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

Jamie Catlow; Linda Sharp; Adetayo Kasim; Liya Lu; Matthew Brookes; Tom Lee; Stephen McCarthy; Joanne Gray; Falko Sniehotta; Jill Deane; Matt Rutter

doi:10.1055/a-1261-3151

Endoscopy International Open, Inhaltsverzeichnis

CC BY-NC-ND 4.0 · Endosc Int Open 2020; 08(11): E1545-E1552
DOI: 10.1055/a-1261-3151

Original article

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

Jamie Catlow

¹Newcastle University Centre for Cancer – Populations Health Sciences Institute, Newcastle Upon Tyne, United Kingdom of Great Britain and Northern Ireland

²North Tees and Hartlepool NHL Foundation Trust – Gastroenterology, Stockton on Tees, United Kingdom of Great Britain and Northern Ireland

,

Linda Sharp

¹Newcastle University Centre for Cancer – Populations Health Sciences Institute, Newcastle Upon Tyne, United Kingdom of Great Britain and Northern Ireland

,

Adetayo Kasim

³Durham University, Wolfson Research Institute of Health and Wellbeing, Newcastle Upon Tyne, United Kingdom of Great Britain and Northern Ireland

,

Liya Lu

¹Newcastle University Centre for Cancer – Populations Health Sciences Institute, Newcastle Upon Tyne, United Kingdom of Great Britain and Northern Ireland

,

Matthew Brookes

⁴Royal Wolverhampton Hospitals NHS Trust, Gastroenterology, Wolverhamptonm

,

Tom Lee

⁵Northumbria Healthcare NHS Foundation Trust, Gastroenterology, North Shields, Tyne and Wear, United Kingdom of Great Britain and Northern Ireland

,

Stephen McCarthy

⁶Northumbria University, Department of Nursing, Midwifery & Health, Newcastle Upon Tyne, United Kingdom of Great Britain and Northern Ireland

,

Joanne Gray

⁶Northumbria University, Department of Nursing, Midwifery & Health, Newcastle Upon Tyne, United Kingdom of Great Britain and Northern Ireland

,

Falko Sniehotta

⁷Newcastle University, Population and Health Sciences Institute, Newcastle Upon Tyne, Tyne and Wear, United Kingdom of Great Britain and Northern Ireland

,

Jill Deane

²North Tees and Hartlepool NHL Foundation Trust – Gastroenterology, Stockton on Tees, United Kingdom of Great Britain and Northern Ireland

,

Matt Rutter

²North Tees and Hartlepool NHL Foundation Trust – Gastroenterology, Stockton on Tees, United Kingdom of Great Britain and Northern Ireland

⁸Newcastle University, Centre for Cancer, Newcastle Upon Tyne, Tyne and Wear, United Kingdom of Great Britain and Northern Ireland

› Institutsangaben

Abstract

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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Referenzen

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