Health Care Professionals' and Parents' Perspectives on the Use of AI for Pain Monitoring in the Neonatal Intensive Care Unit: Multisite Qualitative Study.

AI HCP NICU acceptance adoption artificial intelligence assessment attitude attitudes babies baby digital health experience experiences health care professional health care professionals health technologies health technology infant infants intensive care interview interviews neonatal neonatal intensive care unit neonate neonates newborn newborns opinion pain pain management pain monitoring parent parents pediatric pediatrics perception perceptions perspective perspectives premature preterm preterm infant willingness

Journal

JMIR AI
ISSN: 2817-1705
Titre abrégé: JMIR AI
Pays: Canada
ID NLM: 9918645789006676

Informations de publication

Date de publication:
09 Feb 2024
Historique:
received: 02 08 2023
accepted: 17 12 2023
revised: 24 11 2023
medline: 14 6 2024
pubmed: 14 6 2024
entrez: 14 6 2024
Statut: epublish

Résumé

The use of artificial intelligence (AI) for pain assessment has the potential to address historical challenges in infant pain assessment. There is a dearth of information on the perceived benefits and barriers to the implementation of AI for neonatal pain monitoring in the neonatal intensive care unit (NICU) from the perspective of health care professionals (HCPs) and parents. This qualitative analysis provides novel data obtained from 2 large tertiary care hospitals in Canada and the United Kingdom. The aim of the study is to explore the perspectives of HCPs and parents regarding the use of AI for pain assessment in the NICU. In total, 20 HCPs and 20 parents of preterm infants were recruited and consented to participate from February 2020 to October 2022 in interviews asking about AI use for pain assessment in the NICU, potential benefits of the technology, and potential barriers to use. The 40 participants included 20 HCPs (17 women and 3 men) with an average of 19.4 (SD 10.69) years of experience in the NICU and 20 parents (mean age 34.4, SD 5.42 years) of preterm infants who were on average 43 (SD 30.34) days old. Six themes from the perspective of HCPs were identified: regular use of technology in the NICU, concerns with regard to AI integration, the potential to improve patient care, requirements for implementation, AI as a tool for pain assessment, and ethical considerations. Seven parent themes included the potential for improved care, increased parental distress, support for parents regarding AI, the impact on parent engagement, the importance of human care, requirements for integration, and the desire for choice in its use. A consistent theme was the importance of AI as a tool to inform clinical decision-making and not replace it. HCPs and parents expressed generally positive sentiments about the potential use of AI for pain assessment in the NICU, with HCPs highlighting important ethical considerations. This study identifies critical methodological and ethical perspectives from key stakeholders that should be noted by any team considering the creation and implementation of AI for pain monitoring in the NICU.

Sections du résumé

BACKGROUND BACKGROUND
The use of artificial intelligence (AI) for pain assessment has the potential to address historical challenges in infant pain assessment. There is a dearth of information on the perceived benefits and barriers to the implementation of AI for neonatal pain monitoring in the neonatal intensive care unit (NICU) from the perspective of health care professionals (HCPs) and parents. This qualitative analysis provides novel data obtained from 2 large tertiary care hospitals in Canada and the United Kingdom.
OBJECTIVE OBJECTIVE
The aim of the study is to explore the perspectives of HCPs and parents regarding the use of AI for pain assessment in the NICU.
METHODS METHODS
In total, 20 HCPs and 20 parents of preterm infants were recruited and consented to participate from February 2020 to October 2022 in interviews asking about AI use for pain assessment in the NICU, potential benefits of the technology, and potential barriers to use.
RESULTS RESULTS
The 40 participants included 20 HCPs (17 women and 3 men) with an average of 19.4 (SD 10.69) years of experience in the NICU and 20 parents (mean age 34.4, SD 5.42 years) of preterm infants who were on average 43 (SD 30.34) days old. Six themes from the perspective of HCPs were identified: regular use of technology in the NICU, concerns with regard to AI integration, the potential to improve patient care, requirements for implementation, AI as a tool for pain assessment, and ethical considerations. Seven parent themes included the potential for improved care, increased parental distress, support for parents regarding AI, the impact on parent engagement, the importance of human care, requirements for integration, and the desire for choice in its use. A consistent theme was the importance of AI as a tool to inform clinical decision-making and not replace it.
CONCLUSIONS CONCLUSIONS
HCPs and parents expressed generally positive sentiments about the potential use of AI for pain assessment in the NICU, with HCPs highlighting important ethical considerations. This study identifies critical methodological and ethical perspectives from key stakeholders that should be noted by any team considering the creation and implementation of AI for pain monitoring in the NICU.

Identifiants

pubmed: 38875686
pii: v3i1e51535
doi: 10.2196/51535
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e51535

Informations de copyright

©Nicole Racine, Cheryl Chow, Lojain Hamwi, Oana Bucsea, Carol Cheng, Hang Du, Lorenzo Fabrizi, Sara Jasim, Lesley Johannsson, Laura Jones, Maria Pureza Laudiano-Dray, Judith Meek, Neelum Mistry, Vibhuti Shah, Ian Stedman, Xiaogang Wang, Rebecca Pillai Riddell. Originally published in JMIR AI (https://ai.jmir.org), 09.02.2024.

Auteurs

Nicole Racine (N)

School of Psychology, University of Ottawa, Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada.

Cheryl Chow (C)

Department of Psychology, York University, Toronto, ON, Canada.

Lojain Hamwi (L)

Department of Psychology, York University, Toronto, ON, Canada.

Oana Bucsea (O)

Department of Psychology, York University, Toronto, ON, Canada.

Carol Cheng (C)

Department of Nursing, Mount Sinai Hospital, Toronto, ON, Canada.

Hang Du (H)

Department of Mathematics and Statistics, York University, Toronto, ON, Canada.

Lorenzo Fabrizi (L)

Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.

Sara Jasim (S)

Department of Psychology, York University, Toronto, ON, Canada.

Lesley Johannsson (L)

Mount Sinai Hospital, Toronto, ON, Canada.

Laura Jones (L)

Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.

Maria Pureza Laudiano-Dray (MP)

Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.

Judith Meek (J)

Neonatal Care Unit, University College London Hospitals, London, United Kingdom.

Neelum Mistry (N)

Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.

Vibhuti Shah (V)

Department of Pediatrics, Mount Sinai Hospital, Toronto, ON, Canada.

Ian Stedman (I)

School of Public Policy and Administration, York University, Toronto, ON, Canada.

Xiaogang Wang (X)

Department of Mathematics and Statistics, York University, Toronto, ON, Canada.

Rebecca Pillai Riddell (RP)

Department of Psychology, York University, Toronto, ON, Canada.

Classifications MeSH