# Implementing endoscopy video recording in routine clinical practice: Strategies from three tertiary care centers

**Authors:** 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

PMC · DOI: 10.1055/a-2592-3338 · Endoscopy International Open · 2025-06-17

## TL;DR

This paper discusses how three hospitals successfully implemented video recording during endoscopy procedures to support AI development.

## Contribution

The paper provides practical strategies and solutions for implementing endoscopy video recording in clinical settings.

## Key findings

- Each center customized recording setups to fit their specific endoscopy unit needs.
- Common challenges included integrating with electronic health records and managing data privacy.
- Dedicated research staff were crucial for managing operations and ensuring successful implementation.

## Abstract

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.

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.

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.

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.

## Full-text entities

- **Diseases:** bleeding (MESH:D006470), AI (MESH:C538142)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12223936/full.md

## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12223936/full.md

## References

14 references — full list in the complete paper: https://tomesphere.com/paper/PMC12223936/full.md

---
Source: https://tomesphere.com/paper/PMC12223936