RSS-Feed abonnieren

DOI: 10.1055/a-2592-3338
Implementing endoscopy video recording in routine clinical practice: Strategies from three tertiary care centers
Gefördert durch: Bundesministerium für Bildung und Forschung 03ZU1210GA ,03ZU121HB

Abstract
Background and study aims
Endoscopy video recordings are valuable data for training and deploying artificial intelligence (AI) models. However, collecting these data is challenging and time-consuming, demanding new workflows and robust data management strategies.
Methods
Here, we outline the challenges associated with routinely recording endoscopy data in clinical practice and share experiences and solutions from three endoscopy centers in Germany and the United States.
Results
Each center uses a recording setup tailored to specific needs of that endoscopy unit. Common challenges include integrating with the hospital’s electronic health records, automating video recording, and addressing data privacy concerns. In all cases, having dedicated research staff to manage daily operations has proven essential for successful implementation.
Conclusions
By describing successful strategies, we aim to inspire gastroenterology divisions worldwide to adapt routine video recording for endoscopy procedures, thereby increasing the volume and diversity of datasets necessary for developing clinically impactful AI applications.
Publikationsverlauf
Eingereicht: 04. Dezember 2024
Angenommen nach Revision: 17. März 2025
Accepted Manuscript online:
22. April 2025
Artikel online veröffentlicht:
17. Juni 2025
© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/).
Georg Thieme Verlag KG
Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany
Jonas L. Steinhäuser, Tyler M. Berzin, Mark E. Geissler, Cornelius Weber, Nora Herzog, Maxime Le Floch, Stefan Brückner, Jochen Hampe, Sami Elamin, Joel Troya, Alexander Hann, Franz Brinkmann. Implementing endoscopy video recording in routine clinical practice: Strategies from three tertiary care centers. Endosc Int Open 2025; 13: a25923338.
DOI: 10.1055/a-2592-3338
-
References
- 1
Doutreligne M,
Degremont A,
Jachiet P-A.
et al.
Good practices for clinical data warehouse implementation: A case study in France.
PLOS Digit Health 2023; 2: e0000298
MissingFormLabel
- 2 Cho J, Lee K, Shin E et al. How much data is needed to train a medical image deep
learning system to achieve necessary high accuracy? 2015. https://arxiv.org/abs/1511.06348v2
MissingFormLabel
- 3
Uche-Anya EN,
Gerke S,
Berzin TM.
Video endoscopy as big data: Balancing privacy and progress in gastroenterology. Am
J Gastroenterol 2024; 119: 600
MissingFormLabel
- 4
Campbell RJ.
Change management in health care. Health Care Manag 2008; 27: 23
MissingFormLabel
- 5
Willner N,
Peled-Raz M,
Shteinberg D.
et al.
Digital recording and documentation of endoscopic procedures: Do patients and doctors
think alike?. Can J Gastroenterol Hepatol 2016; 2016: e2493470
MissingFormLabel
- 6
Harris PA,
Taylor R,
Thielke R.
et al.
Research electronic data capture (REDCap) – A metadata-driven methodology and
workflow process for providing translational research informatics support. J Biomed
Inform 2009; 42: 377-381
MissingFormLabel
- 7
Geissler M,
Jha D,
Elamin S.
et al.
The Boston ERCP Dataset: A video dataset for advanced endoscopy. Gastrointest Endosc
2024; 99: AB5-AB6
MissingFormLabel
- 8
Lux TJ,
Banck M,
Saßmannshausen Z.
et al.
Pilot study of a new freely available computer-aided polyp detection system in clinical
practice. Int J Colorectal Dis 2022; 37: 1349-1354
MissingFormLabel
- 9
Brand M,
Troya J,
Krenzer A.
et al.
Development and evaluation of a deep learning model to improve the usability of polyp
detection systems during interventions. United Eur Gastroenterol J 2022; 10: 477-484
MissingFormLabel
- 10
Lux TJ,
Saßmannshausen Z,
Kafetzis I.
et al.
Assisted documentation as a new focus for artificial intelligence in endoscopy: the
precedent of reliable withdrawal time and image reporting. Endoscopy 2023; 55: 1118-1123
MissingFormLabel
- 11
Henken KR,
Jansen FW,
Klein J.
et al.
Implications of the law on video recording in clinical practice. Surg Endosc 2012;
26: 2909-2916
MissingFormLabel
- 12
Turnbull AMJ,
Emsley ES.
Video recording of ophthalmic surgery--ethical and legal considerations. Surv Ophthalmol
2014; 59: 553-558
MissingFormLabel
- 13
Zhang J,
Symons J,
Agapow P.
et al.
Best practices in the real-world data life cycle. PLOS Digit Health 2022; 1: e0000003
MissingFormLabel
- 14
Bommasani R,
Hudson DA,
Adeli E.
et al.
On the opportunities and risks of foundation models. 2022
MissingFormLabel