Patient-Reported Outcomes Collection at an Urban HIV Clinic Associated With a Historically Black Medical College in the Southern United States: Qualitative Interview Study Among Patients With HIV
Bibliographic record
Abstract
BACKGROUND: Black Americans, particularly in the southern United States, are disproportionately affected by the US HIV epidemic. Patient-reported outcome (PRO) data collection can improve patient outcomes and provide oft-overlooked data on mental health, substance use, and patient adherence to antiretroviral therapy. OBJECTIVE: We piloted the use of an electronic tablet to collect PRO data on social and behavioral determinants of health among people with HIV at the Meharry Community Wellness Center, an HIV clinic affiliated with a Historically Black Medical College in Nashville, Tennessee. Our primary objective was to better understand patients' experiences and comfort with using an electronic PRO tool through patient interviews. METHODS: We enrolled 100 people with HIV in care at the Meharry Community Wellness Center consecutively to completely validate PRO tools using the Research Electronic Data Capture platform on a hand-held tablet. Using a purposive sampling strategy, we enrolled 20 of the 100 participants in an in-depth interview (IDI). Interview guide development was grounded in the cognitive-behavioral model, in which thoughts, feelings, and behaviors are interrelated. IDIs were audio recorded, transcribed, deidentified, and formatted for coding. A hierarchical coding system was developed and refined using an inductive-deductive approach. RESULTS: Among the 100 people with HIV enrolled, the median age was 50 (IQR 42-54) years; 89% (n=89) were Black, 60% (n=60) were male, and 82% (n=82) were living below 100% of the federal poverty level in 2016. Five major interview themes emerged: overall experience, question content, sensitive topics, clinic visit impact, and future recommendations. IDI participants felt that the tablet was easy to use and that the question content was meaningful. Question content related to trauma, sexual and drug use behaviors, mental health, stigma, and discrimination elicited uncomfortable or distressing feelings in some participants. Patients expressed a strong desire to be truthful, and most would complete these surveys without compensation at future visits if offered. CONCLUSIONS: The use of an electronic tablet to complete PRO data collection was well received by this cohort of vulnerable persons in HIV care in the southern United States. Despite some discomfort related to question content, our cohort overwhelmingly believed this was a meaningful part of their medical experience and expressed a high desire for truthfulness. Future research will focus on scaling up the implementation and evaluation of PRO data collection in a contextually appropriate manner while obtaining input from providers and staff to ensure that the collected data are both applicable and actionable.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".