RESUMO
INTRODUCTION: Vascular access is the most common invasive procedure performed in health care. This fundamental procedure must be performed in a safe and effective manner. Vascular access devices (VADs) are often the source of infections and other complications, yet there is a lack of clear guidance on VADs for health providers across different settings. A Best Practice Guideline (BPG) was developed by the Registered Nurses' Association of Ontario (RNAO) to provide evidence-based recommendations on the assessment and management of VADs. METHODS: RNAO BPGs are based on systematic reviews of the literature following the GRADE approach. Experts on the topic of vascular access were selected to form a panel. Systematic reviews were conducted on six research areas: education, vascular access specialists, blood draws, daily review of peripheral VADs, visualization technologies, and pain management. A search for relevant research studies published in English limited to January 2013 was applied to eight databases. All studies were independently assessed for eligibility and risk of bias by two reviewers based on predetermined inclusion and exclusion criteria. The GRADE approach was used to determine certainty of the evidence. RESULTS: Over 65,000 articles were screened related to the six priority research questions. Of these, 876 full-text publications were examined for relevance, with 174 articles designated to inform nine recommendations in the BPG on the subject areas of: comprehensive health teaching, practical education for health providers, blood draws, daily review of peripheral VADs, visualization technologies, and pain management. In June 2021, the RNAO published the BPG on vascular access, which included the recommendations and other supporting resources. CONCLUSION: The vascular access BPG provides high quality guidance and updated recommendations, and can serve as a primary resource for health providers assessing and managing VADs.
RESUMO
BACKGROUND: It is predicted that artificial intelligence (AI) will transform nursing across all domains of nursing practice, including administration, clinical care, education, policy, and research. Increasingly, researchers are exploring the potential influences of AI health technologies (AIHTs) on nursing in general and on nursing education more specifically. However, little emphasis has been placed on synthesizing this body of literature. OBJECTIVE: A scoping review was conducted to summarize the current and predicted influences of AIHTs on nursing education over the next 10 years and beyond. METHODS: This scoping review followed a previously published protocol from April 2020. Using an established scoping review methodology, the databases of MEDLINE, Cumulative Index to Nursing and Allied Health Literature, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central, Education Resources Information Centre, Scopus, Web of Science, and Proquest were searched. In addition to the use of these electronic databases, a targeted website search was performed to access relevant grey literature. Abstracts and full-text studies were independently screened by two reviewers using prespecified inclusion and exclusion criteria. Included literature focused on nursing education and digital health technologies that incorporate AI. Data were charted using a structured form and narratively summarized into categories. RESULTS: A total of 27 articles were identified (20 expository papers, six studies with quantitative or prototyping methods, and one qualitative study). The population included nurses, nurse educators, and nursing students at the entry-to-practice, undergraduate, graduate, and doctoral levels. A variety of AIHTs were discussed, including virtual avatar apps, smart homes, predictive analytics, virtual or augmented reality, and robots. The two key categories derived from the literature were (1) influences of AI on nursing education in academic institutions and (2) influences of AI on nursing education in clinical practice. CONCLUSIONS: Curricular reform is urgently needed within nursing education programs in academic institutions and clinical practice settings to prepare nurses and nursing students to practice safely and efficiently in the age of AI. Additionally, nurse educators need to adopt new and evolving pedagogies that incorporate AI to better support students at all levels of education. Finally, nursing students and practicing nurses must be equipped with the requisite knowledge and skills to effectively assess AIHTs and safely integrate those deemed appropriate to support person-centered compassionate nursing care in practice settings. INTERNATIONAL REGISTERED REPORT IDENTIFIER IRRID: RR2-10.2196/17490.
RESUMO
BACKGROUND: It is predicted that digital health technologies that incorporate artificial intelligence will transform health care delivery in the next decade. Little research has explored how emerging trends in artificial intelligence-driven digital health technologies may influence the relationship between nurses and patients. OBJECTIVE: The purpose of this scoping review is to summarize the findings from 4 research questions regarding emerging trends in artificial intelligence-driven digital health technologies and their influence on nursing practice across the 5 domains outlined by the Canadian Nurses Association framework: administration, clinical care, education, policy, and research. Specifically, this scoping review will examine how emerging trends will transform the roles and functions of nurses over the next 10 years and beyond. METHODS: Using an established scoping review methodology, MEDLINE, Cumulative Index to Nursing and Allied Health Literature, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central, Education Resources Information Centre, Scopus, Web of Science, and Proquest databases were searched. In addition to the electronic database searches, a targeted website search will be performed to access relevant grey literature. Abstracts and full-text studies will be independently screened by 2 reviewers using prespecified inclusion and exclusion criteria. Included literature will focus on nursing and digital health technologies that incorporate artificial intelligence. Data will be charted using a structured form and narratively summarized. RESULTS: Electronic database searches have retrieved 10,318 results. The scoping review and subsequent briefing paper will be completed by the fall of 2020. CONCLUSIONS: A symposium will be held to share insights gained from this scoping review with key thought leaders and a cross section of stakeholders from administration, clinical care, education, policy, and research as well as patient advocates. The symposium will provide a forum to explore opportunities for action to advance the future of nursing in a technological world and, more specifically, nurses' delivery of compassionate care in the age of artificial intelligence. Results from the symposium will be summarized in the form of a briefing paper and widely disseminated to relevant stakeholders. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17490.
RESUMO
BACKGROUND: Artificial intelligence (AI) is set to transform the health system, yet little research to date has explored its influence on nurses-the largest group of health professionals. Furthermore, there has been little discussion on how AI will influence the experience of person-centered compassionate care for patients, families, and caregivers. OBJECTIVE: This review aims to summarize the extant literature on the emerging trends in health technologies powered by AI and their implications on the following domains of nursing: administration, clinical practice, policy, and research. This review summarizes the findings from 3 research questions, examining how these emerging trends might influence the roles and functions of nurses and compassionate nursing care over the next 10 years and beyond. METHODS: Using an established scoping review methodology, MEDLINE, CINAHL, EMBASE, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central, Education Resources Information Center, Scopus, Web of Science, and ProQuest databases were searched. In addition to the electronic database searches, a targeted website search was performed to access relevant gray literature. Abstracts and full-text studies were independently screened by 2 reviewers using prespecified inclusion and exclusion criteria. Included articles focused on nursing and digital health technologies that incorporate AI. Data were charted using structured forms and narratively summarized. RESULTS: A total of 131 articles were retrieved from the scoping review for the 3 research questions that were the focus of this manuscript (118 from database sources and 13 from targeted websites). Emerging AI technologies discussed in the review included predictive analytics, smart homes, virtual health care assistants, and robots. The results indicated that AI has already begun to influence nursing roles, workflows, and the nurse-patient relationship. In general, robots are not viewed as replacements for nurses. There is a consensus that health technologies powered by AI may have the potential to enhance nursing practice. Consequently, nurses must proactively define how person-centered compassionate care will be preserved in the age of AI. CONCLUSIONS: Nurses have a shared responsibility to influence decisions related to the integration of AI into the health system and to ensure that this change is introduced in a way that is ethical and aligns with core nursing values such as compassionate care. Furthermore, nurses must advocate for patient and nursing involvement in all aspects of the design, implementation, and evaluation of these technologies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/17490.
RESUMO
The synthesis and beta-lactamase inhibitory activity of four 6-(mercaptomethyl)penicillinates and the four corresponding 6-(hydroxymethyl)penicillinates are described. These penicillins include both C6 stereoisomers as well as the sulfide and sulfone oxidation states of the penam thiazolidine sulfur. All compounds were evaluated as inhibitors of representative metallo- and serine-beta-lactamases enzymes. Selected (mercaptomethyl)penicillinates are shown to inactivate both metallo- and serine-beta-lactamases and to display synergism with piperacillin against beta-lactamase producing strains.
