Abstract
As the number of signals and data to be handled grows in intensive care unit, it is necessary to design more powerful computing systems that integrate and summarize all this information. The manual input of data as e.g. clinical signs and drug prescription and the synthetic representation of these data requires an ever more sophisticated user interface. The introduction of knowledge bases in the data management allows to conceive contextual interfaces.
The objective of this paper is to show the importance of the design of the user interface, in the daily use of clinical information system. Then we describe a methodology that uses the man-machine interaction to capture the clinician knowledge during the clinical practice. The different steps are the audit of the user's actions, the elaboration of statistic models allowing the definition of new knowledge, and the validation that is performed before complete integration. A part of this knowledge can be used to improve the user interface. Finally, we describe the implementation of these concepts on a UNIX platform using OSF/MOTIF graphical interface.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Explore related subjects
Discover the latest articles and news from researchers in related subjects, suggested using machine learning.References
Mora FA, Passariello G, Carrault G, Le Pinchon JP. Intelligent patient monitoring and management systems: a review. IEEE Engineering in Medicine and Biology 1993; 12(4): 23–33.
Thull B, Popp HJ, Rau G. Man-machine interaction in critical care settings. IEEE Engineering in Medicine and Biology 1993; 12(4): 42–9.
Kari A, Ruokonen E, Takala J. Comparison of acceptance and performance of automated and manual data management systems in intensive care. Int J Clin Mon Comput 1990; 7: 157–62.
Hammond J, Johnson HM, Varas R, Ward CG. A qualitative comparison of paper flowsheets vs a computer based clinical information system. Chest 1991; 99: 155–7.
Uckun S, Dawant BM, Lindstrom. Model-based diagnosis in intensive therapy: the YAQ approach. Artificial Intelligence in Medicine 1993; 5: 31–48.
Hayes-Roth B, Washington R, Ash D, Hewett R, Collinot A, Vina A, Seiver. Guardian: a prototype intelligent agent for intensive care monitoring. Artificial Intelligence in Medicine 1992; 4: 165–85.
Windyga P, Almeida D, Passariello G, Mora-Ciangherotti FA, Coatrieux JL. Knowledge-based approach to the management of serious arrhythmia in the CCU. Med & Biol Eng & Comput 1991; 29: 254–60.
Jamieson PW. A model for diagnosing and explaining multiple disorders. Comput and Biomed research 1991; 24: 307–21.
User's Guide, OSF/MOTIFTM Guides, ed. Prentice Hall 1990.
Style Guide, OSF/MOTIFTM Guides, ed. Prentice Hall 1991.
Hunter J, Chambrin MC, Collinson P, Hedlund A, Groth T, Kalli S, Kari A, Lenoudias G, Ravaux P, Ross D, Salle JM, Sukuvaara T, Summers R, Zaar B: INFORM: Integrated support for decisions and activities in intensive care. Int J Clin Mon Comput 1991; 8: 189–99.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Chambrin, M.C., Ravaux, P., Jaborska, A. et al. Introduction of knowledge bases in patient's data management system: Role of the user interface. J Clin Monit Comput 12, 11–16 (1995). https://doi.org/10.1007/BF01142440
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/BF01142440