A Review on the Quality of Colonoscopy Reporting

Sharma, Robyn

doi:10.1155/2016/9423142

Cited by 14 publications

(8 citation statements)

References 52 publications

(69 reference statements)

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“…Currently, no standard criteria or definition exists for qualitative terms such as “adequate”, “inadequate”, “excellent”, “good”, “fair”, or “poor”; in some scales, adequate cleansing is defined as a composite of “good” and “excellent”[ 11 , 26 ]. Physician reporting on quality of bowel preparation, as well as overall colonoscopy quality, is highly inconsistent and often missing important elements, which may be attributable to lack of clear and consistent quality assessment standards[ 27 ]. Therefore, this review was conducted to summarize and discuss currently available bowel preparation quality scales and highlight the benefits of using a reliable and validated scale in both clinical practice and clinical trials of bowel preparation agents.…”

Section: Introductionmentioning

confidence: 99%

Bowel preparation quality scales for colonoscopy

Kastenberg

Bertiger

Brogadir

2018

WJG

157

144

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Colorectal cancer (CRC) is the third most common cancer and second leading cause of cancer-related death in the United States. Colonoscopy is widely preferred for CRC screening and is the most commonly used method in the United States. Adequate bowel preparation is essential for successful colonoscopy CRC screening. However, up to one-quarter of colonoscopies are associated with inadequate bowel preparation, which may result in reduced polyp and adenoma detection rates, unsuccessful screens, and an increased likelihood of repeat procedure. In addition, standardized criteria and assessment scales for bowel preparation quality are lacking. While several bowel preparation quality scales are referred to in the literature, these differ greatly in grading methodology and categorization criteria. Published reliability and validity data are available for five bowel preparation quality assessment scales, which vary in several key attributes. However, clinicians and researchers continue to use a variety of bowel preparation quality measures, including nonvalidated scales, leading to potential confusion and difficulty when comparing quality results among clinicians and across clinical trials. Optimal clinical criteria for bowel preparation quality remain controversial. The use of validated bowel preparation quality scales with stringent but simple scoring criteria would help clarify clinical trial data as well as the performance of colonoscopy in clinical practice related to quality measurements.

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Section: Introductionmentioning

confidence: 99%

Bowel preparation quality scales for colonoscopy

Kastenberg

Bertiger

Brogadir

2018

WJG

157

144

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“…The reporting of quality measures is subjective and operator-dependent [23]. These studies and observations highlight the multitude of factors that can impact the effectiveness and quality of a colonoscopy.…”

Section: Discussionmentioning

confidence: 93%

Software Analysis of Colonoscopy Videos Enhances Teaching and Quality Metrics

Rajan¹,

Srinath²,

Bong³

et al. 2022

Cureus

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Machine learning algorithms were hypothesized as being able to predict the quality of colonoscopy luminal images. This is to enhance training and quality indicators in endoscopy. MethodsA separate study involving a randomized controlled trial of capped vs. un-capped colonoscopies provided the colonoscopy videos for this study. Videos were analyzed with an algorithm devised by the Australian Institute for Machine Learning. The image analysis validated focus measure, steerable filters-based metrics (SFIL), was used to assess luminal visualization quality and was compared with two independent clinician assessments (C1 and C2). Goodman and Kruskal's gamma (G) measure was used to assess rank correlation data using IBM SPSS Statistics for Windows, version 25.0 (IBM Corp., Armonk, NY). ResultsA total of 500 random colonoscopy video clips were extracted and analyzed, 88 being excluded. SFIL scores matched with C1 in 45% and C2 in 42% of cases, respectively. There was a significant correlation between SFIL and C1 (G = 0.644, p < 0.005) and SFIL and C2 (G = 0.734, p < 0.005). ConclusionThis study demonstrates that machine learning algorithms can recognize the quality of luminal visualization during colonoscopy. We intend to apply this in the future to enhance colonoscopy training and as a metric for quality assessment.

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“…Deficiencies in colonoscopy reports has been noted in several studies. [22] All of the polyp and polypectomy details required to be collected about the index colonoscopy are consistent with elements recommended by the Quality Assurance Task Group of the National Colorectal Cancer Roundtable to be part of a standard colonoscopy report. [23] Therefore, a high quality colonoscopy report should contain all information required to apply the criteria.…”

Section: Plos Onementioning

confidence: 99%

Development of a definition and rules for causal attribution of post-colonoscopy bleeding

et al. 2020

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Background Post-colonoscopy bleeding (PCB) is an important colonoscopy quality indicator that is recommended to be routinely collected by colorectal cancer screening programs and endoscopy quality improvement programs. We created a standardized and reliable definition of PCB and set of rules for attributing the relatedness of PCB to a colonoscopy. Methods PCB events were identified from colonoscopies performed at the Forzani & MacPhail Colon Cancer Screening Centre. Existing definitions and relatedness rules for PCB were reviewed by the authors and a draft definition and set of rules was created. The definition and rules were revised after initial testing was performed using a set of 15 bleeding events. Information available for each event included the original endoscopy report and data abstracted from the emergency or inpatient record by a trained research assistant. A validation set of 32 bleeding events were then reviewed to assess their interrater reliability by having three endoscopists and one research assistant complete independent reviews and three endoscopists complete a consensus review. The Kappa statistic was used to measure interrater reliability. Results The panel classified 28 of 32 events as meeting the definition of PCB and rated 7, 8 and 6 events as definitely, probably and possibly related to the colonoscopy, respectively. The Kappa for the definition of PCB for the three independent reviews was 0.82 (substantial agreement). The Kappa for the attribution of the PCB to the colonoscopy by the three endosocopists was 0.74 (substantial agreement). The research assistant had a high agreement with the panel for both the definition (100% agreement) and application of the causal criteria (kappa 0.95).

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A Review on the Quality of Colonoscopy Reporting

Cited by 14 publications

References 52 publications

Bowel preparation quality scales for colonoscopy

Bowel preparation quality scales for colonoscopy

Software Analysis of Colonoscopy Videos Enhances Teaching and Quality Metrics

Development of a definition and rules for causal attribution of post-colonoscopy bleeding

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