Improving ward round documentation using the Heidi Health application

Area of Science:

• Medical Informatics
• Artificial Intelligence in Healthcare
• Surgical Workflow Optimization

Background:

• Accurate and timely documentation is crucial for patient safety and care continuity in surgical settings.
• Resident doctors in busy surgical departments face documentation delays due to competing clinical priorities.
• This study addresses the need for efficient documentation solutions in high-demand surgical environments.

Purpose of the Study:

• To evaluate the effectiveness of an artificial intelligence (AI) transcription tool, Heidi, in reducing documentation time for surgical residents.
• To assess the impact of AI-assisted documentation on workflow efficiency and resident training in an ear, nose, and throat (ENT) department.

Main Methods:

• A quality improvement project was conducted in a tertiary center's ENT department.
• Baseline documentation times using conventional methods were recorded over 4 days.
• The Heidi AI tool was implemented to transcribe and format ward round discussions, with subsequent documentation times recorded over 4 days.

Main Results:

• The implementation of the Heidi AI tool resulted in a statistically significant reduction in documentation time.
• AI-assisted documentation proved more efficient than traditional methods.

Conclusions:

• AI tools can improve the timeliness of clinical records and reduce administrative burdens for resident doctors.
• Utilizing AI in documentation enhances workflow efficiency, patient flow, and provides greater opportunities for resident participation in patient care and education.