Modeling Method Decision Tree

Modeling MethodDecision Tree

Decision tree: 4 basic elements

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http://www.excelquant.com/decision-tree-analysis-in-excel/

https://msdn.microsoft.com/en-us/library/ms175312.aspx

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The process of the analysis is:

1. Structure the problem: identify alternatives, list possible outcomes, represent sequence of events

2. Assign probabilities to all chance events

3. Assign utility, or other values, to all outcomes

4. Evaluate the expected utility, or other values, and cost of each choice

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Parameters

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Name Description Root Definition Low HighpEradicateRad Prob tumor is eradicated by radiation 0.6 0 1pEradicateRadSurg Prob tumor is eradicated by radiation and surgery 0.8 0 1cRadiation Cost of radiation 30K 25000 35000cSurgery Cost of surgery 50K 40000 60000cFollowupAnnual Cost of followup per year 2K 1800 2200effEradicated Life expectancy if tumor eradicated 10 8 15effNotEradicated Life expectancy if tumor is not eradicated 3 0 3

Step 1: structure the problem

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Step 2: assign probabilities to all chance events

Note: sum of probabilities at each chance node is equal to 1

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Step 3: assign utility, or other values, to all outcomes

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Step 4: evaluate the expected utility, or other values, and cost of each choice

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(0.6 x 10) + (0.4 x 3) LYs

(0.8 x 10) + (0.2 x 3) LYs

(0.6 x 50K) + (0.4 x 36K) THB

(0.6 x 100K) + (0.4 x 96K) THB

ICER Calculation

(0.6 x 10) + (0.4 x 3) LYs= 6 + 1.2 = 7.2

(0.8 x 10) + (0.2 x 3) LYs= 8 + 0.6 = 8.6

(0.6 x 50K) + (0.4 x 36K) THB= 30,000 + 14,400 = 44,400

(0.8 x 100K) + (0.2 x 96K) THB= 80,000 + 19,200 = 99,200

Cost = 99,200 – 44,400 = 54,800  LY = 8.6 – 7.2 = 1.4 

= 39,142.86 THB/LY

Limitations of decision tree are:

1. Conclusion depends heavily on the assumptions, so sensitivity analysis is important

2. Force movement to occur in one direction from left to right

3. Hard to do the model with long cycle time

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TreeAge Pro®Decision Tree

Exercise: Decision tree by TreeAge Pro®- install program - create new decision tree (Ctrl + N)- run sensitivity analysis

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File Projects New project

File Open

File New decision tree or Ctrl + N

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1. Add branch by double click on node

2. Define name

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3. Add node

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Tree Tree Preferences

4. Select tree preferences

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5. Add probabilities

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6. Change “Terminal node” and edit payoffs

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8. Roll back

Analysis Roll Back

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Define variables (parameters)

Window views variable properties

Add variable

Edit variable

Delete variable

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Define variables (parameters)

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Edit probability

Add “#” to

sum prob. = 1

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TreeAge Pro®Markov model

Exercise: develop Markov model by TreeAge Pro®- install program - create new decision tree (Ctrl + N)- run sensitivity analysis

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Convert to STD (State Transition Diagram)

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1. Add branch by double click on node

2. Add Markov node by drag and drop from Palette

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3. Define name and insert node for Markov

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4. Complete chance nodes as shown in State Transition Diagram

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5. Assign terminal nodes for each branch

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6. Add variable properties

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7. Add variables in the model

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8. At Markov nodeAnalysis Expected value

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Collapse subtree : Ctrl + J

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TreeAge Pro®Tornado Diagram

Exercise: Decision tree by TreeAge Pro®- install program - create new decision tree (Ctrl + N)- run sensitivity analysis

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Tornado diagramAnalysis Sensitivity analysis Tornado diagram

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TreeAge Pro®Monte Carlo Simulation

1. Define definitions

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2. Define variable properties

3. Run: Analysis Monte Carlo Simulation Sampling

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ICER distribution (Charts -> scatter plots -> ICE scatter)

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Acceptability curve (Charts -> CE acceptability)

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