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Decision Modeling Techniques

Decision Modeling Techniques. HINF 371 - Medical Methodologies Session 3. Objective. To review decision modeling techniques and discuss their use in healthcare decision making. Reading.

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Decision Modeling Techniques

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  1. Decision Modeling Techniques HINF 371 - Medical Methodologies Session 3

  2. Objective • To review decision modeling techniques and discuss their use in healthcare decision making

  3. Reading • Roberts M S and Sonnenberg F A (2000) Chapter 2: Decision Modeling Techniques, in Chapman G B and Sonnenberg F A (eds) Decision Making In Health Care: Theory, Psychology and Applications, Cambridge University Press, USA,

  4. Evidence Preparation Engine where data is translated into information

  5. Why do we need them? • To create a quantitative representation of clinical choices • To compare alternatives and results of choices • To integrate data from various sources to describe a clinical situation • To simulate trial results to the whole population

  6. Requirements for a Decision Model • Perspective: identification of whose perspective has been used to develop the model • Context: who is involved, what conditions, what interventions • Complexity (or granularity): what should be the level of detail • Time horizon

  7. Simple Decision Tree Chance Node Outcome 1 Value 1 (U1) p1 Choice 1 Decision Node p2 Outcome 2 Value 2 (U2) Total = 1 Outcome 3 Value 3 (U3) p3 Choice 2 p4 Outcome 4 Value 4 (U4)

  8. HIV+ LERx p1 Test + p2 HIV- LETox Test + LERx HIV+ p1 LE LateRx HIV+ p3 Test - Test - p2 p4 HIV- LETox LE Test + LE LateRx p3 HIV- Test - p4 LE Terminology Sensitivity True Positive False Positive False Negative True Negative Specificity

  9. HIV+ LERx p1 Test + p2 HIV- LETox HIV+ LE LateRx p3 Test - p4 HIV- LE Example 3.5444 0.9988 3.5 QALYs 0.4856 0.0012 39.4 QALYs 39.2050 Screen 2.75 QALYs 21.89 0.5144 40.3 QALYs 21.5250 HIV+ LE Late Rx 2.75 QALYs 0.5 21.53 p5 No Screen p6 LE 40.3 QALYs 0.5 HIV-

  10. Influence Diagrams HIV Status Test Result Screen for HIV Yes/No Life Expec Treat for HIV Yes/No

  11. Test + LERx p1 HIV+ Test - p2 LETox Test + LE LateRx p3 HIV- Test - p4 LE Sensitivity Analysis

  12. Markov Processes • Iterative in time, can be repeated until everybody in the absorbing state • Based on the probabilities of change in status • Three states • Recurrent state • Transient state • Absorbing state

  13. Asymptomatic HIV+ p1 p1 p3 p2 AIDS DEAD P6 p5 Markov Processes p1 HIV+ HIV+ p2 AIDS p3 DEAD p4 AIDS AIDS p5 DEAD p4 DEAD DEAD P6

  14. HIV+ LERx p1 Test + p2 HIV- LETox HIV+ AIDS AIDS AIDS LE LateRx p3 Test - HIV+ HIV+ HIV+ DEAD DEAD DEAD p4 HIV- LE HIV- DEAD Screen HIV- DEAD HIV+ LE Late Rx p5 No Screen p6 LE HIV- DEAD HIV-

  15. Alternatives to Markov Processes • Markov Processes has no memory and based on discrete snapshots in time • Semi Markov Processes – time is continuous, one does not move to the next another stage in the next term and measures holding times • Individual Simulations as a solution: simulates individuals’ travel • Dynamic influence diagrams creates a new influence diagram for the next cycle • Discrete event simulation: what is possible to do

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