Evidence map›Paper›PMID 38628616›Full record

ReviewJournal of multidisciplinary healthcare2024

A Systematic Review of the Application of Artificial Intelligence in Nursing Care: Where are We, and What's Next?

Suebsarn Ruksakulpiwat, Sutthinee Thorngthip, Atsadaporn Niyomyart, Chitchanok Benjasirisan, Lalipat Phianhasin, Heba Aldossary, Bootan Hasan Ahmed, Thanistha Samai

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of multidisciplinary healthcare, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  3. The Role of AI in Nursing Education and Practice: Umbrella Review.Journal of medical Internet research · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Suebsarn RuksakulpiwatDepartment of Medical Nursing, Faculty of Nursing, Mahidol University, Bangkok, Thailand.ORCID 0000-0003-2168-5195
Sutthinee ThorngthipDepartment of Nursing Siriraj Hospital, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.ORCID 0009-0007-9393-5081
Atsadaporn NiyomyartRamathibodi School of Nursing, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.ORCID 0000-0002-5460-2934
Chitchanok BenjasirisanDepartment of Medical Nursing, Faculty of Nursing, Mahidol University, Bangkok, Thailand.ORCID 0000-0001-6465-0721
Lalipat PhianhasinDepartment of Medical Nursing, Faculty of Nursing, Mahidol University, Bangkok, Thailand.ORCID 0000-0003-1960-5539
Heba AldossaryDepartment of Nursing, Prince Sultan Military College of Health Sciences, Dammam, Saudi Arabia.ORCID 0000-0001-8842-6169
Bootan Hasan AhmedFrances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH, USA.ORCID 0009-0002-5105-7659
Thanistha SamaiDepartment of Public Health Nursing, Faculty of Nursing, Mahidol University, Nakhon Pathom, Thailand.ORCID 0000-0002-0791-7108

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Integrating Artificial Intelligence (AI) into healthcare has transformed the landscape of patient care and healthcare delivery. Despite this, there remains a notable gap in the existing literature synthesizing the comprehensive understanding of AI's utilization in nursing care. Objective: This systematic review aims to synthesize the available evidence to comprehensively understand the application of AI in nursing care. Methods: Studies published between January 2019 and December 2023, identified through CINAHL Plus with Full Text, Web of Science, PubMed, and Medline, were included in this review. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines guided the identification, screening, exclusion, and inclusion of articles. The convergent integrated analysis framework, as proposed by the Joanna Briggs Institute, was employed to synthesize data from the included studies for theme generation. Results: A total of 337 records were identified from databases. Among them, 35 duplicates were removed, and 302 records underwent eligibility screening. After applying inclusion and exclusion criteria, eleven studies were deemed eligible and included in this review. Through data synthesis of these studies, six themes pertaining to the use of AI in nursing care were identified: 1) Risk Identification, 2) Health Assessment, 3) Patient Classification, 4) Research Development, 5) Improved Care Delivery and Medical Records, and 6) Developing a Nursing Care Plan. Conclusion: This systematic review contributes valuable insights into the multifaceted applications of AI in nursing care. Through the synthesis of data from the included studies, six distinct themes emerged. These findings not only consolidate the current knowledge base but also underscore the diverse ways in which AI is shaping and improving nursing care practices.

Indexed as

artificial intelligencenursing carepatient caresystematic review

Identifiers

PMID38628616
PMCPMC11020344

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.