Dealing with Medical Knowledge: Computers in Clinical Decision Making

302 Pages·1994·27.647 MB·English

by  Tibor Deutsch, Ewart Carson, Endre Ludwig (auth.)

Dealing with
Medical Knowledge
Computers in Clinical Decision Making
Dealing with
Medical Knowledge
Computers in Clinical Decision Making
Tibor Deutsch
Semmelweis University of Medicine
Budapest, Hungary
Ewart Carson
City University
London, England
and
Endre Ludwig
P€terfy Teaching Hospital
Budapest, Hungary
Springer Science+Business Media, LLC
Library of Congress Cataloging-in-Publication Data
On file
ISBN 978-1-4757-9953-8 ISBN 978-1-4757-9951-4 (eBook)
DOI 10.1007/978-1-4757-9951-4
© 1994 Springer Science+Business Media New York
Originally published by Plenum Press, New York in 1994
Softcover reprint of the hardcover 1st edition 1994
All rights reserved
No part of this book may be reproduced s,tored in a retrieval system, or transmitted in any form
or by any means, electronic, mechanical, photocopying, microfilming, recording, or otherwise,
without written permission from the Publisher
Preface
"Dealing with complexity" is a phrase that neatly summarizes many of the issues
associated with clinical decision making and problem solving. In fact, Dealing
with Complexity was the very title of another book published by Plenum, one of the
authors of which contributed to this new volume. That first book was devoted
entirely to the nature of complex problems in various fields of science, manage
ment, and technology and the approaches that are available for their resolution
(Flood and Carson, 1993). In some respects, this book is a descendant of the earlier
volume in that it focuses on problems that clinicians are facing when making
clinical decisions.
The individual clinician, or members of the clinical team, are required to
process and interpret, in context, large quantities of complex data relating to the
patient, often derived from diverse sources. In this way, data are transformed into
information that is used to effect the appropriate decision, be it in relation to
diagnosis, treatment, or monitoring the progress of the patient over a period of
time.
The complexity of the issues involved is such that the ability to make
appropriate decisions and solve problems is limited to those who have the
necessary expertise. However, the impact of the information revolution means that
clinical decision making and problem solving can now be assisted using
knowledge-based approaches; this decision-assisting capability is implemented on
computers, which are providing increasingly powerful performance at ever
decreasing real cost. In this way, the ability to make decisions can be made more
widely available, in effect enabling the individual to operate at a higher level of
expertise.
This role of knowledge-based techniques in relation to clinical decision
making is one facet of the growing subject of medical informatics. Medical
informatics, in essence, is the application of information science and technology in
clinical research and education and in clinical practice. The concepts, methods,
and techniques embedded within knowledge-based approaches constitute power
ful aids to clinical decision making, particularly when set within a clear control
system framework, with its emphasis on the patient-clinician feedback model.
v
vi Preface
In order to develop and disseminate these knowledge-based approaches in
relation to clinical decision making and problem solving, there is the need for an
interdisciplinary forum drawing together on the one hand clinicians and on the
other engineers and computer scientists. There is the need for greater understand
ing on the part of both groups. For the clinician, there is the need to understand the
nature of these new approaches and the way in which they can be used to assist in
clinical decision making when set within the control-system framework. For the
engineer and computer scientist, there is the need to understand the true nature
of the clinical problems that require solution using these approaches.
It is these twin needs that this book addresses. This is achieved first by
providing a guided tour (from a bird's-eye perspective) that highlights the general
nature of the problems and issues involved and then by effectively dropping in on a
number of places of interest on this tour in order to examine some representative
clinical examples in greater detail.
This book differs from the likes of the classic medical informatics compendia
of Gremy (1987), Shortliffe and Perrault (1990), and Degoulet et al. (1992) and
focuses only on that area of medical informatics that is concerned with clinical
decision making. This means that topics such as signal analysis, image process
ing, and biomedical engineering in general are deliberately not included.
The manner in which the subject matter is presented is different from that
adopted in a number of edited volumes that are available (for example, Szolovits,
1982; Carson and Cramp, 1985; Reggia and Thhrim, 1985; P. L. Miller, 1988).
They convey information by presenting some of the classic papers of this field
rather than providing a systematic discussion. The aim of this book differs also
from those that focus either on a specific area of medical decision making, such as
medical diagnosis (for inst~ce, Warner, 1978; Sox et al., 1988) or on using a
specific method, such as statistical decision making (Grenier, 1990), decision trees
(Weinstein and Fineberg, 1980), fuzzy logic (Fieschi, 1990), or artificial intel
ligence (de Lotto and Stefanelli, 1985; Keravnou, 1992).
In contrast to these other works with their own particular approaches to
presenting the subject, this volume is intended to provide a systematic and unified
presentation of problems associated with clinical decision making and methods
that can be used in assisting their solution. It should be noted, however, that it
is not a technical treatise on decision-making methods. Rather, it aims to convey
the flavor of clinical decision-making issues in terms of frameworks and ap
proaches that are available, accessible, and relevant.
Central to the theme of the book is the synergy that results from the bringing
together of the classic control-system approach, which views the interaction
between clinician and patient in terms of a feedback model, with the symbolic
approaches that have been central to developments in artificial intelligence. Stress
has been placed on concepts and examples. This means that only a very limited
mathematical treatment is included. Equally, the examples considered essentially
Preface vii
represent classes of clinical problems rather than provide complete coverage of the
clinical domain. Again, within the chosen examples, it is the informatics "mes
sage" that is highlighted rather than the use of the "medium," which is the
computer. There is no lengthy computer code in the text.
Medical knowledge can be likened to a "living" system in which the
concepts (diseases, symptoms, drugs, etc.) constitute its anatomy while the means
of dealing with such concepts, that is, information processing and decision
making, correspond to different "metabolic" and "physiological" processes
(Schoolman, 1982). A particular feature of the style of presentation adopted is to
regard clinical decision making as an information-processing "living system" that
has its anatomy (structure of concepts that are used), physiology (how it is to be
manipulated), and pathophysiology (what happens if it is manipulated inappro
priately). Problem solving also requires intensive knowledge "metabolism"
whereby pieces of concepts and relations (as catabolized and stored products) are
resynthesized (anabolized) when more complex constructs and reasoning are
needed. The techniques described in this volume in some respects resemble the
"enzymes" that facilitate this knowledge synthesis needed for solving medical
problems.
Chapter 1 introduces a number of the features of the control-system approach
through the description of a clinical case report. This serves to motivate the reader
for whom such an approach might be unfamiliar. Chapter 2 focuses on the
fundamentals of systems and control, introducing concepts that are highly relevant
as aids to understanding the complex nature of clinical situations. This is followed,
in Chapter 3, by a general discussion of data and knowledge representation and
manipulation, outlining general methodologies that can be used when tackling
clinical information-processing and problem-solving tasks. The tools that emerge
from these two chapters are then employed in Chapter 4 in analyzing clinical
activity (the therapeutic process).
The anatomy of medical knowledge is the focus of Chapter 5, providing a
formalism in terms of which changes in patient state and/or function can be
analyzed and of which schemes for intervention (control) can be assessed. This
leads naturally on to Chapter 6, which discusses methods for computer-assisted
clinical decision making.
Chapters 7-9 focus on clinical application. The several types of clinical
activity are represented, including diagnosis and assessment of the patient's state,
therapy planning, and the monitoring of ongoing therapeutic regimes. Chapter 7
describes methods for medical diagnosis. Chapter 8 focuses on the planning of
therapeutic action, including the computer-assisted planning of drug dosage,
Finally, Chapter 9, as a "firework," provides examples of clinical problem solving
in a particular medical field, diabetes management, that serve to illustrate how
wide is the range over which doctors may find decision-support tools to be useful
assistants.
viii Preface
In preparing this book for publication, we are indebted to many of our
colleagues who, in their various ways, have helped to bring it to reality. First, we
are grateful to members of our own respective institutions for having encouraged
and supported an endeavor in applying knowledge-based approaches, within a
control-system framework, to a range of clinical problems. We also wish to thank
those colleagues who have worked with us in many projects over the past seven
years. Much of the material in this book is the result of collaboration between
systems scientists, engineers and computer scientists, and members of the relevant
clinical professions. To all those who have catalyzed and supported this fruitful
interdisciplinary activity we extend our sincere gratitude.
Special thanks must be expressed to a number of friends and colleagues,
Derek Cramp, Ivan Futo, Istvan Hermanyi, Roman Hovorka, Eldon Lehmann,
Emma Nicolosi, Abdol Roudsari, Peter Sonksen, Ron Summers, and Gyula
Tamas, who have worked with one or more of us and whose stimulating ideas and
enthusiasm have helped to maintain the momentum of our progress.
The preparation of this book would not have been possible without regular
travel between Budapest and London. Funding for these visits was provided by the
British Council, the Science and Engineering Research Council of the United
Kingdom, and the Wellcome Trust. We are most grateful to all of them for their
generous support.
The authors are indebted to Csaba Stanka for his technical assistance in
preparing the manuscript and the figures.
TIBOR DEUTSCH
EWART R. CARSON
ENDRE LuDWIG
Budapest and London, February 1994
Contents
1. Introduction
1. 1. Case Report ........................................... .
1.1.1. Patient History and Clinical Data ................... 1
1.1.2. Decisions, Actions, and Patient Response. . . . . . . . . . . . . 2
1.1.3. Commentary .................................... 4
1.2. Role of Computers in the Therapeutic Process ................ 5
2. Systems and Control
2.1. Introduction............................................ 11
2.2. Basic Concepts in Systems Dynamics ................... . . . . 11
2.3. Systems and Modeling Methodology ....................... 14
2.4. Control Loops.......................................... 17
2.5. Clinical Context ........................................ 19
2.6. Summary .............................................. 20
3. Knowledge Representation and Manipulation
3.1. Introduction............................................ 23
3.2. Representing Uncertainty ................................. 24
3.3. Sets .................................................. 26
3.4. Representing Objects and Relationships ..................... 29
3.4.1. Frames......................................... 29
3.4.2. Databases ...................................... 31
3.4.3. Graphs......................................... 32
3.4.4. Logic .......................................... 36
3.5. Representing Dynamic Knowledge ......................... 39
3.6. Manipulating Knowledge ................................. 43
3.6.1. Manipulating Probabilistic Knowledge (Bayes's Rule) ... 44
ix
x Contents
3.6.2. Rule-Based Reasoning ............................ 47
3.6.3. Manipulating Knowledge Stored in Models ........... 52
3.7. Problem Solving ........................................ 54
3.7.1. Knowledge-Based versus Algorithmic Problem Solving 56
3.7.2. Architectures for Knowledge-Based Problem Solving ... 58
3.8. Summary.............................................. 63
4. Analysis of the Therapeutic Process
4.1. Introduction............................................ 65
4.2. Basic Medical Concepts .................................. 67
4.3. Describing the Patient's Illness ............................ 69
4.4. Clinical Problem Solving ................................. 71
4.5. Control-System Model of Therapeutics. . . . . . . .. . . . . . . . . . . . . . 74
4.6. The Therapeutic Process Seen from a Systems Perspective ..... 79
4.7. Summary.............................................. 81
s.
Anatomy of Medical Knowledge
5.1. Introduction............................................ 83
5.2. Declarative Medical Knowledge ........................... 84
5.2.1. Coding Schemes ................................. 85
5.3. Representing Preclinical Knowledge ........................ 87
5.3.1. Anatomical Classification. . . . . . . . . . . . . . . . . . . . . . . . . . 87
5.3.2. Describing Physiological Systems. . . . . . . . . . . . . . . . . . . 88
5.4. Representing Clinical Knowledge .......................... 95
5.4.1. Pathophysiology-Based Organizations of Clinical
Knowledge ..................................... 96
5.4.2. Findings and Pathophysiological States. . . . . . . . . . . . . . . 96
5.4.3. Diseases........................................ 101
5.4.4. Tests and Therapies .............................. 105
5.4.5. Diseases as System FauIts ......................... 106
5.4.6. Representing Case-Based (Associational) Clinical
Knowledge ..................................... 110
5.4.7. Characterizing Diagnostic Tests . . . . . . . . . . . . . . . . . . . . . 113
5.5. Suminary.............................................. 118
6. Methods for Computer-Assisted Clinical Decisions
6.1. Introduction............................................ 119
6.2. The Need for Assistance in Decision Making. . . . . . . . . . . . . . . . . 120