A63 COLONOSCOPY QUALITY IN COLORECTAL CANCER SCREENING: HOW BEST TO CAPTURE THE DATA?
Notice bibliographique
Résumé
Colonoscopy quality indicators have been developed to ensure performance of accurate and safe colonoscopies as part of screening for colorectal cancer. Measurement of these indicators requires timely recording of data during the colonoscopy procedure to allow for subsequent calculation of indicator rates. While various data capture methods currently exist, ranging from paper-based to electronic record systems, there is very little guidance available regarding the necessary requirements for accurate data entry into these systems. In this outcomes project, our objectives were to assess both the uptake and barriers to implementation of quality data capture using a standardized bedside data collection form. A pilot project was conducted in the Coaldale Screening Centre in southern Alberta over a 6-month period in 2016. This centre is a stand-alone endoscopy unit solely dedicated to performing colonoscopies for colorectal cancer screening. A standardized data collection form was developed to capture key quality indicators of interest as well as information regarding colonic polyps removed. The endoscopy theatre nurse completed the form during each procedure. Data from the completed forms were then entered into a centralized electronic reporting system (Synoptec). Site visits, surveys and interviews were carried out to determine satisfaction with the method and to identify barriers to broader implementation of this quality initiative in other units. A manual audit was performed to determine the accuracy of data collection and entry. During the study timeframe, 660 cases were entered into Synoptec and available for analysis. Feedback from the site visits, interviews and user surveys demonstrated the following concerns a) disparity between the endoscopists and nursing record regarding confirmation of landmarks b) concern over duplicate data entry and, c) extra time required to collect quality data resulting in delayed theatre turnover. An audit was completed on 10% (n=67) of the total cases to determine the level of agreement between the data collected on the standardized form (nurse) to the colonoscopy report (endoscopist). Findings indicated data were comparable for all quality indicators with the exception of withdrawal time; 75% case disparity. 54% of cases had a variance in withdrawal time within 1 minute and 30% were more than 2 minutes. Institution of a colonoscopy quality program requires a culture of quality in the endoscopy unit that facilitates clear and purposeful communication between colonoscopist and theatre nurse, avoids duplication of data entry and builds quality data collection into the main work flow of the endoscopy unit. None
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,233 | 0,445 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,004 | 0,003 |
| Bibliométrie | 0,009 | 0,018 |
| Études des sciences et des technologies | 0,004 | 0,007 |
| Communication savante | 0,019 | 0,022 |
| Science ouverte | 0,005 | 0,009 |
| Intégrité de la recherche | 0,004 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».