Towards Automated Screening of Literature on Artificial Intelligence in Nursing.

We evaluate the performance of multiple text classification methods used to automate the screening of article abstracts in terms of their relevance to a topic of interest. The aim is to develop a system that can be first trained on a set of manually screened article abstracts before using it to identify additional articles on the same topic. Here the focus is on articles related to the topic "artificial intelligence in nursing". Eight text classification methods are tested, as well as two simple ensemble systems. The results indicate that it is feasible to use text classification technology to support the manual screening process of article abstracts when conducting a literature review. The best results are achieved by an ensemble system, which achieves a F1-score of 0.41, with a sensitivity of 0.54 and a specificity of 0.96. Future work directions are discussed.

How to Improve Information Technology to Support Healthcare to Address the COVID-19 Pandemic: an International Survey with Health Informatics Experts.

OBJECTIVES: To identify the ways in which healthcare information and communication technologies can be improved to address the challenges raised by the COVID-19 pandemic. METHODS: The study population included health informatics experts who had been involved with the planning, development and deployment of healthcare information and communication technologies in healthcare settings in response to the challenges presented by the COVID-19 pandemic. Data were collected via an online survey. A non-probability convenience sampling strategy was employed. Data were analyzed with content analysis. RESULTS: A total of 65 participants from 16 countries responded to the conducted survey. The four major themes regarding recommended improvements identified from the content analysis included: improved technology availability, improved interoperability, intuitive user interfaces and adoption of standards of care. Respondents also identified several key healthcare information and communication technologies that can help to provide better healthcare to patients during the COVID-19 pandemic, including telehealth, advanced software, electronic health records, remote work technologies (e.g., remote desktop computer access), and clinical decision support tools. CONCLUSIONS: Our results help to identify several important healthcare information and communication technologies, recommended by health informatics experts, which can help to provide better care to patients during the COVID-19 pandemic. The results also highlight the need for improved interoperability, intuitive user interfaces and advocating the adoption of standards of care.

Benefits Innovations in Employee Behavioral Health.

More and more employers recognize the business impact of behavioral health concerns in the workplace. This article provides insights into some of the current innovations in behavioral health benefits, along with their rationale for development. Areas of innovation include conceptual and delivery models, technological advance- ments, tools for engaging employees and ways of quantifying the business value of behavioral health benefits. The rapid growth of innovative behavioral health services should provide employers with confidence that they can tailor a program best suited to their priorities, organizational culture and cost limitations.

Adoption of Speech Recognition Technology in Community Healthcare Nursing.

Adoption of new health information technology is shown to be challenging. However, the degree to which new technology will be adopted can be predicted by measures of usefulness and ease of use. In this work these key determining factors are focused on for design of a wound documentation tool. In the context of wound care at home, consistent with evidence in the literature from similar settings, use of Speech Recognition Technology (SRT) for patient documentation has shown promise. To achieve a user-centred design, the results from a conducted ethnographic fieldwork are used to inform SRT features; furthermore, exploratory prototyping is used to collect feedback about the wound documentation tool from home care nurses. During this study, measures developed for healthcare applications of the Technology Acceptance Model will be used, to identify SRT features that improve usefulness (e.g. increased accuracy, saving time) or ease of use (e.g. lowering mental/physical effort, easy to remember tasks). The identified features will be used to create a low fidelity prototype that will be evaluated in future experiments.

Mapping Wound Assessment Data Elements in SNOMED CT.

The use of standardized terminologies is an essential component to support interoperability in electronic health records. In British Columbia, Canada, a commonly used nursing wound assessment template was mapped to SNOMED CT. Preliminary results have found that 50.8% of the wound assessment data elements had direct matches to concepts within SNOMED CT. Results of this mapping activity have produced a set of mapped wound assessment parameters to SNOMED CT.