HIV-ASSIST

HIV-ASSIST provides decision support for personalized antiretroviral (ARV) regimen selection by ranking candidate regimens using patient-specific and virus-specific factors to prioritize viral suppression, tolerability, and adherence.


Key Features:

  • Personalized ARV Regimen Selection: Ranks antiretroviral regimens using a composite objective that prioritizes viral suppression while maximizing tolerability and adherence, incorporating comorbidities, treatment history, and virus-specific attributes such as HIV mutations.
  • Multiple-Criteria Decision Analysis Framework: Implements a multiple-criteria decision analysis framework to construct mathematical algorithms that synthesize modifying factors including pill burden, side effects, barriers to resistance, and impact on comorbidities.
  • Educational Resource: Provides educational content for clinicians about ART options and principles for tailoring regimens to individual patient needs.

Scientific Applications:

  • Clinical Decision Support: Generates ranked lists of ARV options tailored to individual patient scenarios to inform clinician regimen selection.
  • Research Validation: Validated against prescribing choices of experienced HIV providers at four academic centers, showing 99% concordance for ARV-naive patients and 84%–88% concordance for ARV-experienced patients.

Methodology:

Uses multiple-criteria decision analysis to construct mathematical algorithms that integrate patient-specific and virus-specific data (including HIV mutations) into regimen rankings; validation compared tool recommendations with provider selections across hypothetical patient-case scenarios.

Topics

Details

Cost:
Free of charge
Tool Type:
web application
Operating Systems:
Mac, Linux, Windows
Added:
11/14/2019
Last Updated:
11/24/2024

Operations

Publications

Maddali MV, Mehtani NJ, Converse C, Kapoor S, Pham P, Li JZ, Shah M. Development and Validation of HIV-ASSIST, an Online, Educational, Clinical Decision Support Tool to Guide Patient-Centered ARV Regimen Selection. JAIDS Journal of Acquired Immune Deficiency Syndromes. 2019;82(2):188-194. doi:10.1097/qai.0000000000002118. PMID:31513553.