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Defining information needs in neonatal resuscitation with work domain analysis.

Authors :
Zestic, Jelena
Sanderson, Penelope
Dawson, Jennifer
Liley, Helen
Source :
Journal of Clinical Monitoring & Computing; Aug2021, Vol. 35 Issue 4, p689-710, 22p
Publication Year :
2021

Abstract

Objective: To gain a deeper understanding of the information requirements of clinicians conducting neonatal resuscitation in the first 10 min after birth. Background: During the resuscitation of a newborn infant in the first minutes after birth, clinicians must monitor crucial physiological adjustments that are relatively unobservable, unpredictable, and highly variable. Clinicians' access to information regarding the physiological status of the infant is also crucial to determining which interventions are most appropriate. To design displays to support clinicians during newborn resuscitation, we must first carefully consider the information requirements. Methods: We conducted a work domain analysis (WDA) for the neonatal transition in the first 10 min after birth. We split the work domain into two 'subdomains'; the physiology of the neonatal transition, and the clinical resources supporting the neonatal transition. A WDA can reveal information requirements that are not yet supported by resources. Results: The physiological WDA acted as a conceptual tool to model the exact processes and functions that clinicians must monitor and potentially support during the neonatal transition. Importantly, the clinical resources WDA revealed several capabilities and limitations of the physical objects in the work domain—ultimately revealing which physiological functions currently have no existing sensor to provide clinicians with information regarding their status. Conclusion: We propose two potential approaches to improving the clinician's information environment: (1) developing new sensors for the information we lack, and (2) employing principles of ecological interface design to present currently available information to the clinician in a more effective way. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13871307
Volume :
35
Issue :
4
Database :
Complementary Index
Journal :
Journal of Clinical Monitoring & Computing
Publication Type :
Academic Journal
Accession number :
151457265
Full Text :
https://doi.org/10.1007/s10877-020-00526-7