INTRODUCTION: Speech recognition technology (SRT) recognises an individual's spoken word signals through a microphone and subsequently processes the user's words into digital text by means of a computer. SRT remains well established and continues to grow in popularity among the various health disciplines. Many studies have been done to examine the effects of SRT on nursing documentation, however, no previous systematic review (SR) on the effects of SRT on accuracy and efficiency of nursing documentation was identified. AIMS AND METHODS: To systematically review the impact of speech recognition technology on the accuracy and efficiency of clinical nursing documentation. A SR was conducted that measures the accuracy and efficiency (time to complete documentation) of SRT on nursing documentation. An extensive search of the literature included Web of Science, CINAHL via EBSCO host, Cochrane Library, Embase, MEDLINE and Google Scholar. The PRISMA checklist screened eligible papers. The quality of each paper was critically appraised, data extracted and analysed/synthesised. RESULTS: A total of 10 studies were included. Various devices and systems have been used to examine the accuracy, efficiency and impact of SRT on nursing documentation. A positive impact of SRT with significant advances in accuracy/productivity of nursing documentation at the point of care was found. However, a substantial degree of initial costing, training requirements and studied interface modification to individual healthcare units are needful in incorporating SRT systems. CONCLUSIONS: Speech recognition technology when applied to nursing documentation could open up a promising new interface for data entry from the point of care, though the full potential of the technology has not been explored. RELEVANCE TO CLINICAL PRACTICE: The compatibility/effectiveness of SRT with existing computer systems remains understudied. SRT training, prompt on-site technical support, maintenance and upgrades cannot be underestimated towards achieving high-level accuracy and efficiency (time to complete documentation) with SRT.
INTRODUCTION: Speech recognition technology (SRT) recognises an individual's spoken word signals through a microphone and subsequently processes the user's words into digital text by means of a computer. SRT remains well established and continues to grow in popularity among the various health disciplines. Many studies have been done to examine the effects of SRT on nursing documentation, however, no previous systematic review (SR) on the effects of SRT on accuracy and efficiency of nursing documentation was identified. AIMS AND METHODS: To systematically review the impact of speech recognition technology on the accuracy and efficiency of clinical nursing documentation. A SR was conducted that measures the accuracy and efficiency (time to complete documentation) of SRT on nursing documentation. An extensive search of the literature included Web of Science, CINAHL via EBSCO host, Cochrane Library, Embase, MEDLINE and Google Scholar. The PRISMA checklist screened eligible papers. The quality of each paper was critically appraised, data extracted and analysed/synthesised. RESULTS: A total of 10 studies were included. Various devices and systems have been used to examine the accuracy, efficiency and impact of SRT on nursing documentation. A positive impact of SRT with significant advances in accuracy/productivity of nursing documentation at the point of care was found. However, a substantial degree of initial costing, training requirements and studied interface modification to individual healthcare units are needful in incorporating SRT systems. CONCLUSIONS: Speech recognition technology when applied to nursing documentation could open up a promising new interface for data entry from the point of care, though the full potential of the technology has not been explored. RELEVANCE TO CLINICAL PRACTICE: The compatibility/effectiveness of SRT with existing computer systems remains understudied. SRT training, prompt on-site technical support, maintenance and upgrades cannot be underestimated towards achieving high-level accuracy and efficiency (time to complete documentation) with SRT.
Authors: Kyoung Hyup Nam; Da Young Kim; Dong Hwan Kim; Jung Hwan Lee; Jae Il Lee; Mi Jeong Kim; Joo Young Park; Jae Hyun Hwang; Sang Seok Yun; Byung Kwan Choi; Min Gyu Kim; In Ho Han Journal: Neurospine Date: 2022-05-12