Conceptual framework of knowledge management for ethical decision-making support in neonatal intensive care.
This research is built on the belief that artificial intelligence estimations need to be integrated into clinical social context to create value for health-care decisions. In sophisticated neonatal intensive care units (NICUs), decisions to continue or discontinue aggressive treatment are an integral part of clinical practice. High-quality evidence supports clinical decision-making, and a decision-aid tool based on specific outcome information for individual NICU patients will provide significant support for parents and caregivers in making difficult "ethical" treatment decisions. In our approach, information on a newborn patient's likely outcomes is integrated with the physician's interpretation and parents' perspectives into codified knowledge. Context-sensitive content adaptation delivers personalized and customized information to a variety of users, from physicians to parents. The system provides structuralized knowledge translation and exchange between all participants in the decision, facilitating collaborative decision-making that involves parents at every stage on whether to initiate, continue, limit, or terminate intensive care for their infant.
Frize
Monique
M
Systems and Computer Engineering, Carleton University, Ottawa, ON KlS 5B6, Canada. mfrize@connect.carleton.ca
Yang
Lan
L
Walker
Robin C
RC
O'Connor
Annette M
AM
D001185:Artificial Intelligence; D003659:Decision Making, Organizational; D004992:Ethics, Medical; D006801:Humans; D007231:Infant, Newborn; D015931:Intensive Care, Neonatal / Q000458:organization & administration*; D014584:User-Computer Interface