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The National Endoscopy Database (NED) Automated Performance Reports to Improve Quality Outcomes Trial (APRIQOT) randomized controlled trial design

Background and study aims  Colonoscopists with low polyp detection have higher post colonoscopy colorectal cancer incidence and mortality rates. The United Kingdom’s National Endoscopy Database (NED) automatically captures patient level data in real time and provides endoscopy key performance indica...

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Autores principales: Catlow, Jamie, Sharp, Linda, Kasim, Adetayo, Lu, Liya, Brookes, Matthew, Lee, Tom, McCarthy, Stephen, Gray, Joanne, Sniehotta, Falko, Deane, Jill, Rutter, Matt
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Georg Thieme Verlag KG 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584467/
https://www.ncbi.nlm.nih.gov/pubmed/33140009
http://dx.doi.org/10.1055/a-1261-3151
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author Catlow, Jamie
Sharp, Linda
Kasim, Adetayo
Lu, Liya
Brookes, Matthew
Lee, Tom
McCarthy, Stephen
Gray, Joanne
Sniehotta, Falko
Deane, Jill
Rutter, Matt
author_facet Catlow, Jamie
Sharp, Linda
Kasim, Adetayo
Lu, Liya
Brookes, Matthew
Lee, Tom
McCarthy, Stephen
Gray, Joanne
Sniehotta, Falko
Deane, Jill
Rutter, Matt
author_sort Catlow, Jamie
collection PubMed
description Background and study aims  Colonoscopists with low polyp detection have higher post colonoscopy colorectal cancer incidence and mortality rates. The United Kingdom’s National Endoscopy Database (NED) automatically captures patient level data in real time and provides endoscopy key performance indicators (KPI) at a national, endoscopy center, and individual level. Using an electronic behavior change intervention, the primary objective of this study is to assess if automated feedback of endoscopist and endoscopy center-level optimal procedure-adjusted detection KPI (opadKPI) improves polyp detection performance. Methods  This multicenter, prospective, cluster-randomized controlled trial is randomizing NHS endoscopy centres to either intervention or control. The intervention is targeted at independent colonoscopists and each center’s endoscopy lead. The intervention reports are evidence-based from endoscopist qualitative interviews and informed by psychological theories of behavior. NED automatically creates monthly reports providing an opadKPI, using mean number of polyps, and an action plan. The primary outcome is opadKPI comparing endoscopists in intervention and control centers at 9 months. Secondary outcomes include other KPI and proximal detection measures at 9 and 12 months. A nested histological validation study will correlate opadKPI to adenoma detection rate at the center level. A cost-effectiveness and budget impact analysis will be undertaken. Conclusion  If the intervention is efficacious and cost-effective, we will showcase the potential of this learning health system, which can be implemented at local and national levels to improve colonoscopy quality, and demonstrate that an automated system that collects, analyses, and disseminates real-time clinical data can deliver evidence- and theory-informed feedback.
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spelling pubmed-75844672020-11-01 The National Endoscopy Database (NED) Automated Performance Reports to Improve Quality Outcomes Trial (APRIQOT) randomized controlled trial design Catlow, Jamie Sharp, Linda Kasim, Adetayo Lu, Liya Brookes, Matthew Lee, Tom McCarthy, Stephen Gray, Joanne Sniehotta, Falko Deane, Jill Rutter, Matt Endosc Int Open Background and study aims  Colonoscopists with low polyp detection have higher post colonoscopy colorectal cancer incidence and mortality rates. The United Kingdom’s National Endoscopy Database (NED) automatically captures patient level data in real time and provides endoscopy key performance indicators (KPI) at a national, endoscopy center, and individual level. Using an electronic behavior change intervention, the primary objective of this study is to assess if automated feedback of endoscopist and endoscopy center-level optimal procedure-adjusted detection KPI (opadKPI) improves polyp detection performance. Methods  This multicenter, prospective, cluster-randomized controlled trial is randomizing NHS endoscopy centres to either intervention or control. The intervention is targeted at independent colonoscopists and each center’s endoscopy lead. The intervention reports are evidence-based from endoscopist qualitative interviews and informed by psychological theories of behavior. NED automatically creates monthly reports providing an opadKPI, using mean number of polyps, and an action plan. The primary outcome is opadKPI comparing endoscopists in intervention and control centers at 9 months. Secondary outcomes include other KPI and proximal detection measures at 9 and 12 months. A nested histological validation study will correlate opadKPI to adenoma detection rate at the center level. A cost-effectiveness and budget impact analysis will be undertaken. Conclusion  If the intervention is efficacious and cost-effective, we will showcase the potential of this learning health system, which can be implemented at local and national levels to improve colonoscopy quality, and demonstrate that an automated system that collects, analyses, and disseminates real-time clinical data can deliver evidence- and theory-informed feedback. Georg Thieme Verlag KG 2020-11 2020-10-21 /pmc/articles/PMC7584467/ /pubmed/33140009 http://dx.doi.org/10.1055/a-1261-3151 Text en The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/) https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.
spellingShingle Catlow, Jamie
Sharp, Linda
Kasim, Adetayo
Lu, Liya
Brookes, Matthew
Lee, Tom
McCarthy, Stephen
Gray, Joanne
Sniehotta, Falko
Deane, Jill
Rutter, Matt
The National Endoscopy Database (NED) Automated Performance Reports to Improve Quality Outcomes Trial (APRIQOT) randomized controlled trial design
title The National Endoscopy Database (NED) Automated Performance Reports to Improve Quality Outcomes Trial (APRIQOT) randomized controlled trial design
title_full The National Endoscopy Database (NED) Automated Performance Reports to Improve Quality Outcomes Trial (APRIQOT) randomized controlled trial design
title_fullStr The National Endoscopy Database (NED) Automated Performance Reports to Improve Quality Outcomes Trial (APRIQOT) randomized controlled trial design
title_full_unstemmed The National Endoscopy Database (NED) Automated Performance Reports to Improve Quality Outcomes Trial (APRIQOT) randomized controlled trial design
title_short The National Endoscopy Database (NED) Automated Performance Reports to Improve Quality Outcomes Trial (APRIQOT) randomized controlled trial design
title_sort national endoscopy database (ned) automated performance reports to improve quality outcomes trial (apriqot) randomized controlled trial design
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584467/
https://www.ncbi.nlm.nih.gov/pubmed/33140009
http://dx.doi.org/10.1055/a-1261-3151
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