
Speech recognition for medical documentation: an analysis of time, cost efficiency and acceptance in a clinical setting
Author(s) -
Matthias Zuchowski,
Aydan Göller
Publication year - 2022
Publication title -
british journal of health care management/british journal of healthcare management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.155
H-Index - 15
eISSN - 1759-7382
pISSN - 1358-0574
DOI - 10.12968/bjhc.2021.0074
Subject(s) - documentation , software , computer science , word error rate , speech recognition , software documentation , health care , artificial intelligence , medicine , software development , software development process , economics , programming language , economic growth
Background/Aims Medical documentation is an important and unavoidable part of a health professional's working day. However, the time required for medical documentation is often viewed negatively, particularly by clinicians with heavy workloads. Digital speech recognition has become more prevalent and is being used to optimise working time. This study evaluated the time and cost savings associated with speech recognition technology, and its potential for improving healthcare processes.Methods Clinicians were directly observed while completing medical documentation. A total of 313 samples were collected, of which 163 used speech recognition and 150 used typing methods. The time taken to complete the medical form, the error rate and error correction time were recorded. A survey was also completed by 31 clinicians to gauge their level of acceptance of speech recognition software for medical documentation. Two-sample t-tests and Mann–Whitney U tests were performed to determine statistical trends and significance.Results On average, medical documentation using speech recognition software took just 5.11 minutes to complete the form, compared to 8.9 minutes typing, representing significant time savings. The error rate was also found to be lower for speech recognition software. However, 55% of clinicians surveyed stated that they would prefer to type their notes rather than use speech recognition software and perceived the error rate of this software to be higher than typing.Conclusions The results showed that there are both temporal and financial advantages of speech recognition technology over text input for medical documentation. However, this technology had low levels of acceptance among staff, which could have implications for the uptake of this method.