Introduction to Decision Analysis

1. Introduction to Decision Analysis Farrokh Alemi, PhD

2. What is a Decision? • Choice between alternative courses of action • Involves managing uncertain outcomes • Involves tradeoffs between different benefits

3. What is Decision Analysis • Separation of a whole into its component parts • Using a mathematical formula to reconstitute the whole • Decision makers make simple and familiar choices • A formula is used to infer what would the decision maker had preferred to do in the complex choice Subjective data are needed

4. Evaluating Nursing Homes • Possible actions: fining the home, prohibiting admissions, and teaching the home personnel more appropriate use of psychotropic drugs • Many different effects • Constituencies' values should be taken into account • Outcomes cannot be guaranteed

5. Three Sources of Uncertainty • Nature of the problem • Cause and effect  • External events

6. Organizing Thoughts

7. Analysis Simplifies • It may be cost prohibitive to fully consider all elements of a decision. • Ignore some values • Ignore some uncertainties • Simplify the decision enough to meet the decision maker's needs • Do not diminish the usefulness and accuracy of the analysis

8. Purpose of Analysis • Describe problem structure • Reduce uncertainty • Clarify values • Analyze conflict

9. Describe Problem Structure • Help them understand the problem they are addressing: • Individual assumptions about the problem and its causes • Objectives being pursued by each decision maker • Constituencies having different perceptions and values • Options available • Factors that influence the desirability of various outcomes • Principal uncertainties that complicate the problem

10. Reduce Uncertainty • Not sure what will happen if an action is taken • Not sure what state the environment is really in • The analyst uses various tools to forecast the future  • Some clues suggest the target event might occur, other clues suggest the opposite  • The analyst distills the implications of often contradictory clues into a single forecast  • Bayes' theorem

11. Clarify Values • Optimally, analysis provides answers to these questions: •  Which objectives are paramount? • How can an option's performance on a wide range of measuring scales be collapsed into an overall measure of relative value? • Use multi-attribute value (MAV) modeling  • The British National Health Service

12. Analyze Conflict • Model the uncertainties and values that different constituencies see in the same decision  • A contract between an HMO and a clinician  • Conflict can be understood • Steps can be taken to avoid disrupting negotiations 

13. Process of Analysis • Do not conduct an independent analysis  • Decision conference  • Day‑long retreat on structure of the problem • Follow-up day: • possible actions, uncertainties, outcomes, values, and probabilities • Back and forth to the decision maker • Active listening

14. Steps in Cycle of Analysis • Problem exploration • Problem classification • Problem structuring • Quantifying values • Quantifying uncertainties • Analyze & Recommendations • Sensitivity analysis

15. Step 1: Exploring the Problem • Why the decision maker wants to solve a problem? • Problem statement: "Excessive use of drugs to restrain residents." • How should nursing home residents behave? What does restraint mean? Why must residents be restrained? Why are drugs used at all? When are drugs appropriate, and when not? What other alternatives does a nursing home have to deal with problem behavior? • Understand the objective of an organization • Define frequently misunderstood terms • Clarify the practices causing the problem • Understand the reasons for the practice • Separate desirable from undesirable aspects of the practice • What is the agenda? • Protect an individual patient without changing the nursing home • Change the home's general practices • Correct a problem that appears to be industry wide

16. Problem Classification • Which aspects of the decision model should be emphasized? • Uncertainty analysis (diagnosis or prediction) • Value analysis (evaluation) • Both uncertainty and value analysis • Which constituencies should be included? • Where information for the analysis will be obtained? • The analysis could emphasize: • Uncertainty analysis (diagnosis or prediction) • Value analysis (evaluation) • Both uncertainty and value analysis • Single or multiple constituencies

17. Problem Structuring • What the problem is about, why it exists, and whom it affects? • The assumptions and objectives of each affected constituency • A creative set of options for the decision maker • Outcomes to be sought or avoided • The uncertainties that affect the choice of action

18. Quantifying Values • Break complex outcomes into their components and weight the relative value of each component • Cost is typically measured in dollars and may appear straightforward.  But true costs are complex measures and difficult to measure.  • Benefits need to be measured based on various constituencies' preferences.  • Major pitfall: Ignoring values and focusing on costs

19. Quantifying Uncertainties • Measure uncertainty as probability scores • Estimate the chance that the home's chemical restraint practice resulted from ignorance or knowing intention to save money • Additional data are needed • Too much data • The assessment must be divided into manageable components

20. Analysis & Recommendations • Expected utility or expected valueis the weighted average of the values associated with outcomes of each action.  • Two actions are possible: • A1 = Consult • A2 = Stop admission • The possible outcomes are: • Industry changes • Only one home changes • No change

21. Analysis & Recommendations (Continued)

22. Analysis & Recommendations (Continued)

23. Analysis & Recommendations (Continued) • If  pij is the probability of action "i" leading to outcome "j" • Vj is the value associated with outcome "j", • then: • Expected value of action "i"  =∑pij Vj • Expected value of consultation =  0.05 * 100+ 0.60*25 + 0.35*0 = 20 • Expected value for stopping admission = 0.40 *100 + 0.20 *25 + 0.40 * 0 = 45 • Most desirable action would be to stop admissions

24. Sensitivity Analysis • Identify how various assumptions in the analysis affect the conclusion.  • How much an estimate would have to change to alter the choice of "preferred" action. • Several estimates can also be modified at once, especially using computers. • Return to an earlier stage: • Add a new action or outcome • Add new uncertainties • Refine probability estimates • Refine utility estimates

25. Take Home Lesson Decision Analysis reconstitutes the whole from its parts. The process of analysis matters as much as the end result.