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 researcher-made 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 technology managers of healthcare centers can make more informed decisions in selecting and implementing SRS for nursing report documentation. This will help to avoid potential challenges that may reduce the efficiency, effectiveness, and productivity of the systems.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10259462PMC
http://dx.doi.org/10.1002/hsr2.1330DOI Listing

Publication Analysis

Top Keywords

speech recognition
16
benefits barriers
12
barriers facilitators
8
recognition technology
8
technology nursing
8
nursing reports
8
nursing
7
benefits
5
nurses
5
facilitators
4

Similar Publications

Objective: Measuring listening effort using pupillometry is challenging in cochlear implant (CI) users. We assess three validated speech tests (Matrix, LIST, and DIN) to identify the optimal speech material for measuring peak-pupil-dilation (PPD) in CI users as a function of signal-to-noise ratio (SNR).

Design: Speech tests were administered in quiet and two noisy conditions, namely at the speech recognition threshold (0 dB re SRT), i.

View Article and Find Full Text PDF

Tibetan-Chinese speech-to-speech translation based on discrete units.

Sci Rep

January 2025

Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing, 100081, China.

Speech-to-speech translation (S2ST) has evolved from cascade systems which integrate Automatic Speech Recognition (ASR), Machine Translation (MT), and Text-to-Speech (TTS), to end-to-end models. This evolution has been driven by advancements in model performance and the expansion of cross-lingual speech datasets. Despite the paucity of research on Tibetan speech translation, this paper endeavors to tackle the challenge of Tibetan-to-Chinese direct speech-to-speech translation within the multi-task learning framework, employing self-supervised learning (SSL) and sequence-to-sequence model training.

View Article and Find Full Text PDF

Some Challenging Questions About Outcomes in Children With Cochlear Implants.

Perspect ASHA Spec Interest Groups

December 2024

DeVault Otologic Research Laboratory, Department of Otolaryngology-Head and Neck Surgery, Indiana University School of Medicine, Indianapolis.

Purpose: Cochlear implants (CIs) have improved the quality of life for many children with severe-to-profound sensorineural hearing loss. Despite the reported CI benefits of improved speech recognition, speech intelligibility, and spoken language processing, large individual differences in speech and language outcomes are still consistently reported in the literature. The enormous variability in CI outcomes has made it challenging to predict which children may be at high risk for limited benefits and how potential risk factors can be improved with interventions.

View Article and Find Full Text PDF

Introduction: It is still under debate whether and how semantic content will modulate the emotional prosody perception in children with autism spectrum disorder (ASD). The current study aimed to investigate the issue using two experiments by systematically manipulating semantic information in Chinese disyllabic words.

Method: The present study explored the potential modulation of semantic content complexity on emotional prosody perception in Mandarin-speaking children with ASD.

View Article and Find Full Text PDF

Artificial intelligence (AI) scribe applications in the healthcare community are in the early adoption phase and offer unprecedented efficiency for medical documentation. They typically use an application programming interface with a large language model (LLM), for example, generative pretrained transformer 4. They use automatic speech recognition on the physician-patient interaction, generating a full medical note for the encounter, together with a draft follow-up e-mail for the patient and, often, recommendations, all within seconds or minutes.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!