EBM --- Journal Reading Presenter ：葉麗雯 Date ： 2005/10/27

Users’ Guides to the Medical Literature Ⅶ. How to Use a Clinical Decision Analysis A. Are the Results of the study Valid ？ W. Scott Richardson, MD. Allan S. Detsky, MD, PhD, for the Evidence-Based Medicine Working Group JAMA; April 26, 1995; 273, 16

What is Clinical Decision Analysis? …..the application of explicit quantitative methods to analyze decisions made under conditions of uncertainty. In more simple term…..  It uses a mathematical formula to reconstitute the whole scenario, helping clinicians to visualize choices that are available and make appropriate decisions.

Decision analysis helps clinicians to compare the expected consequences of pursuing different strategies. A decision analysis model must compare at least two decision options. The process involves identifying all the available management options, and the potential outcomes of each, in a series of decisions that have to be made about patient care. Each decision option can be more clearly evaluated, and a strategy can be identified for maximizing clinical utility and minimizing related health care costs. The range of choices are plotted on a decision tree.

Analyzing the Analysis 1.Are The Results Valid? 2.What Are The Results? 3.Will The Results Help Me in Caring For My Patients?

Are the Results Valid? 1.Were all important strategies and outcome included? 2.Was an explicit and sensible process used to identify, select, and combine the evidence into probabilities? 3.Were utilities obtained in an explicit and sensible way from credible sources? 4.Was the potential impact of any uncertainty in the evidence determined?

1. Were all important strategies and outcome included? The issue here is….. how well the structure of the model fits the clinical decision analyses are built as decision trees Decision trees are displayed graphically, oriented from left-to-right.

Decision tree Illustrates all the potential choices and subsequent outcomes in diagrammatic form. The decisions and outcomes are presented in the order in which they are likely to occur, hence it is hierarchical in structure. Decision node A point in a decision tree where a decision has to be made. Generally illustrated by a square. The lines emanating from a decision node represent the clinical strategies being compared. Chance node Chance events that may occur following a decision. Generally illustrated by a circle. The probability of these events occurring are included in the decision tree Outcome node The final outcome of a decision path. Generally illustrated by a triangle or rectangle.

2. Were all of the realistic clinical strategies compared? Strategies  sequences of actions and decisions that are contingent on each other The authors of the analysis should specify which decision strategies are being compared Clinical strategies should be described in detail to recognize them as separate and realistic choices.

3. Were all clinically relevant outcomes considered? To be useful to clinicians and patients, the decision model should include the outcomes of the disease that matter to patients. These include not only the quantity of life, but also the quality, in measures of disease and disability.

The specific disorder in question determines which outcomes are clinically relevant. E.g.….  For an analysis of an acute, life-threatening condition, life expectancy might be appropriate as the main outcome measure  In an analysis of diagnostic strategies for a nonfatal disorder, more relevant outcomes would be discomfort from testing or days of disability avoided.

Clinical decision analyses should be built from the perspective of the patient, that is, should include all the clinical benefits and risks of importance to patients. By comparing the outcomes between strategies, you can discover the trade-offs (between competing benefits and competing risks) built into the model. The choice of strategies should be balanced on one or more of such trade-offs. The outcomes are measured as “ quality-adjusted life expectancy”, a scale that combines information about both the quantity and quality of life.

4. Was an explicit and sensible process used to identify, select, and combine the evidence into probabilities ? To assemble the large amount of information necessary for a decision analysis, the authors should search and select the literature in an explicit and unbiased way, and then appraise the validity, effect size, and homogeneity of the studies in a reproducible fashion. In other words, authors should perform as comprehensive a literature review as is required for a meta-analysis.

Once gathered, the information must be transformed into quantitative estimates of the likelihood of events, or probabilities. The scale of probability estimates ranges from 0 (impossible) to 1.0 (absolute certain). Probabilities must be assigned to each branch emanating from a chance node, and for each chance node, the sum of probabilities must add to 1.0.

5. Were the utilities obtained in an explicit and sensible way from credible sources? Utilities represent quantitative measurements of the value to the decision maker of the various outcomes of the decision. Utility : The preference or desirability of a particular outcome. A commonly used utility scale ranges from 0 (worst outcome, usually death) to 1.0 (excellent health) In a decision analysis built for an individual patient, the most credible ratings are those measured directly from that patient. For analysis built to inform clinical policy, credible ratings could come from three sources: (1) direct measurements from a large groups of patients with the disorder in question and to whom results of the decision analysis could be applied (2) from published studies of quality-of-life ratings by patients (3) from an equally large group of people representing the general public

6. Was the potential impact of any uncertainty in the evidence determined? Much of the uncertainty in clinical decision making arises from the lack of valid literature. Even when it is present, published evidence is often imprecise, with wide confidence intervals around estimates for important variables.

Decision analyst uses “sensitivity analysis” to see what effect varying estimates for risks, benefits, and values have on the expected clinical outcomes, and therefore on the choice of clinical strategies. Estimates can be varied one at a time  “one-way” sensitivity analyses two or three at a time  “multi-way” sensitivity analyses