV regimens across a variety of domains, including common laboratory markers (viral load, genotype, etc.) and patient-specific characteristics (medical comorbidities and drug interactions, treatment history, adherence, etc.). Through a user-friendly interface, clinicians are shown the impact of these modifying factors on ARV regimens and dosing, along with supporting clinical trial evidence. Conclusion: HIV-ASSIST is a patient-centric tool to improve patient outcomes through real-time ARV decision support and enhance knowledge of evidence-based HIV care guidelines. Disclosures: All authors: No reported disclosures.