A Real Time Control Architecture for Continuously Managing Patients in a Care Unit

V. Morice; B. Seroussi; J. F. Boisvieux

doi:10.1055/s-0038-1634619

Methods of Information in Medicine, Table of Contents

Methods Inf Med 1995; 34(05): 475-488
DOI: 10.1055/s-0038-1634619

Original Article

Schattauer GmbH

A Real Time Control Architecture for Continuously Managing Patients in a Care Unit

V. Morice

¹Service d’Informatique Médicale, Paris, France

,

B. Seroussi

¹Service d’Informatique Médicale, Paris, France

,

J. F. Boisvieux

¹Service d’Informatique Médicale, Paris, France

› Author Affiliations

Abstract

Abstract:

The monitoring and treatment of patients in a care unit is a complex task in which even the most experienced clinicians can make errors. A hemato-oncology department in which patients undergo chemotherapy asked for a computerized system able to provide intelligent and continuous support in this task. One issue in building such a system is the definition of a control architecture able to manage, in real time, a treatment plan containing prescriptions and protocols in which temporal constraints are expressed in various ways, that is, which supervises the treatment, including controlling the timely execution of prescriptions and suggesting modifications to the plan according to the patient’s evolving condition. The system to solve these issues, called SEPIA, has to manage the dynamic, processes involved in patient care. Its role is to generate, in real time, commands for the patient’s care (execution of tests, administration of drugs) from a plan, and to monitor the patient’s state so that it may propose actions updating the plan. The necessity of an explicit time representation is shown. We propose using a linear time structure towards the past, with precise and absolute dates, open towards the future, and with imprecise and relative dates. Temporal relative scales are introduced to facilitate knowledge representation and access.

Keywords:

Care Monitoring - Time Representation - Real Time Control - Knowledge-based System

Full Text

References

References
1 Miller RA, Masarie Jr FE. The demise of the “Greek Oracle” model for medical diagnostic systems. Meth Inform Med 1990; 29: 1-2.
2 Hickam DH, Shortliffe EH, Bischoff MB, Scott AC, Jacobs CD. A study of the treatment advice of a computer-based cancer chemotherapy protocol advisor. Ann Inter Med 1985; 101: 928-36.
3 Shortliffe EH. Medical expert systems – Knowledge tools for physicians. West J Med 1986; 145: 830-39.
4 Tu SW, Kahn MG, Musen MA, Ferguson JC, Shortliffe EH, Fagan LM. Episodic skeletal plan refinement based on temporal data. Comm ACM 1989; 32: 1439-55.
5 Hayes-Roth B, Washington R, Hewett R, Hewett M. Intelligent monitoring and control. In: Sridharan NS. ed. Proceedings IJCAI. New York: Morgan Kaufmann; 1989: 243-9.
6 Hayes-Roth B, Washington R, Ash D. et al. Guardian: a prototype intelligent agent for intensive-care monitoring. Artif Intell Med 1992; 4: 165-85.
7 Hayes-Roth B. An architecture for adaptive intelligent system. Artif Intell 1995; 72: 329-65.
8 Allen JF. Towards a general theory of action and time. Artif Intell 1984; 23: 123-54.
9 McDermott D. A temporal logic for reasoning about processes and plans. Cognitive Science 1982; 6: 101-55.
10 Shoham Y. Temporal logics in AI: semantical and ontological considerations. Artif Intell 1987; 33: 89-104.
11 Shoham Y. Chronological ignorance: experiments in nonmonotonic temporal reasoning. Artif Intell 1988; 36: 279-331.
12 Vere SA. Planning in time: windows and durations for activities and goals. IEEE PAMI-5 1983; 3: 246-67.
13 Morice V. SAGA: un générateur de plans pour la recherche diagnostique. (Thése de doctorat d’état). Université Paris; 6 1988
14 Kohane IS. Temporal Reasoning in Medical Expert Systems. (PhD thesis). Boston University; 1987
15 Dean TL, McDermott DV. Temporal data base management. Artif Intell 1987; 32: 1-55.
16 Uckun S, Dawant BM, Lindstrom DP. Model-based diagnosis in intensive care monitoring: the YAQ approach. Artif Intell Med 1993; 5: 31-48.
17 Hripcask G, Clayton PD, Pryor TA, Haug P, Wigertz OB, Van der Lei J. The Arden Syntax for Medical Logic Modules. In: Miller RA. ed. Proceedings 14th SCAMC. New York: IEEE Comp Soc Press; 1990: 200-4.
18 McCray AT. The UMLS Semantic Network. In: Proceedings 12th SCAMC. New York: IEEE Comp Soc Press; 1988: 503-7.
19 Lindberg DAB, Humphreys BL. The UMLS knowledge sources. tools for building better user interfaces. In: Miller RA. ed. Proceedings 14th SCAMC. New York: IEEE Comp Soc Press; 1990: 121-5.
20 Séroussi B, Morice V, Dreyfus F, Boisvieux JF. Control theory as a conceptual framework for intensive care monitoring. Artif Intell Med 1995; 7: 155-77.
21 Morice V. Le système SEPIA: documentation. Rapport interne No 94-143 Paris: DIAM; 1994
22 Ferrand P. SESAM: an explanatory medical aid system. In: O’Shea T. ed. Proceedings ECAI. Amsterdam: Elsevier North-Holland; 1984: 13-20.
23 Kuperman GJ, Gardner RM, Pryor TA. HELP: A dynamic hospital information system. In: Orthner HF. ed. Computers and Medicine. New York: Springer-Verlag; 1991
24 Pryor TA, Gardner RM, Clayton PD, Warner HR. The HELP system. J Med Systems 1983; 7: 87-102.
25 Kahn MG, Fagan LM, Tu S. Extensions to the time-oriented database model to support temporal reasoning in medical expert systems. Meth Inform Med 1991; 30: 4-14.
26 Shahar Y, Musen MA. RESUME: a temporal-abstraction system for patient monitoring. Comput Biomed Research 1993; 26: 255-73.
27 Das AK, Musen MA. A temporal query system for protocol-directed decision support. Meth Inform Med 1994; 33: 358-70.
28 Musen MA, Fagan LM, Combs OM, Shortliffe EH. Use of a domain model to drive an interactive knowledge-editing tool. Internat Man-Machine Stud 1987; 26: 105-21.
29 Musen MA. Automated Generation of Model-Based Knowwledge-Acquisition Tools. London: Pitman Publ; 1989
30 Puerta AR, Egar JW, Tu SW, Musen MA. A multiple-method knowledge-acquisition shell for the automatic generation of knowledge-acquisition tools. Knowledge Acquisition 1992; 4: 171-96.