The Integration of AI into the Nursing Process: A Comparative Analysis of NANDA, NOC, and NIC-Based Care Plans

<b>Background/Objectives</b>: Nursing diagnosis is a complex process that requires clinical judgment, time, and resources and whose implementation is hindered by factors such as workload, lack of time, and resistance to computerized systems. This study aimed to compare the quality and ef...

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Main Authors: Ester Gilart, Anna Bocchino, Patricia Gilart-Cantizano, Eva Manuela Cotobal-Calvo, Isabel Lepiani-Diaz, Daniel Román-Sánchez, José Luis Palazón-Fernández
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Nursing Reports
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Online Access:https://www.mdpi.com/2039-4403/15/6/186
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author Ester Gilart
Anna Bocchino
Patricia Gilart-Cantizano
Eva Manuela Cotobal-Calvo
Isabel Lepiani-Diaz
Daniel Román-Sánchez
José Luis Palazón-Fernández
author_facet Ester Gilart
Anna Bocchino
Patricia Gilart-Cantizano
Eva Manuela Cotobal-Calvo
Isabel Lepiani-Diaz
Daniel Román-Sánchez
José Luis Palazón-Fernández
author_sort Ester Gilart
collection DOAJ
description <b>Background/Objectives</b>: Nursing diagnosis is a complex process that requires clinical judgment, time, and resources and whose implementation is hindered by factors such as workload, lack of time, and resistance to computerized systems. This study aimed to compare the quality and efficiency of care plans generated by nursing professionals versus those produced by an artificial intelligence (AI) model, using the NANDA, NOC, and NIC taxonomies as criteria. <b>Methods</b>: An observational study was carried out with three simulated clinical cases. Thirty experts, fifty-four nursing professionals, and the ChatGPT model (GPT-4) were included. The experts established the referral plans using the Delphi technique. Responses were evaluated with a validated rubric (EADE-2) and analyzed using nonparametric tests. Professionals’ perceptions on the use of computer systems were also collected. <b>Results</b>: ChatGPT scored significantly higher on several dimensions (<i>p</i> < 0.001) and resolved all three cases in 35 s, compared to an average of 30 min for practitioners. Professionals expressed dissatisfaction with current diagnostic documentation systems. <b>Conclusions</b>: AI demonstrates high potential in optimizing the diagnostic process in nursing, although for its implementation human supervision, ethical aspects and improvements in current systems must be considered to achieve effective integration.
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spelling doaj-art-d80cdcc3f22e44aa9db24d58986937972025-08-20T03:29:48ZengMDPI AGNursing Reports2039-439X2039-44032025-05-0115618610.3390/nursrep15060186The Integration of AI into the Nursing Process: A Comparative Analysis of NANDA, NOC, and NIC-Based Care PlansEster Gilart0Anna Bocchino1Patricia Gilart-Cantizano2Eva Manuela Cotobal-Calvo3Isabel Lepiani-Diaz4Daniel Román-Sánchez5José Luis Palazón-Fernández6Department of Nursing and Physiotherapy, University of Cádiz, 11009 Cádiz, SpainNursing Faculty “Salus Infirmorum”, University of Cádiz, Calle Ancha 29, 11001 Cádiz, SpainHospital la Linea de la Concepción, 11300 Cadiz, SpainNursing Faculty “Salus Infirmorum”, University of Cádiz, Calle Ancha 29, 11001 Cádiz, SpainNursing Faculty “Salus Infirmorum”, University of Cádiz, Calle Ancha 29, 11001 Cádiz, SpainNursing Faculty “Salus Infirmorum”, University of Cádiz, Calle Ancha 29, 11001 Cádiz, SpainNursing Faculty “Salus Infirmorum”, University of Cádiz, Calle Ancha 29, 11001 Cádiz, Spain<b>Background/Objectives</b>: Nursing diagnosis is a complex process that requires clinical judgment, time, and resources and whose implementation is hindered by factors such as workload, lack of time, and resistance to computerized systems. This study aimed to compare the quality and efficiency of care plans generated by nursing professionals versus those produced by an artificial intelligence (AI) model, using the NANDA, NOC, and NIC taxonomies as criteria. <b>Methods</b>: An observational study was carried out with three simulated clinical cases. Thirty experts, fifty-four nursing professionals, and the ChatGPT model (GPT-4) were included. The experts established the referral plans using the Delphi technique. Responses were evaluated with a validated rubric (EADE-2) and analyzed using nonparametric tests. Professionals’ perceptions on the use of computer systems were also collected. <b>Results</b>: ChatGPT scored significantly higher on several dimensions (<i>p</i> < 0.001) and resolved all three cases in 35 s, compared to an average of 30 min for practitioners. Professionals expressed dissatisfaction with current diagnostic documentation systems. <b>Conclusions</b>: AI demonstrates high potential in optimizing the diagnostic process in nursing, although for its implementation human supervision, ethical aspects and improvements in current systems must be considered to achieve effective integration.https://www.mdpi.com/2039-4403/15/6/186expert panelnursing professionalsartificial intelligencediagnostic process
spellingShingle Ester Gilart
Anna Bocchino
Patricia Gilart-Cantizano
Eva Manuela Cotobal-Calvo
Isabel Lepiani-Diaz
Daniel Román-Sánchez
José Luis Palazón-Fernández
The Integration of AI into the Nursing Process: A Comparative Analysis of NANDA, NOC, and NIC-Based Care Plans
Nursing Reports
expert panel
nursing professionals
artificial intelligence
diagnostic process
title The Integration of AI into the Nursing Process: A Comparative Analysis of NANDA, NOC, and NIC-Based Care Plans
title_full The Integration of AI into the Nursing Process: A Comparative Analysis of NANDA, NOC, and NIC-Based Care Plans
title_fullStr The Integration of AI into the Nursing Process: A Comparative Analysis of NANDA, NOC, and NIC-Based Care Plans
title_full_unstemmed The Integration of AI into the Nursing Process: A Comparative Analysis of NANDA, NOC, and NIC-Based Care Plans
title_short The Integration of AI into the Nursing Process: A Comparative Analysis of NANDA, NOC, and NIC-Based Care Plans
title_sort integration of ai into the nursing process a comparative analysis of nanda noc and nic based care plans
topic expert panel
nursing professionals
artificial intelligence
diagnostic process
url https://www.mdpi.com/2039-4403/15/6/186
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