Capturing patient information at nursing shift changes: methodological evaluation of speech recognition and information extraction

Suominen, Hanna; Johnson, Maree; Zhou, Liyuan; Sanchez, Paula; Sirel, Raul; Basilakis, Jim; Hanlen, Leif; Estival, Dominique; Dawson, Linda; Kelly, Barbara F.

doi:10.1136/amiajnl-2014-002868

Cited by 22 publications

(45 citation statements)

References 36 publications

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“…As depicted in the combined search PRISMA flow diagram (Figure 1), the search results identified 10 studies, which were deemed appropriate for inclusion in this systematic review. Following the rigorous quality appraisal, six studies met with the validity criterion (Alapetite, 2008; Fratzke et al, 2014; NSLHD, 2012; Saxena et al, 2018; Suominen et al, 2014; Suominen, Zhou, Hanlen, & Ferraro, 2015). Despite poor validity, studies by Awan et al, (2018), Chang, Sheng, Sang, and Wang (2008), Carter‐Wesley (2009), and Marukami et al, (2010) were included in critical appraisal in this review for their potential to yield valuable insight towards the primary and secondary outcomes.…”

Section: Resultsmentioning

confidence: 99%

“…Six studies scored >75% validity, namely Alapetite (2008), Fratzke et al (2014), NSLHD (2012), Saxena et al (2018), Suominen et al (2015), and Suominen et al (2014). Therefore, conclusions from these studies seemed generalisable.…”

Section: Resultsmentioning

confidence: 99%

“…Six studies were conducted in simulated clinical settings (Alapetite, 2008; Awan et al, 2018; Carter‐Wesley, 2009; Fratzke et al, 2014; Suominen et al, 2014, 2015). Notably, Alapetite (2007) conducted their study within a simulated hospital operating room environment, while the other six studies were conducted in simulated medical settings.…”

Section: Resultsmentioning

confidence: 99%

“…Saxena et al (2018) do not describe the exact number of nurses; however, they state that 18% of the 108 clinicians who participated in both pre‐ and postimplementation surveys constituted of nurse practitioners. In total, nine studies described 192 nurses and 129 non‐nursing participants using SRT for clinical documentation (Alapetite, 2008; Awan et al, 2018; Carter‐Wesley, 2009; Chang et al, 2008; Fratzke et al, 2014; Marukami et al, 2010; NSLHD, 2012; Suominen et al, 2014, 2015). Five studies were conducted exclusively on nursing personnel (Awan et al, 2018; Carter‐Wesley, 2009; Chang et al, 2008; Fratzke et al, 2014; Suominen et al, 2014) (see Table 3).…”

Section: Resultsmentioning

confidence: 99%

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The impact of implementing speech recognition technology on the accuracy and efficiency (time to complete) clinical documentation by nurses: A systematic review

Joseph

Moore

Patton

et al. 2020

Journal of Clinical Nursing

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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.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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The impact of implementing speech recognition technology on the accuracy and efficiency (time to complete) clinical documentation by nurses: A systematic review

Joseph

Moore

Patton

et al. 2020

Journal of Clinical Nursing

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“…1 This paper will explore the challenges and opportunities for implementing this intervention specifically within midwifery practice.…”

Section: Introductionmentioning

confidence: 99%

Digital voice recorders – A conceptual intervention to facilitate contemporaneous record keeping in midwifery practice

Pezaro

Lilley

2015

Women and Birth

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Benefits, barriers, and facilitators of using speech recognition technology in nursing documentation and reporting: A cross‐sectional study

Dinari,

Bahaadinbeigy,

Bassiri

et al. 2023

Health Science Reports

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Background and Aim: Nursing reports are necessary for clinical communication and provide an accurate reflection of nursing assessments, care provided, changes in clinical status, and patient-related information to support the multidisciplinary team to provide individualized care. Nurses always face challenges in recording and documenting nursing reports. Speech recognition systems (SRS), as one of the documentation technologies, can play a potential role in recording medical reports. Therefore, this study seeks to identify the barriers, benefits, and facilitators of utilizing speech recognition technology in nursing reports. Materials and Methods: This cross-sectional was conducted through a researchermade questionnaire in 2022. Invitations were sent to 200 ICU nurses working in the three educational hospitals of Imam Reza (AS), Qaem and Imam Zaman in Mashhad city (Iran), 125 of whom accepted our invitation. Finally, 73 nurses included the study based on inclusion and exclusion criteria. Data analysis was performed using SPSS 22.0.Results: According to the nurses, "paperwork reduction" (3.96, ±1.96), "performance improvement" (3.96, ±0.93), and "cost reduction" (3.95, ±1.07) were the most common benefits of using the SRS. "Lack of specialized, technical, and experienced staff to teach nurses how to work with speech recognition systems" (3.59, ±1.18), "insufficient training of nurses" (3.59, ±1.11), and "need to edit and control quality and correct documents" (3.59, ±1.03) were the most common barriers to using SRS.As well as "ability to fully review documentation processes" (3.62, ±1.13), "creation of integrated data in record documentation" (3.58, ±1.15), "possibility of error correction for nurses" (3.51, ±1.16) were the most common facilitators. There was no significant relationship between nurses' demographic information and the benefits, barriers, and facilitators.Conclusions: By providing information on the benefits, barriers, and facilitators of using this technology, hospital managers, nursing managers, and information

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Capturing patient information at nursing shift changes: methodological evaluation of speech recognition and information extraction

Abstract: The benefits of this automation include storing all information; making the drafts available and accessible almost instantly to everyone with authorized access; and avoiding information loss, delays, and misinterpretations inherent to using a ward clerk or transcription services.

Cited by 22 publications

References 36 publications

The impact of implementing speech recognition technology on the accuracy and efficiency (time to complete) clinical documentation by nurses: A systematic review

The impact of implementing speech recognition technology on the accuracy and efficiency (time to complete) clinical documentation by nurses: A systematic review

Digital voice recorders – A conceptual intervention to facilitate contemporaneous record keeping in midwifery practice

Benefits, barriers, and facilitators of using speech recognition technology in nursing documentation and reporting: A cross‐sectional study

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