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Record W3186740875 · doi:10.1177/09564624211032796

Feasibility of implementing a same-day electronic screening tool for clinical assessment to measure patient-reported outcomes for eliciting actionable information on adherence to HIV medication and related factors in a busy Canadian urban HIV clinic

2021· article· en· W3186740875 on OpenAlexaffabout
Shivali Suri, Deborah Yoong, Duncan Short, Darrell H. S. Tan, Mark Naccarato, Heidi M. Crane, Alexandra Musten, Rob J. Fredericksen, William B. Lober, Kevin Gough

Bibliographic record

VenueInternational Journal of STD & AIDS · 2021
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsOntario HIV Treatment NetworkUniversity of TorontoSt. Michael's Hospital
FundersViiV Healthcare
KeywordsMedicineLogistic regressionFamily medicineHuman immunodeficiency virus (HIV)Odds ratioOddsMedication adherenceHealth careViral loadInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: An optimal adherence to antiretroviral therapy (ART) is fundamental for suppression of HIV viral load and favourable treatment outcomes. Patient-reported outcomes (PROs) are effective tools for improving patient-provider communication and focusing providers' awareness on current health problems. The objectives of this analysis were (1) to determine the feasibility of implementing an electronic screening tool to measure PROs in a Canadian HIV clinic to obtain information on ART adherence and related factors and (2) to determine the factors related to sub-optimal adherence. METHODS: This implementation research with a convenience sample of 600 people living with HIV (PLWH) was conducted in a busy, academic, urban HIV clinic in Toronto, Canada. PLWH were approached to participate in PRO assessments just prior to their in-clinic appointments, including health-related domains such as mental health, housing, nutrition, financial stress and medication adherence, and responses were summarized on a single sheet available for providers to review. Feasibility of implementing PROs was assessed by quantifying response rate, completion rate, time taken and participation rate. Medication adherence was elicited by self-report of the percentage of prescribed HIV medications taken in the last month. Unadjusted and adjusted odds ratios were estimated from logistic regression models to identify factors associated with adherence of <95%. RESULTS: Of the 748 PLWH invited to participate, 692 (participation rate: 92.5%) completed the PRO assessments as standard of care in clinic. Of these, 600 consented to the use of their PRO results for research and were included in this analysis. The average response rate to the ART-related questions was 96.8% and mean completion rate was 95.5%. The median time taken to complete the assessment was 12.0 (IQR = 8.4-17.3) min, adjusted 8.7 (IQR = 7.2-10.8) min. 445 (74.9%) of participants were male, and 153 (26.2%) reported dissatisfaction with ART. 105 (19.7%) of the PLWH reported ART adherence of <95%. Multivariable logistic regression identified the following risk factors for sub-optimal adherence: dissatisfaction with ART (OR = 2.30, 95% CI 1.38-3.83), not having a family doctor or not visiting a family doctor in last year (OR = 1.69, 95% CI 1.02-2.79). CONCLUSION: Collecting self-reported health information from PLWH through PROs in a busy urban clinic was feasible and can provide relevant information to healthcare providers on issues related to adherence. This has a potential to help in individualizing ambulatory care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.088
GPT teacher head0.450
Teacher spread0.362 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2021
Admission routes2
Has abstractyes

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