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Record W3008246424 · doi:10.1093/jcag/gwz047.168

A169 DEVELOPMENT OF A DECISION TOOL TO IMPROVE UTILISATION OF RECOMMENDED SURVEILLANCE INTERVALS FOR INDIVIDUALS WITH COLORECTAL POLYPS: A FOCUS GROUP ANALYSIS

2020· article· en· W3008246424 on OpenAlexaffabout
E Lee, Harminder Singh, Alexandria Simms, Gayle Restall, Leigh Anne Shafer, John R. Walker, J Park

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2020
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineGuidelineColonoscopyFocus groupConfidence intervalMedical physicsPrimary careMedical educationFamily medicineColorectal cancerInternal medicinePathology

Abstract

fetched live from OpenAlex

Abstract Background Several studies have demonstrated a high utilization of colonoscopy at shorter and longer time intervals than guideline recommendations. Innovative methods are required to increase adherence to recommended timing. Aims 1) Explore current approaches used by endoscopist (EPs) and primary care providers (PCPs) to determine and communicate colonoscopy surveillance intervals (SI) between EPs, PCPs, and patients. 2) Obtain feedback for refining a decision tool to facilitate recommended SI. 3) Determine participant agreement of recommended SIs with current guidelines. Methods We conducted 4 focus groups (FGs); 3 FGs included EPs (n=12) and EPs in training (n=6); 1 FG included PCPs (n=4). FG questions explored use of guidelines, communication and follow-up practices with PCPs, EPs and patients, and challenges to follow-up. Participants were also asked for feedback about a prototype polyp SI decision tool that was developed using an algorithm synthesizing current Canadian Association of Gastroenterology, US Multisociety Task Force, and expert panel guidelines on SI. FGs were audio-recorded and transcribed for qualitative content analysis. FGs were analysed separately, then compared for similarities and differences. Finally, participants individually made interval recommendations for 7 common endoscopy scenarios. Responses were analyzed for agreement with the guidelines used to develop the decision tool. Results EPs reported not routinely referring to guidelines and were confident in their memory of the intervals although some reported checking occasionally. Many indicated they may use the tool in a web based or mobile application for more complicated scenarios, although some would never use it. Concerns regarding the tool included being up to date with research evidence and having required data to input on hand. PCPs reported the tool may be useful as a communication aid to involve patients in decision making. A challenge noted in all FGs was role confusion regarding communicating, tracking, and scheduling patients’ future procedures on time. Analysis of EPs (n=9) responses to the 7 scenarios showed that percent agreement with guidelines was low: 44% scored below 50% correct. Participants with the highest agreement scored 6/7; responses with the lowest agreement scored 0/7. The most common score was 3/7. Conclusions EPs appeared to be overconfident in their recommendations, but many were open to trying a website or mobile application decision tool to make evidence-based colonoscopy SI recommendations. Understanding, among PCPs and EPs, regarding responsibility for communicating results and scheduling follow-up surveillance for patients was inconsistent. Participant feedback informed development of a mobile application that is currently being pilot tested. Funding Agencies Research Manitoba

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)0.069
metaresearch head score (Gemma)0.093
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.367

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0690.093
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.002
Science and technology studies0.0030.002
Scholarly communication0.0020.003
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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 designQualitative
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

Citations0
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the Canadian Association of Gastroenterology→Same topicColorectal Cancer Screening and Detection→French-language works237,207→