Decision Modeling Techniques HINF 371 - Medical Methodologies Session 3.
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Transcript of Decision Modeling Techniques HINF 371 - Medical Methodologies Session 3.
Decision Modeling Decision Modeling TechniquesTechniques
HINF 371 - Medical MethodologiesHINF 371 - Medical MethodologiesSession 3Session 3
Objective Objective
To review decision modeling To review decision modeling techniques and discuss their use techniques and discuss their use in healthcare decision makingin healthcare decision making
ReadingReading
Roberts M S and Sonnenberg F A (2000) Roberts M S and Sonnenberg F A (2000) Chapter 2: Decision Modeling Techniques, in Chapter 2: Decision Modeling Techniques, in Chapman G B and Sonnenberg F A (eds) Chapman G B and Sonnenberg F A (eds) Decision Making In Health Care: Theory, Decision Making In Health Care: Theory, Psychology and Applications, Cambridge Psychology and Applications, Cambridge University Press, USA, University Press, USA,
Why do we need them?Why do we need them?
To create a quantitative To create a quantitative representation of clinical choicesrepresentation of clinical choices
To compare alternatives and To compare alternatives and results of choicesresults of choices
To integrate data from various To integrate data from various sources to describe a clinical sources to describe a clinical situationsituation
To simulate trial results to the To simulate trial results to the whole populationwhole population
Requirements for a Requirements for a Decision ModelDecision Model
Perspective: identification of Perspective: identification of whose perspective has been whose perspective has been used to develop the modelused to develop the model
Context: who is involved, what Context: who is involved, what conditions, what interventionsconditions, what interventions
Complexity (or granularity): what Complexity (or granularity): what should be the level of detailshould be the level of detail
Time horizonTime horizon
Simple Decision TreeSimple Decision Tree
Value 1 (U1)
Value 2 (U2)
Value 3 (U3)
Value 4 (U4)
Outcome 1
Outcome 2
Outcome 3
Outcome 4
p1
p2
p3
Choice 1
Choice 2
Total = 1
Decision Node
Chance Node
p4
TerminologyTerminology
LE LateRx
LETox
Test +
Test -
p1
p2
p3
p4
LERx
LE
HIV+
HIV+
HIV-
HIV-
LE LateRx
LETox
HIV+
HIV-
p1
p2
p3
p4
LERx
LE
Test +
Test +
Test -
Test -
Sensitivity
Specificity
True Positive
False Positive
False Negative
True Negative
ExampleExample
LE Late Rx
LE
HIV+
HIV-
Screen
No Screen
LE LateRx
LETox
Test +
Test -
p1
p2
p3
p4
LERx
LE
HIV+
HIV+
HIV-
HIV-
p5
p6
40.3 QALYs
40.3 QALYs
3.5 QALYs
39.4 QALYs
2.75 QALYs
2.75 QALYs
0.9988
0.0012
0.4856
0.5144
0.5
0.5
39.2050
3.5444
21.5250
21.89
21.53
Influence DiagramsInfluence Diagrams
Screen for HIV
Yes/No
Treat for HIV
Yes/No
Test Result
HIVStatus
Life Expec
Sensitivity AnalysisSensitivity Analysis
LE LateRx
LETox
HIV+
HIV-
p1
p2
p3
p4
LERx
LE
Test +
Test +
Test -
Test -
Markov ProcessesMarkov Processes
Iterative in time, can be repeated Iterative in time, can be repeated until everybody in the absorbing until everybody in the absorbing statestate
Based on the probabilities of Based on the probabilities of change in statuschange in status
Three statesThree states Recurrent stateRecurrent state Transient stateTransient state Absorbing stateAbsorbing state
Markov ProcessesMarkov Processes
p4
HIV+
AIDS
DEAD
HIV+
AIDS
DEAD
AIDS
DEAD
DEAD
p1
AsymptomaticHIV+
AIDS DEAD
p1
p2
p3
p5
P6
p1
p2
p3
p4
p5
P6
LE Late Rx
LE
HIV+
HIV-
Screen
No Screen
LE LateRx
LETox
Test +
Test -
p1
p2
p3
p4
LERx
LE
HIV+
HIV+
HIV-
HIV-
p5
p6
HIV+
AIDS
DEAD
HIV+
AIDS
DEAD
HIV+
AIDS
DEAD
HIV- DEAD
HIV- DEAD
HIV- DEAD
Alternatives to Markov Alternatives to Markov ProcessesProcesses
Markov Processes has no memory and Markov Processes has no memory and based on discrete snapshots in timebased on discrete snapshots in time
Semi Markov Processes – time is Semi Markov Processes – time is continuous, one does not move to the continuous, one does not move to the next another stage in the next term next another stage in the next term and measures holding timesand measures holding times
Individual Simulations as a solution: Individual Simulations as a solution: simulates individuals’ travelsimulates individuals’ travel
Dynamic influence diagrams creates a Dynamic influence diagrams creates a new influence diagram for the next new influence diagram for the next cyclecycle
Discrete event simulation: what is Discrete event simulation: what is possible to dopossible to do