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Related Experiment Video

Updated: Jan 22, 2026

Use of a Low-flow Digital Anesthesia System for Mice and Rats

Use of a Low-flow Digital Anesthesia System for Mice and Rats

Published on: September 7, 2016

The digital scribe.

Enrico Coiera¹, Baki Kocaballi¹, John Halamka²

¹1Australian Institute of Health Innovation, Macquarie University, Level 6 75 Talavera Rd, Sydney, NSW 2109 Australia.

NPJ Digital Medicine

|July 16, 2019

Summary

This summary is machine-generated.

Digital scribes, powered by AI, aim to automate clinical documentation, improving electronic health record efficiency. These systems will evolve through human-led, mixed-initiative, and computer-led stages, offering future diagnostic and therapeutic support.

Keywords:

Health services Translational research

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Last Updated: Jan 22, 2026

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Area of Science:

Medical Informatics
Artificial Intelligence in Medicine
Clinical Documentation

Background:

Current electronic health records (EHRs) present inefficiencies and contribute to low clinician satisfaction.
Manual clinical documentation is time-consuming and prone to errors.

Purpose of the Study:

To explore the evolution and potential impact of digital scribes (intelligent documentation support systems) on clinical workflows.
To identify the stages of digital scribe development and their implications for healthcare.

Main Methods:

Review of current trends in speech recognition, natural language processing, and artificial intelligence for clinical documentation.
Conceptual framework outlining three developmental stages of digital scribes: human-led, mixed-initiative, and computer-led.

Main Results:

Digital scribes are evolving from clinician support tools to autonomous documentation systems.
Intelligent clinical environments can integrate automated data capture and AI interpretation.
Potential risks include automation bias and a shift towards comprehensive encounter recording.

Conclusions:

Digital scribes promise to enhance EHR efficiency and clinician satisfaction.
These systems represent a pathway for advanced AI-driven clinical decision support.
Careful consideration of patient safety and workflow integration is crucial for successful implementation.