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Asthma Detection Research Based on Voice Signal Processing and Machine Learning

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Enhancing nursing practice by utilizing voice recognition for direct documentation.

Jason Fratzke¹, Sharon Tucker, Heidi Shedenhelm

¹Author Affiliations: Nurse Administrator (Mr Fratzke), Mayo Clinic, Rochester, Minnesota; Director of Nursing Research and Evidence-Based (Dr Tucker), Department of Nursing Services and Patient Care, University of Iowa Hospitals and Clinics, Iowa City, Iowa; Nurse Manager (Ms Shedenhelm), Mayo Clinic, Rochester, Minnesota; Director (Ms Arnold), Multidisciplinary Simulation Center, Cleveland Clinic Abu Dhabi; Information Technology Specialist (Mr Belda), Mayo Clinic, Rochester, Minnesota; Chief Technology Officer (Mr Petera), VoiceViewer Technologies, Inc, Casper, Wyoming.

The Journal of Nursing Administration

|January 24, 2014

Summary

This summary is machine-generated.

Voice recognition (VR) software shows potential for documenting nursing care but faces challenges. Nurse acceptance depends on addressing technical issues, providing training, and minimizing workflow interference for successful adoption.

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Area of Science:

Nursing Informatics
Human-Computer Interaction
Health Information Technology

Background:

Nursing time is valuable and often consumed by documentation.
Innovative strategies are needed to preserve nursing time for direct patient care.
Electronic health records (EHRs) require efficient documentation methods.

Purpose of the Study:

To examine the utility, feasibility, and acceptability of voice recognition (VR) software for EHR documentation in a simulated nursing environment.
To identify barriers and facilitators for the adoption of VR technology in nursing practice.

Main Methods:

A phase 1 trial involving 5 iterative experiments.
Incorporated observations and feedback from nurse participants.
Focused on refining speech detection, technology, software, and processes.

Main Results:

Utility ratings for VR software improved over the study period.
Interference with nursing care remained a significant concern.
Nurses preferred traditional keyboard entry due to software/technical issues and cultural shifts.

Conclusions:

Voice recognition software has potential but requires significant refinement for nursing practice.
Successful adoption hinges on nurse receptiveness, perceived benefits, adequate training, and minimizing usability barriers.
Addressing technical and workflow integration challenges is crucial for VR technology in nursing.