Identifying HIV treatment engagement factors using clinical informatics and stated preference methods

/ABSTRACT People with HIV (PWH) who experience challenges with antiretroviral therapy (ART) adherence are at increased risk for suboptimal treatment outcomes, including viral non-suppression and disengagement from care. Despite advancements in ART delivery options, personalized treatment approaches that integrate patient preferences remain underutilized, particularly among PWH facing psychosocial and documented barriers. Clinical decision support (CDS) tools offer a promising avenue to address this gap by tailoring treatment recommendations based on patient-specific needs and barriers. However, current CDS tools often fail to incorporate rich patient insights available from unstructured electronic health record (EHR) notes or systematically integrate directly reported preferences, limiting their potential to enhance adherence and outcomes. The proposed training and research plan for this K23 will enable José I. Gutierrez, Jr., PhD, FNP- BC, to acquire the expertise necessary to become an NIH-funded independent investigator who designs patient-informed CDS interventions that optimize HIV treatment delivery. Under the mentorship of an experienced multidisciplinary team, Dr. Gutierrez will use a mixed-methods approach to develop foundational components of a CDS prototype that integrates natural language processing (NLP)–derived EHR information with patient-reported preference data. Building on prior work in HIV treatment delivery and preference evaluation, he will pursue the following specific aims: (1) explore HIV treatment delivery preferences, barriers, and facilitators within EHR notes using NLP; (2) identify and quantify patient preferences, barriers, and facilitators using qualitative interviews and MaxDiff; and (3) develop the key features of a CDS prototype that generates tailored suggested actions informed by EHR and patient-preference data, and evaluate its acceptability, feasibility, usability, and intended adoption in a 9-month, cross-sectional, non-clinical user-testing study using standardized vignettes and de-identified/fictionalized cases (no live EHR). This research plan aligns with Dr. Gutierrez's career development goal to gain advanced skills in clinical informatics and NLP, qualitative and mixed-methods research, and patient-informed intervention design. Findings will provide the foundation for a subsequent NIH R01 to rigorously evaluate effectiveness in clinical settings, with the overarching goal of improving ART adherence and treatment outcomes among PWH. 1 Project Number: 1K23MH142206-01A1 | Fiscal Year: 2026 | NIH Institute/Center: National Institute of Mental Health (NIMH) | Principal Investigator: JOSE GUTIERREZ | Institution: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO, SAN FRANCISCO, CA | Award Amount: $200,880 | Activity Code: K23 | Study Section: Special Emphasis Panel[ZRG1 F17B-Q (20)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11412165