Uncertainty and Complexity in
Clinical Decisions
Roger Strand, building upon work with Guri
Rørtveit, Yngvild S. Hannestad & Edvin Schei
University of Bergen, Norway
Part I: Risk, strict uncertainty and
ignorance in clinical decisions

Risk, probability and uncertainty

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Why probabilities are important
Why concepts of probability differ
Orthodox and Bayesian views on probability
Ignorance
B. Wynne (1992),
Global Environmental
Change, 2:111-127.
B. Wynne (1992),
Global Environmental
Change, 2:111-127.
Risk, strict uncertainty and ignorance

Risk: when we know (can quantify) the probabilities
(Strict) uncertainty: the event space is known, but
the probabilities cannot be estimated

Frank Knight (1921): Risk, Uncertainty and Profit


There can be no stock market without strict uncertainty
Enlightenment model of reason
Difficult
practical
problem
Decomposition
+
+
+
Small and manageable technical problems
Modern rationality: predict-then-act
Big
practical
problem
Decision
(Solution)
Technical
problem #1
FACTS
VALUES
Facts of sufficient quality

Certainty? (Descartes)
Sources of uncertainty
Sources of uncertainty





Incomplete/imperfect
observations
Incomplete conceptual
frameworks
Inaccurate prescriptions of
known processes (poor
parameterisations etc)
Chaos
Lack of predictability
Uncertainty
Facts of sufficient quality


Certainty? (Descartes)
Probabilities




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Pascal and the Jesuite solution
The plausibility of signs that are often seen (cf Ian Hacking)
The orthodox concept: Probability = Frequency
Frequencies may not exist
Bayesian methods: combining frequencies and
degrees of belief

Problem: Why trust degrees of belief?
Ignorance




Unknown parts of event space
There are the known unknowns, and the unknown
unknowns…
DDT, thalidomide, diethylstilbestrol (DES)
In clinical decisions: Indirect effects that are not
categorised as «adverse effects»


Less energy, less initiative, «brain fog»!? (e.g. statins)
Promiscuity!? (e.g. anti-depressants)
B. Wynne (1992),
Global Environmental
Change, 2:111-127.
Indeterminacy

In clinical decisions:



risks: probabilities known for patient groups
uncertainties: Is my patient representative? Or too
different? Of which relevant peculiarities am I ignorant?
ignorance: What other consequences will my decision
have, than main effect and medically studied side-effects?


Which of these feed back into health?
indeterminacy: How did we define the system and the
problem?
Indeterminacy


Causal chains or networks are open
Different system definition → different




sources of risks
sources of uncertainties
border with ignorance
Trade-offs: narrowing the problem may decrease
uncertainty at the expense of ignorance
Indeterminacy = Complexity ??


Causal chains or networks are open
Different system definition → different



sources of risks
sources of uncertainties
border with ignorance
R. Strand, G. Rørtveit
& E. Schei (2005),
ComplexUs, 2:2-6.
Complex Systems & Human Complexity

Complex systems: “thin” complexity


nonlinear systems of many agents following rules
Agent-based models; complex adaptive systems
paradigms; neural networks; self-organised criticality…
Complex Systems & Human Complexity

Complex systems: “thin” complexity


nonlinear systems of many agents following rules
Human complexity: “thick” complexity


self-awareness, interpretation, self-deception, creativity
self-fulfilling and self-destructive prophecies…
Complex Systems & Human Complexity

Complex systems: “thin” complexity


Human complexity: “thick” complexity



nonlinear systems of many agents following rules
self-awareness, interpretation, self-deception, creativity
self-fulfilling and self-destructive prophecies…
Human complexity and medical care



simplicity: health by a technical fix
complex systems: healthy attractor patterns
human complexity: dialogue, negotiation, mutual learning
The ideal of algorithmic rationality
Big
practical
problem
Decision
(Solution)
Technical
problem #1
FACTS
VALUES