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Record W4212782205 · doi:10.1093/jcag/gwab049.099

A100 A PROVINCIAL APPROACH TO ASSESSING ENDOSCOPY PATIENT EXPERIENCE ENHANCES SITE PARTICIPATION AND CANADA-GLOBAL RATING SCALE COMPLIANCE

2022· article· en· W4212782205 on OpenAlexaffabout
C Oilund, Louise Morrin, B Moysey, Susan Jelinski, Joanne Snider, Fox E. Underwood, C Spankie, N Nemecek, M Greenaway

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2022
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsUniversity of CalgaryAlberta HealthAlberta Health Services
Fundersnot available
KeywordsUnit (ring theory)MedicineQuality managementScale (ratio)Rating scaleEndoscopyQuality (philosophy)Patient satisfactionMedical educationFamily medicineBusinessPsychologyNursingSurgeryMarketingGeographyService (business)

Abstract

fetched live from OpenAlex

Abstract Background The Canada-Global Rating Scale (C-GRS) is a web-based, patient centered endoscopy quality improvement tool. It assesses the quality of services a unit provides in two dimensions: clinical quality and patient experience. Endoscopy units submit results to the Canadian Association of Gastroenterology twice a year. In Alberta, units receive an A, B, C or D grade for each of the 12 C-GRS Items and a C-GRS score. The C-GRS promotes that patient feedback is sought annually. Patient feedback is important because it informs practice improvement opportunities. However, survey creation, distribution, analysis and reporting can be time consuming and costly for an endoscopy unit and is a potential barrier to participation. Aims The purpose of this quality improvement project is to demonstrate how a provincial infrastructure, which includes coordination, management and reporting of an endoscopy patient satisfaction survey, can enhance provincial endoscopy unit survey participation and facilitate C-GRS compliance. Methods The Digestive Health Strategic Clinical Network (DHSCN), the Alberta Colorectal Cancer Screening Program and Primary Data Support (PDS) collaborated on the Provincial Endoscopy Patient Experience Survey (PEPES) in 2019. An existing paper survey was adapted to meet the needs of the 50 endoscopy units in AB with the addition of an electronic version. Education about the PEPES process was provided via a webinar and site visits. Each unit was responsible for distribution of the surveys to their patients. PDS coordinated the paper survey process and the DHSCN managed the electronic survey submissions. Paper survey results were merged with electronic PEPES data. A summary report was provided to units and shared with each AHS Zone Endoscopy Executive Leadership Team. Results Provincially coordinated implementation of the PEPES fosters compliance with C-GRS criteria. Participating endoscopy units were able to achieve at minimum 9 C-GRS descriptors and improve their C-GRS score in the following 7 of the 12 C-GRS Items: consent, comfort, equality, booking, privacy, aftercare and feedback. Initial enrollment in the PEPES increased with the onset of provincial coordination (Figure 1). However, subsequent participation was negatively impacted by COVID-19 as many endoscopy units in AB were required to decrease their capacity and redeploy staff. Conclusions A provincially coordinated approach to the management of an endoscopy patient experience survey is an effective way to enhance site participation and improve C-GRS scores. Units can focus on actioning survey results, rather than the burden of survey administration. Future work includes comparison of results across sites allowing for potential provincial equity issues to be addressed. Funding Agencies None

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)0.019
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.800

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.058
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.067
GPT teacher head0.383
Teacher spread0.315 · 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 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".

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Citations0
Published2022
Admission routes2
Has abstractyes

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