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Record W4294486566 · doi:10.1136/gutjnl-2022-iddf.179

IDDF2022-ABS-0110 Cuagain: providing care in the covid era, a randomized trial of video assisted virtual, in-person, telephone appointments in gastroenterology patients

2022· article· en· W4294486566 on OpenAlexaff
Ciarán Galts, Dustin Loomes, Kia Cade, Braden D. Siempelkamp

Bibliographic record

VenueClinical Gastroenterology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsIsland HealthUniversity of British ColumbiaMcMaster University
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)MedicineRandomized controlled trialMultimediaComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

Background COVID-19 spurred a dramatic shift from in-person patient visits toward virtual care. To date, there are no prospective studies randomizing patients to different styles of appointment and assessing their perspectives on the type of visit. We aimed to identify preferred styles of appointments across various patient factors to inform decisions regarding the optimal appointment style for patients. Methods We randomized Inflammatory Bowel Disease (IBD) patients’ follow-up appointments to either in-person, telehealth (video+audio), or telephone and subsequent appointments to the alternate appointment types in a single-centre study. Participants completed surveys after each appointment style to minimize bias. We collected anthropometric data and analyzed average scores assessing for potential associations. We used standard regression analyses and T-scores for the assessment of statistical significance. Results Fifty-two surveys were completed, 20 in-person, 17 telephones, and 15 telehealth, for a total of 56 participants (more data to come). The average age was 45.0 ±16yrs and 59% were female. The overall patient score by appointment type (out of ten) was 9.2 ±0.7 for in-person, 8.3 ±1.4 for telephone, and 7.3 ±2.4 for telehealth (IDDF2022-ABS-0110 Figure 1. Ratings of key elements by appointment type). The percentage of patients who would have preferred an alternate appointment style was 25.0% for in-person, 52.9% for telephone, and 33.0% for telehealth (IDDF2022-ABS-0110 Figure 2. Appointment preferences and requirements). The highest-rated factors for preference for an in-person appointment were optimal communication and interaction with the care provider (86.4%) (IDDF2022-ABS-0110 Figure 3. Factors contributing to preferred appointment type). Among participants who would have preferred telehealth appointments 62.5%, and 37.5% cited time savings and cost savings as reasons respectively, and 60.0% and 33.3% for the same reasons for telephone-based appointments. In-person appointments were associated with a higher cost and longer time commitment. Conclusions In our study randomizing IBD patients to telehealth, telephone or in-person visits, it is clear that all appointment styles have their merits. Despite the increased cost and time commitment, there was a trend toward the preference for in-person appointments, though not statistically significant. As we shift away from in-person patient visits, we suggest that providers should consider patient preferences in choosing a style of appointment.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0200.001

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 head0.094
GPT teacher head0.401
Teacher spread0.307 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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