Using natural language processing in emergency medicine health service research: A systematic review and meta-analysis.

OBJECTIVES: Natural language processing (NLP) represents one of the adjunct technologies within artificial intelligence and machine learning, creating structure out of unstructured data. This study aims to assess the performance of employing NLP to identify and categorize unstructured data within the emergency medicine (EM) setting. METHODS: We systematically searched publications related to EM research and NLP across databases including MEDLINE, Embase, Scopus, CENTRAL, and ProQuest Dissertations & Theses Global. Independent reviewers screened, reviewed, and evaluated article quality and bias. NLP usage was categorized into syndromic surveillance, radiologic interpretation, and identification of specific diseases/events/syndromes, with respective sensitivity analysis reported. Performance metrics for NLP usage were calculated and the overall area under the summary of receiver operating characteristic curve (SROC) was determined. RESULTS: A total of 27 studies underwent meta-analysis. Findings indicated an overall mean sensitivity (recall) of 82%-87%, specificity of 95%, with the area under the SROC at 0.96 (95% CI 0.94-0.98). Optimal performance using NLP was observed in radiologic interpretation, demonstrating an overall mean sensitivity of 93% and specificity of 96%. CONCLUSIONS: Our analysis revealed a generally favorable performance accuracy in using NLP within EM research, particularly in the realm of radiologic interpretation. Consequently, we advocate for the adoption of NLP-based research to augment EM health care management.

Trends in Adoption of Twitter by Health Sciences Librarians.

There is substantial research on librarians' engagement with various social media platforms as part of their professional obligations. We were interested in examining librarians' use of Twitter outside of the context of a job-related, but still professional, context. To find out more, we invited health sciences librarians via Twitter to discuss the impact that the platform has had on their professional lives, offering this column as an opportunity to share their experiences. The case reports support the premise that Twitter can be an impactful communications tool and can benefit librarians in meaningful ways, both professionally and personally.

Defining, conceptualizing, and measuring perceived maternal care quality in low- to high-income countries: a scoping review protocol.

BACKGROUND: Health practitioners and researchers must be able to measure and assess maternal care quality in facilities to monitor, intervene, and reduce global maternal mortality rates. On the global scale, there is a general lack of consensus on how maternal care quality is defined, conceptualized, and measured. Much of the literature addressing this problem has focused primarily on defining, conceptualizing, and measuring clinical indicators of maternal care quality. Less attention has been given in this regard to perceived maternal care quality among women which is known to influence care utilization and adherence. Therefore, there is a need to map the literature focused on defining, conceptualizing, and measuring perceived maternal care quality across low-, middle-, and high-income country contexts. METHODS: This scoping review protocol will follow the Arksey and O'Malley methodological framework. A comprehensive search strategy will be used to search for articles published from inception to 2020 in Ovid MEDLINE, Embase, AMED, and WHO Global Index Medicus. Gray literature will be included. Two independent reviewers will screen articles by title and abstract, then by full-text based on pre-determined inclusion/exclusion criteria. A third reviewer will arbitrate any discrepancies. This protocol outlines a four-step analytic approach that includes numerical, graphical, tabular, and narrative summaries to provide a comprehensive description of the body of literature. DISCUSSION: The findings from this scoping review will provide a comprehensive overview of the existing evidence on perceived maternal care quality. The findings are expected to inform future work on building consensus around the definition and conceptualization of perceived maternal care quality, and lay the groundwork for future research aimed at developing measures of perceived maternal care quality that can be applied across country contexts. Consequently, this review may aid in facilitating coordinated efforts to measure and improve maternal care quality across diverse country contexts (i.e., low-, middle-, and high-income country contexts). REVIEW REGISTRATION: This scoping review has been registered in the Open Science Framework (osf.io/k8nqh).