Improving ward round documentation using the Heidi Health application

Journal article

Introduction: Accurate and timely documentation during surgical ward rounds is critical for ensuring patient safety, effective multidisciplinary communication and continuity of care. In high-demand surgical settings, resident doctors often experience delays in completing documentation due to competing clinical priorities. This quality improvement project aimed to assess whether an artificial intelligence (AI) transcription tool, Heidi, could reduce documentation time in a busy ear, nose and throat (ENT) department within a tertiary centre. Methods: Baseline data on time taken to complete conventional ward round documentation were collected over a 4-day period. The Heidi AI tool was then implemented to transcribe real-time discussions during ward rounds and automatically format the information using a structured template adapted from the SHINE Surgical Ward Round Toolkit. Documentation times using the AI system were recorded over a subsequent 4-day period. Results: The implementation of Heidi led to a statistically significant reduction in documentation time compared with conventional methods. Conclusions: Using AI tools can not only improve timeliness of clinical records but also free resident doctors from scribing duties, allowing greater participation in patient care and enhancing educational opportunities. This intervention demonstrated the potential of AI-assisted documentation to improve workflow efficiency and patient flow while supporting resident doctor training and reducing administrative burden in a surgical setting.

Authors: Qamar, A; Kelly, M; Maweni, R; Abdul-Hamid, A

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: BMJ Publishing Group
• Journal: BMJ Open Quality
• Volume: 15
• Issue: 1
• Pages: e003910
• Article number: bmjoq-2025-003910
• Publication date: 2026-03-01
• Acceptance date: 2026-02-24
• DOI: 10.1136/bmjoq-2025-003910
• EISSN: 2399-6641
• ISSN: 2399-6641
• Language: English
• Keywords: Information technology; Electronic Health Records; Artificial Intelligence