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 implementation of AI for neonatal pain monitoring in the neonatal intensive care unit (NICU) from the perspective of healthcare professionals (HCPs) and parents. This qualitative analysis provides novel data obtained from two large tertiary care hospitals in Canada and the United Kingdom.
OBJECTIVE
To explore the perspectives of HCPs and parents regarding the use of AI for pain assessment in the NICU.
METHODS
20 HCPs and 20 parents of preterm infants were recruited and consented to participate from February 2020 to October 2022 in interviews about implications of AI use for pain assessment in the NICU, potential benefits of the technology, and potential barriers of use.
RESULTS
The 40 participants included 20 HCPs (17 women, 3 men) with an average of 19.4 years of experience in the NICU and 20 parents (mean age 34.4 years) of preterm infants who were on average 42.81 days old. Six themes from the perspective of HCPs were identified: regular use of technology in the NICU, concerns with regards to AI integration, the potential to improve patient care, requirements for implementation, AI as a tool for clinical judgment, and ethical considerations. Seven parent themes included: potential for improved care, increased parental distress, supports for parents regarding AI, the impact on parent engagement, 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
HCPs and parents were generally positive about the potential use of AI for pain assessment in the NICU. For the first time in the literature, this study identifies critical methodological and ethical perspectives from key stakeholders that should be considered by any team considering creation and implementation of AI for pain monitoring in the NICU.