Biostatistics for the Clinician
Biostatistics for the Clinician
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University of Texas-Houston
Health Science CenterLesson 3.2
Decision Analysis
Lesson 3: Clinical Decision Making in a Multivariable Environment 3.2 - 1
Biostatistics for the Clinician
3.2 Decision Analysis
3.2.1 Decision Trees
Now for a brief look at decision analysis, an increasingly important part of medicine. In fact, a few years ago it spawned an entirely new journal that's good to be aware of called Medical Decision Making. You might wonder what kinds of articles are in this sort of journal. How about, "The Roles of Experience and Domain of Expertise in Using Numerical and Verbal Probability Terms in Medical Decisions". The journal features scientists that are looking at using artificial intelligence and other kinds of input about patient's decision making, patient's deciding upon what is a good outcome for them, what is a bad outcome, and how physicians make choices about whether or not to use a particular treatment. It has scientific analyses of decision making applied in the medical area. Decision analysis is a very important area, and is becoming increasingly important with the advent of managed care.In developing a decision analysis you break down the medical analysis into a series of events (see the Decision Analysis figure) below. Some of those events are chance events. That is, you perform a treatment and it may or may not work. Or, it works with some probability. That's a chance node. There are certain nodes for events where you make a decision. Those are choice or decision nodes and you still have the chance nodes. Particularly in areas of cancer treatment, where you might have a very complicated protocol where these decision trees can be very complex, there are many chance nodes, and there are many decision nodes. Decision nodes might involve questions like, "Shall I use this particular combination?", "Shall I use it 3 days?" "Shall I use it 5 days?" and so on?
Decision Analysis ![]()
The decision trees can be very complex. But, they illuminate and clarify the decision process that you as physicians and your colleagues go through. In other words, decision trees make very clear, the series of processes that you're going to need to go through to move a patient from diagnosis to cure.
Look at the Decision Analysis figure again now. You can see that decision trees have nodes and branches. First, on the left there's a choice node. So you choose to go with Strategy 1 or Strategy 2. If you choose Strategy 1 there are a couple of events (Event 1 and Event 2) that can happen with certain probabilities. These two different possible events define a probabilistic or "Chance Node". So Event 1 determines Outcome 1 with a certain probability. Likewise, Event 2 determines Outcome 2 with a certain probability. If you choose Stategy 1 you have a certain chance of Event 1 or Event 2 happening and each leads to a different outcome. So what you do, essentially, is to diagram the decisions that you're going to make, the Choice Nodes, the Chance Nodes, the events and their outcomes, as you see in the figure.
Lesson 1: Summary Measures of Data 3.2 - 5