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Speech Recognition Technology for Nursing Charting: A Literature Review
Sally Newton-Mason1,2, Clement Chui1, Saima Hirani2
1Vancouver Coastal Health Authority, Vancouver, BC, Canada.
Studies in Health Technology and Informatics
|July 25, 2024
Summary
Speech Recognition Technology (SRT) can improve nursing documentation efficiency in electronic health records (EHR) by up to 15%. However, integration challenges require further research for optimal clinical implementation.
Area of Science:
- Health Informatics
- Medical Technology
- Nursing Informatics
Background:
- Nursing documentation is crucial for patient care and record-keeping.
- Electronic Health Records (EHR) are standard in modern healthcare.
- Efficient documentation is essential for nurses' workflow and patient safety.
Purpose of the Study:
- To review the impact of Speech Recognition Technology (SRT) on nursing documentation within EHR systems.
- To assess SRT's effects on documentation time, accuracy, and user satisfaction.
- To identify challenges and future directions for SRT implementation in nursing.
Main Methods:
- Literature review of studies from PubMed, CINAHL, and Google Scholar.
- Inclusion criteria applied to 156 identified studies, with seven selected for analysis.
- Analysis focused on reported impacts of SRT on documentation metrics.
Main Results:
- Speech Recognition Technology (SRT) can reduce nursing documentation time by up to 15%, especially when combined with artificial intelligence.
- Studies indicate potential improvements in documentation efficiency.
- User satisfaction and accuracy are key factors influenced by SRT integration.
Conclusions:
- SRT shows promise for enhancing nursing documentation efficiency in EHRs.
- Implementation challenges in clinical settings and EHR workflows need to be addressed.
- Future research should focus on conversational SRT and seamless EHR integration for nursing assessments.
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