Feasibility and Utility of Lexical Analysis for Occupational Health Text

Mapping the concept of health care integration: A lexicographic analysis of scientific literature

BACKGROUND

Systems fragmentation is a major challenge for an efficient organization, integration being a potential solution also proposed in health care field, including pharmacy as a player. However, the use of different terms and definitions in the literature hinders the comparison of different integration initiatives.

OBJECTIVE

To identify and map the terms used in scientific literature regarding integration in health care and to characterize each emerging topic.

METHODS

A lexicographic analysis of the integration of healthcare systems literature indexed in PubMed was conducted. Ten different systematic searches, four using only Medical Subject Headings (MeSH) and six using text words, were conducted in March 2023. Journal scattering was analyzed following Bradford's distribution using the Leimkuhler model. An overall text corpus was created with titles and abstracts of all the records retrieved. The corpus was lemmatized, and the most used bigrams were tokenized as single strings. To perform a topic modeling, the lemmatized corpus text was analyzed using IRaMuTeQ, producing descending hierarchic classification and a correspondence analysis. The 50 words with higher chi-square statistics in each class were considered as representative of the class.

RESULTS

A total of 42,479 articles published from 1943 to 2023 in 4469 different journals were retrieved. The MeSH "Delivery of Health Care, Integrated", created in the 1996 MeSH update, was the most productive retrieving 33.7 % of the total articles but also retrieving 22.6 % of articles not retrieved in any other search. The text word "Integration" appeared in 15,357 (36.2 %) records. The lexicographic analysis resulted in 7 classes, named as: Evidence and implementation, Quantitative research, Professional education, Qualitative research, Governance and leadership, Clinical research, and Financial resources. Association between the classes and the searches or the text-words used ranged from moderate to weak demonstrating the lack of a standard pattern of use of terms in literature regarding healthcare integration.

CONCLUSIONS

The term "integration" and the MeSH "Delivery of Health Care, Integrated" are the most used to represent the concept of integration in healthcare and should be the preferred terms in the literature.

The role of machine learning in the primary prevention of work-related musculoskeletal disorders: A scoping review

To determine the applications of machine learning (ML) techniques used for the primary prevention of work-related musculoskeletal disorders (WMSDs), a scoping review was conducted using seven literature databases. Of the 4,639 initial results, 130 primary research studies were deemed relevant for inclusion. Studies were reviewed and classified as a contribution to one of six steps within the primary WMSD prevention research framework by van der Beek et al. (2017). ML techniques provided the greatest contributions to the development of interventions (48 studies), followed by risk factor identification (33 studies), underlying mechanisms (29 studies), incidence of WMSDs (14 studies), evaluation of interventions (6 studies), and implementation of effective interventions (0 studies). Nearly a quarter (23.8%) of all included studies were published in 2020. These findings provide insight into the breadth of ML techniques used for primary WMSD prevention and can help identify areas for future research and development.

The Unified Medical Language System at 30 Years and How It Is Used and Published: Systematic Review and Content Analysis

BACKGROUND

The Unified Medical Language System (UMLS) has been a critical tool in biomedical and health informatics, and the year 2021 marks its 30th anniversary. The UMLS brings together many broadly used vocabularies and standards in the biomedical field to facilitate interoperability among different computer systems and applications.

OBJECTIVE

Despite its longevity, there is no comprehensive publication analysis of the use of the UMLS. Thus, this review and analysis is conducted to provide an overview of the UMLS and its use in English-language peer-reviewed publications, with the objective of providing a comprehensive understanding of how the UMLS has been used in English-language peer-reviewed publications over the last 30 years.

METHODS

PubMed, ACM Digital Library, and the Nursing & Allied Health Database were used to search for studies. The primary search strategy was as follows: UMLS was used as a Medical Subject Headings term or a keyword or appeared in the title or abstract. Only English-language publications were considered. The publications were screened first, then coded and categorized iteratively, following the grounded theory. The review process followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

RESULTS

A total of 943 publications were included in the final analysis. Moreover, 32 publications were categorized into 2 categories; hence the total number of publications before duplicates are removed is 975. After analysis and categorization of the publications, UMLS was found to be used in the following emerging themes or areas (the number of publications and their respective percentages are given in parentheses): natural language processing (230/975, 23.6%), information retrieval (125/975, 12.8%), terminology study (90/975, 9.2%), ontology and modeling (80/975, 8.2%), medical subdomains (76/975, 7.8%), other language studies (53/975, 5.4%), artificial intelligence tools and applications (46/975, 4.7%), patient care (35/975, 3.6%), data mining and knowledge discovery (25/975, 2.6%), medical education (20/975, 2.1%), degree-related theses (13/975, 1.3%), digital library (5/975, 0.5%), and the UMLS itself (150/975, 15.4%), as well as the UMLS for other purposes (27/975, 2.8%).

CONCLUSIONS

The UMLS has been used successfully in patient care, medical education, digital libraries, and software development, as originally planned, as well as in degree-related theses, the building of artificial intelligence tools, data mining and knowledge discovery, foundational work in methodology, and middle layers that may lead to advanced products. Natural language processing, the UMLS itself, and information retrieval are the 3 most common themes that emerged among the included publications. The results, although largely related to academia, demonstrate that UMLS achieves its intended uses successfully, in addition to achieving uses broadly beyond its original intentions.

Informatics Approaches for Recognition, Management, and Prevention of Occupational Respiratory Disease

Computer and information systems can improve occupational respiratory disease prevention and surveillance by providing efficient resources for patients, workers, clinicians, and public health practitioners. Advances include interlinking electronic health records, autocoding surveillance data, clinical decision support systems, and social media applications for acquiring and disseminating information. Obstacles to advances include inflexible hierarchical coding schemes, inadequate occupational health electronic health record systems, and inadequate public focus on occupational respiratory disease. Potentially transformative approaches include machine learning, natural language processing, and improved ontologies.

Insights from Twitter About Public Perceptions of Asthma, COPD, and Exposures

OBJECTIVE

The aim of this study was to analyze tweets concerning asthma and chronic obstructive pulmonary disease (COPD).

METHODS

Approximately 40,000 tweets containing asthma or COPD were analyzed. Lexical analysis ranked terms and domains of interest, compared COPD with asthma tweets, evaluated co-occurrence of terms within tweets, and assessed differences by source (personal, institutional, or retweet). The frequency of indicator terms relevant to occupational health was determined.

RESULTS

Many tweets address community pollution and effects on children, but there is much less interest in work-related factors and occupational regulatory agencies. Environment is considered much more relevant for asthma than COPD.

CONCLUSION

Although epidemiologic studies demonstrate a major burden of occupational factors upon both diseases, significantly improved outreach is needed to overcome inadequate public interest. Social media represent a valuable resource for assessing perceptions about work-related disease and potentially discovering new associations.

Big Data in occupational medicine: the convergence of -omics sciences, participatory research and e-health

Background:

New occupational hazards and risks are emerging in our progressively globalized society, in which ageing, migration, wild urbanization and rapid economic growth have led to unprecedented biological, chemical and physical exposures, linked to novel technologies, products and duty cycles. A focus shift from worker health to worker/citizen and community health is crucial. One of the major revolutions of the last decades is the computerization and digitization of the work process, the so-called “work 4.0”, and of the workplace.

Objectives:

To explore the roles and implications of Big Data in the new occupational medicine settings.

Methods:

Comprehensive literature search.

Results:

Big Data are characterized by volume, variety, veracity, velocity, and value. They come both from wet-lab techniques (“molecular Big Data”) and computational infrastructures, including databases, sensors and smart devices (“computational Big Data” and “digital Big Data”).

Conclusions:

In the light of novel hazards and thanks to new analytical approaches, molecular and digital underpinnings become extremely important in occupational medicine. Computational and digital tools can enable us to uncover new relationships between exposures and work-related diseases; to monitor the public reaction to novel risk factors associated to occupational diseases; to identify exposure-related changes in disease natural history; and to evaluate preventive workplace practices and legislative measures adopted for workplace health and safety.