Development and Validation of HIV-ASSIST, an Online, Educational, Clinical Decision Support Tool to Guide Patient-Centered ARV Regimen Selection

Manoj V. Maddali, Nicky J. Mehtani, Caro Converse, Sunaina Kapoor, Paul Pham, Jonathan Z. Li, Maunank Shah

Research output: Contribution to journalArticle

Abstract

BACKGROUND: 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. METHODS: 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 used a multiple-criteria decision analysis framework to construct mathematical algorithms and synthesize various patient-specific (eg, comorbidities and treatment history) and virus-specific (eg, HIV mutations) attributes. We then conducted a validation study to evaluate HIV-ASSIST with prescribing practices of experienced HIV providers at 4 large academic centers. We report on concordance of provider ARV selections with the 5 top-ranked HIV-ASSIST regimens for 10 diverse hypothetical patient-case scenarios. RESULTS: In the validation cohort of 17 experienced HIV providers, we found 99% concordance between HIV-ASSIST recommendations and provider ARV selections for 4 case-scenarios of ARV-naive patients. Among 6 cases of ARV-experienced patients (3 with and 3 without viremia), there was 84% and 88% concordance, respectively. Among 3 cases of ARV-experienced patients with viremia, providers reported 20 different ARV selections, suggesting substantial heterogeneity in ARV preferences in clinical practice. CONCLUSIONS: 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.

Original languageEnglish (US)
Pages (from-to)188-194
Number of pages7
JournalJournal of acquired immune deficiency syndromes (1999)
Volume82
Issue number2
DOIs
StatePublished - Oct 1 2019

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Clinical Decision Support Systems
HIV
Viremia
Comorbidity
Decision Support Techniques
Validation Studies
History
Guidelines
Viruses
Education
Mutation

ASJC Scopus subject areas

  • Infectious Diseases
  • Pharmacology (medical)

Cite this

Development and Validation of HIV-ASSIST, an Online, Educational, Clinical Decision Support Tool to Guide Patient-Centered ARV Regimen Selection. / Maddali, Manoj V.; Mehtani, Nicky J.; Converse, Caro; Kapoor, Sunaina; Pham, Paul; Li, Jonathan Z.; Shah, Maunank.

In: Journal of acquired immune deficiency syndromes (1999), Vol. 82, No. 2, 01.10.2019, p. 188-194.

Research output: Contribution to journalArticle

Maddali, Manoj V. ; Mehtani, Nicky J. ; Converse, Caro ; Kapoor, Sunaina ; Pham, Paul ; Li, Jonathan Z. ; Shah, Maunank. / Development and Validation of HIV-ASSIST, an Online, Educational, Clinical Decision Support Tool to Guide Patient-Centered ARV Regimen Selection. In: Journal of acquired immune deficiency syndromes (1999). 2019 ; Vol. 82, No. 2. pp. 188-194.
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abstract = "BACKGROUND: 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. METHODS: 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 used a multiple-criteria decision analysis framework to construct mathematical algorithms and synthesize various patient-specific (eg, comorbidities and treatment history) and virus-specific (eg, HIV mutations) attributes. We then conducted a validation study to evaluate HIV-ASSIST with prescribing practices of experienced HIV providers at 4 large academic centers. We report on concordance of provider ARV selections with the 5 top-ranked HIV-ASSIST regimens for 10 diverse hypothetical patient-case scenarios. RESULTS: In the validation cohort of 17 experienced HIV providers, we found 99{\%} concordance between HIV-ASSIST recommendations and provider ARV selections for 4 case-scenarios of ARV-naive patients. Among 6 cases of ARV-experienced patients (3 with and 3 without viremia), there was 84{\%} and 88{\%} concordance, respectively. Among 3 cases of ARV-experienced patients with viremia, providers reported 20 different ARV selections, suggesting substantial heterogeneity in ARV preferences in clinical practice. CONCLUSIONS: 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.",
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AU - Converse, Caro

AU - Kapoor, Sunaina

AU - Pham, Paul

AU - Li, Jonathan Z.

AU - Shah, Maunank

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