Nursing Informatics Research Trends: Findings from an International Survey

Peltonen, Laura-María; Nibber, Raji; Block, Lorraine; Ronquillo, Charlene; Perezmitre, Erika Lozada; Lewis, Adrienne; Alhuwail, Dari; Ali, Samira; Georgsson, Mattias; Jeon, Eunjoo; Tayaben, Jude L.; Lee, Ying-Li; Kuo, Chiu-Hsiang; Shu, Shao-Hui; Hsu, Han-Jen; Sommer, Janine; Sarmiento, Raymond Francis; Jung, Hyunggu; Eler, Gabrielle Jacklin; Badger, Martha K.; Zhao, Rui; Tong, Zhou; Deforest, Haley; Atique, Suleman; Topaz, Maxim; Pruinelli, Lisiane

doi:10.3233/shti210741

Cited by 9 publications

(15 citation statements)

References 10 publications

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“… 40 In fact, in a 2013 priority list for NI research, integrating genomic data into the EHR was last in a list of 20 research topic areas; no other epigenetic research-related topics were included in the priority list, and a 2021 study listed genomics as 32 of a 36-item priority research list. 41 , 42 Among other priorities of NI research listed were clinical decision support (#2 on the 2021 list), Big Data (#3 on the list), and data science (#25 on the list), all of which are components of genomic and epigenetic research. Nursing informatics theory got a higher priority (#30 of 36) than genomics, indicating that some NI researchers are focusing on topics that do not put the patient at the center of data analysis or NI research.…”

Section: Current Statementioning

confidence: 99%

Nursing Informatics and Epigenetics

Milner

Zadinsky

2022

CIN: Computers, Informatics, Nursing

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Section: Current Statementioning

confidence: 99%

Nursing Informatics and Epigenetics

Milner

Zadinsky

2022

CIN: Computers, Informatics, Nursing

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“…Based on standardized data on patient history and nursing assessment results, clinical decision support (CDS) is made available to accomplish meaningful use of EHR and to assist health care professionals with decision-making [ 3 ]. SNL and CDS are among the top research priorities in nursing informatics [ 4 ]. Despite its potential to support and transform nursing practice by simplifying record-keeping, promoting standards-based practice, and giving timely access to information to aid decision-making [ 5 ], the introduction of NIS, does not necessarily lead to user adoption [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Transition to a new nursing information system embedded with clinical decision support: a mixed-method study using the HOT-fit framework

Zhai

Yang

et al. 2022

BMC Med Inform Decis Mak

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Background Nursing information systems embedded with standardized nursing language and clinical decision support have been increasingly introduced in health care settings. User experience is key to the adoption of health information technologies. Despite extensive research into the user experience with nursing information systems, few studies have focused on the interaction between user, technology and organizational attributes during its implementation. Guided by the human, organization and technology-fit framework, this study aimed to investigate nurses’ perceptions and experiences with transition to a new nursing information system (Care Direct) 2 years after its first introduction. Methods This is a mixed-method study using an embedded design. An online survey was launched to collect nurses’ self-reported use of the new system, perceived system effectiveness and experience of participation in system optimization. Twenty-two semi structured interviews were conducted with twenty nurses with clinical or administrative roles. The quantitative and qualitative data were merged using the Pillar Integration Process. Results The average score of system use behavior was 3.76 ± 0.79. Regarding perceived system effectiveness, the score of each dimension ranged 3.07–3.34 out of 5. Despite large variations in approaches to participating in system optimization, nurses had generally positive experiences with management and technical support. Eight main categories emerged from the integrated findings, which were further condensed into three themes: perceptions on system content, structure, and functionality; perceptions on interdisciplinary and cross-level cooperation; and embracing and accepting the change. Conclusions Effective collaboration between clinicians, administrators and technical staff is required during system promotion to enhance system usability and user experience. Clear communication of organizational missions to staff and support from top management is needed to smooth the system implementation process and achieve broader system adoption.

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“…Additional evidence on nursing informatics (NI; Peltonen et al, 2016;Topaz et al, 2016) The literature adopted for this article was identified adopting the guidance of a modified 'argumentative literature review' methodology as developed by McCullough et al (2004) for evaluating topics while examining literature selectively in order to support or refute an argument. The purpose of this approach to literature review is to develop a body of literature that establishes a contrarian viewpoint.…”

Section: Introductionmentioning

confidence: 99%

Is there a gap between artificial intelligence applications and priorities in health care and nursing management?

Chen

Moreira

Liu

et al. 2022

J Nursing Management

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Aim The article aims to outline a contrast between three priorities for nursing management proposed a decade ago and key features of the following 10 years of developments on artificial intelligence for health care and nursing management. This analysis intends to contribute to update the international debate on bridging the essence of health care and nursing management priorities and the focus of artificial intelligence developers. Background Artificial intelligence research promises innovative approaches to supporting nurses' clinical decision‐making and to conduct tasks not related to patient interaction, including administrative activities and patient records. Yet, even though there has been an increase in international research and development of artificial intelligence applications for nursing care during the past 10 years, it is unclear to what extent the priorities of nursing management have been embedded in the devised artificial intelligence solutions. Evaluation Starting from three priorities for nursing management identified in 2011 in a special issue of the Journal Nursing Management, we went on to identify recent evidence concerning 10 years of artificial intelligence applications developed to support health care management and nursing activities since then. Key Issue The article discusses to what extent priorities in health care and nursing management may have to be revised while adopting artificial intelligence applications or, alternatively, to what extent the direction of artificial intelligence developments may need to be revised to contribute to long acknowledged priorities of nursing management. Conclusion We have identified a conceptual gap between both sets of ideas and provide a discussion on the need to bridge that gap, while admitting that there may have been recent field developments still unreported in scientific literature. Implications for Nursing Management Artificial intelligence developers and health care nursing managers need to be more engaged in coordinating the future development of artificial intelligence applications with a renewed set of nursing management priorities.

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Nursing Informatics Research Trends: Findings from an International Survey

Cited by 9 publications

References 10 publications

Nursing Informatics and Epigenetics

Nursing Informatics and Epigenetics

Transition to a new nursing information system embedded with clinical decision support: a mixed-method study using the HOT-fit framework

Is there a gap between artificial intelligence applications and priorities in health care and nursing management?

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