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Computerisation and decision making in neonatal intensive care: a cognitive engineering investigation

Alberdi, E., Gilhooly, K. J., Hunter, J. , Logie, R., Lyon, A., McIntosh, N. & Reiss, J. (2000). Computerisation and decision making in neonatal intensive care: a cognitive engineering investigation. Journal of Clinical Monitoring and Computing, 16(2), pp. 85-94. doi: 10.1023/A:1009954623304


This paper reports results from a cognitive engineering study that looked at the role of computerised monitoring in neonatal intensive care. A range of methodologies was used: interviews with neonatal staff, ward observations, and experimental techniques. The purpose was to investigate the sources of information used by clinicians when making decisions in the neonatal ICU. It was found that, although it was welcomed by staff, computerised monitoring played a secondary role in the clinicians' decision making (especially for junior and nursing staff) and that staff used the computer less often than indicated by self-reports. Factors that seemed to affect staff use of the computer were the lack (or shortage) of training on the system, the specific clinical conditions involved, and the availability of alternative sources of information. These findings have relevant repercussions for the design of computerised decision support in intensive care and suggest ways in which computerised monitoring can be enhanced, namely: by systematic staff training, by making available online certain types of clinical information, by adapting the user interface, and by developing intelligent algorithms.

Publication Type: Article
Additional Information: The final publication is available at Springer via
Publisher Keywords: Attitude to Computers, Data Collection, Data Display, Decision Support Systems, Clinical, Humans, Infant, Newborn, Intensive Care Units, Neonatal, Medical Staff, Hospital, Monitoring, Physiologic, Neonatal Nursing, Task Performance and Analysis
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RG Gynecology and obstetrics
Departments: School of Science & Technology > Computer Science > Software Reliability
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