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Speech recognition for clinical documentation from 1990 to 2018: a systematic review.

ABSTRACT: OBJECTIVE:The study sought to review recent literature regarding use of speech recognition (SR) technology for clinical documentation and to understand the impact of SR on document accuracy, provider efficiency, institutional cost, and more. MATERIALS AND METHODS:We searched 10 scientific and medical literature databases to find articles about clinician use of SR for documentation published between January 1, 1990, and October 15, 2018. We annotated included articles with their research topic(s), medical domain(s), and SR system(s) evaluated and analyzed the results. RESULTS:One hundred twenty-two articles were included. Forty-eight (39.3%) involved the radiology department exclusively and 10 (8.2%) involved emergency medicine; 10 (8.2%) mentioned multiple departments. Forty-eight (39.3%) articles studied productivity; 20 (16.4%) studied the effect of SR on documentation time, with mixed findings. Decreased turnaround time was reported in all 19 (15.6%) studies in which it was evaluated. Twenty-nine (23.8%) studies conducted error analyses, though various evaluation metrics were used. Reported percentage of documents with errors ranged from 4.8% to 71%; reported word error rates ranged from 7.4% to 38.7%. Seven (5.7%) studies assessed documentation-associated costs; 5 reported decreases and 2 reported increases. Many studies (44.3%) used products by Nuance Communications. Other vendors included IBM (9.0%) and Philips (6.6%); 7 (5.7%) used self-developed systems. CONCLUSION:Despite widespread use of SR for clinical documentation, research on this topic remains largely heterogeneous, often using different evaluation metrics with mixed findings. Further, that SR-assisted documentation has become increasingly common in clinical settings beyond radiology warrants further investigation of its use and effectiveness in these settings.

SUBMITTER: Blackley SV

PROVIDER: S-EPMC7647182 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Speech recognition for clinical documentation from 1990 to 2018: a systematic review.

Blackley Suzanne V SV Huynh Jessica J Wang Liqin L Korach Zfania Z Zhou Li L

Journal of the American Medical Informatics Association : JAMIA 20190401 4

<h4>Objective</h4>The study sought to review recent literature regarding use of speech recognition (SR) technology for clinical documentation and to understand the impact of SR on document accuracy, provider efficiency, institutional cost, and more.<h4>Materials and methods</h4>We searched 10 scientific and medical literature databases to find articles about clinician use of SR for documentation published between January 1, 1990, and October 15, 2018. We annotated included articles with their re ...[more]

PMID: 30753666

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Project description:BackgroundTaiwan has insufficient nursing resources due to the high turnover rate of health care providers. Therefore, reducing the heavy workload of these employees is essential. Herein, speech transcription, which has various potential clinical applications, was employed for the documentation of nursing records. The requirement of including only one speaker per transcription facilitated data collection and system development. Moreover, authorization from patients was unnecessary.ObjectiveThe aim of this study was to construct a speech recognition system for nursing records such that health care providers can complete nursing records without typing or with only a few edits.MethodsNursing records in Taiwan are mainly written in Mandarin, with technical terms and abbreviations presented in both Mandarin and English. Therefore, the training set consisted of English code-switching information. Next, transfer learning (TL) and meta-TL (MTL) methods, which perform favorably in code-switching scenarios, were applied.ResultsAs of September 2021, the China Medical University Hospital Artificial Intelligence Speech (CMaiSpeech) data set was established by manually annotating approximately 100 hours of recordings from 525 speakers. The word error rate (WER) of the benchmark model of syllable-based TL was 29.54% in code-switching. The WER of the proposed model of syllable-based MTL was 22.20% in code-switching. The test set comprised 17,247 words. Moreover, in a clinical case, the proposed model of syllable-based MTL yielded a WER of 31.06% in code-switching. The clinical test set contained 1159 words.ConclusionsThis paper has two main contributions. First, the CMaiSpeech data set-a Mandarin-English corpus-has been established. Health care providers in Taiwan are often compelled to use a mixture of Mandarin and English in nursing records. Second, an automatic speech recognition system for nursing record document conversion was proposed. The proposed system can shorten the work handover time and further reduce the workload of health care providers.

Project description:BACKGROUND:Antimicrobial resistance (AMR) is an increasing threat to global health. There are > 14 million cases of enteric fever every year and > 135,000 deaths. The disease is primarily controlled by antimicrobial treatment, but this is becoming increasingly difficult due to AMR. Our objectives were to assess the prevalence and geographic distribution of AMR in Salmonella enterica serovars Typhi and Paratyphi A infections globally, to evaluate the extent of the problem, and to facilitate the creation of geospatial maps of AMR prevalence to help targeted public health intervention. METHODS:We performed a systematic review of the literature by searching seven databases for studies published between 1990 and 2018. We recategorised isolates to allow the analysis of fluoroquinolone resistance trends over the study period. The prevalence of multidrug resistance (MDR) and fluoroquinolone non-susceptibility (FQNS) in individual studies was illustrated by forest plots, and a random effects meta-analysis was performed, stratified by Global Burden of Disease (GBD) region and 5-year time period. Heterogeneity was assessed using the I2 statistics. We present a descriptive analysis of ceftriaxone and azithromycin resistance. FINDINGS:We identified 4557 articles, of which 384, comprising 124,347 isolates (94,616 S. Typhi and 29,731 S. Paratyphi A) met the pre-specified inclusion criteria. The majority (276/384; 72%) of studies were from South Asia; 40 (10%) articles were identified from Sub-Saharan Africa. With the exception of MDR S. Typhi in South Asia, which declined between 1990 and 2018, and MDR S. Paratyphi A, which remained at low levels, resistance trends worsened for all antimicrobials in all regions. We identified several data gaps in Africa and the Middle East. Incomplete reporting of antimicrobial susceptibility testing (AST) and lack of quality assurance were identified. INTERPRETATION:Drug-resistant enteric fever is widespread in low- and middle-income countries, and the situation is worsening. It is essential that public health and clinical measures, which include improvements in water quality and sanitation, the deployment of S. Typhi vaccination, and an informed choice of treatment are implemented. However, there is no licenced vaccine for S. Paratyphi A. The standardised reporting of AST data and rollout of external quality control assessment are urgently needed to facilitate evidence-based policy and practice. TRIAL REGISTRATION:PROSPERO CRD42018029432.

Project description:Abstract 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.

Project description:ObjectiveTo evaluate the evidence of aerosol generation across tasks involved in voice and speech assessment and intervention, to inform better management and to reduce transmission risk of such diseases as COVID-19 in healthcare settings and the wider community.DesignSystematic literature review.Data sources and eligibilityMedline, Embase, Scopus, Web of Science, CINAHL, PubMed Central and grey literature through ProQuest, The Centre for Evidence-Based Medicine, COVID-Evidence and speech pathology national bodies were searched up until August 13th, 2020 for articles examining the aerosol-generating activities in clinical voice and speech assessment and intervention within speech pathology.ResultsOf the 8288 results found, 39 studies were included for data extraction and analysis. Included articles were classified into one of three categories: research studies, review articles or clinical guidelines. Data extraction followed appropriate protocols depending on the classification of each article (e.g. PRISMA for review articles). Articles were assessed for risk of bias and certainty of evidence using the GRADE system. Six behaviours were identified as aerosol generating. These were classified into three categories: vegetative acts (coughing, breathing), verbal communication activities of daily living (speaking, loud voicing), and performance-based tasks (singing, sustained phonation). Certainty of evidence ranged from very low to moderate with variation in research design and variables.ConclusionsThis body of literature helped to both identify and categorise the aerosol-generating behaviours involved in speech pathology clinical practice and confirm the low level of evidence throughout the speech pathology literature pertaining to aerosol generation. As many aerosol-generating behaviours are common human behaviours, these findings can be applied across healthcare and community settings.Systematic review registrationRegistration number CRD42020186902 with PROSPERO International Prospective Register for Systematic Reviews.

Project description:BACKGROUND:Hospitalizations for chronic ambulatory care sensitive conditions are an important indicator of health system equity and performance. Chronic ambulatory care sensitive conditions refer to chronic diseases that can be managed in primary care settings, including angina, asthma, and diabetes, with hospitalizations for these conditions considered potentially avoidable with adequate primary care interventions. Socioeconomic inequities in the risk of hospitalization have been observed in several health systems globally. While there are multiple studies examining the association between socioeconomic status and hospitalizations for chronic ambulatory care sensitive conditions, these studies have not been systematically reviewed. The objective of this study is to systematically identify and describe socioeconomic inequalities in hospitalizations for chronic ambulatory care sensitive conditions amongst adult populations in economically developed countries reported in high-quality observational studies published in the peer-reviewed literature. METHODS:Peer-reviewed literature was searched in six health and social science databases: MEDLINE, EMBASE, PsycInfo, CINAHL, ASSIA, and IBSS using search terms for hospitalization, socioeconomic status, and chronic ambulatory care sensitive conditions. Study titles and abstracts were first screened followed by full-text review according to the following eligibility criteria: 1) Study outcome is hospitalization for selected chronic ambulatory care sensitive conditions; 2) Primary exposure is individual- or area-level socioeconomic status; 3) Study population has a mean age ± 1 SD < 75 years of age; 4) Study setting is economically developed countries; and 5) Study type is observational. Relevant data was then extracted, and studies were critically appraised using appropriate tools from The Joanna Briggs Institute. Results were narratively synthesized according to socioeconomic constructs and type of adjustment (minimally versus fully adjusted). RESULTS:Of the 15,857 unique peer-reviewed studies identified, 31 studies met the eligibility criteria and were of sufficient quality for inclusion. Socioeconomic constructs and hospitalization outcomes varied across studies. However, despite this heterogeneity, a robust and consistent association between lower levels of socioeconomic status and higher risk of hospitalizations for chronic ambulatory care sensitive conditions was observed. CONCLUSIONS:This systematic review is the first to comprehensively identify and analyze literature on the relationship between SES and hospitalizations for chronic ambulatory care sensitive conditions, considering both aggregate and condition-specific outcomes that are common to several international health systems. The evidence consistently demonstrates that lower socioeconomic status is a risk factor for hospitalization across global settings. Effective health and social interventions are needed to reduce these inequities and ensure fair and adequate care across socioeconomic groups. TRIAL REGISTRATION:PROSPERO CRD42018088727.

Dataset Information

Speech recognition for clinical documentation from 1990 to 2018: a systematic review.

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Speech recognition for clinical documentation from 1990 to 2018: a systematic review.

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