Medical Decision Making

ISBN-13: 9781119627807 / Angielski / Miękka / 2024 / 368 str.

Durham Gillian (Duke-Margolis Institute for Health Policy

Spis treści

CHAPTER 1. INTRODUCTION1.1 How may I be thorough yet efficient when considering the possible causes of my patient's problems?1.2 How may I be thorough yet efficient when considering the possible causes of my patient's problems?1.3 How do I select the appropriate diagnostic test?1.4 How do I choose among several risky treatment alternatives?CHAPTER 2. DIFFERENTIAL DIAGNOSIS2.1 An introduction2.2 How clinicians make a diagnosis2.3 The principles of hypothesis-driven differential diagnosis2.4 An illustrative exampleBibliographyCHAPTER 3. PROBABILITY: QUANTIFYING UNCERTAINTY3.1 Uncertainty and probability in medicine3.2 How to determine a probability3.3 Sources of error in using personal experience to estimate probability3.4 The role for empirical evidence in understanding uncertaintyBibliographyCHAPTER 4. INTERPRETING NEW INFORMATION: BAYES' THEOREM4.1 Conditional probability defined4.2 Bayes' theorem4.3 Odds ratio form of Bayes' theorem4.4 Lessons to be learned from Bayes' theorem4.5 The assumptions of Bayes' theorem4.6 Using Bayes' theorem to interpret a sequence of tests4.7 Using Bayes' theorem when many diseases are under considerationBibliographyCHAPTER 5. MEASURING THE ACCURACY OF CLINICAL FINDINGS5.1 A language to describe test results5.2 Measuring a test's capability to reveal the patient's true state5.3 How to measure test performance: a hypothetical case5.4 Pitfalls of predictive value5.5 Sources of bias in estimates of test performance and how to avoid them5.6 How to adjust for bias in measuring sensitivity and specificity5.7 When to be concerned about inaccurate measures of test performance5.8 Expressing test results as continuous variables: the ROC curve5.9 Combining data from several studies of test performanceBibliographyCHAPTER 6. DECISION TREES - REPRESENTING THE STRUCTURE OF A DECISION PROBLEM.6.1 Key concepts and terminology6.2 Measuring a test's capability to reveal the patient's true state6.3 Constructing the decision tree for a medical decision problemEpilogueBibliographyCHAPTER 7 DECISION TREE ANALYSIS7.1 Folding-back operation7.2 Sensitivity analysisEpilogueBibliographyCHAPTER 8 OUTCOME UTILITY - REPRESENTING RISK ATTITUDES8.1 What are risk attitudes?8.2 Demonstration of risk attitudes in a medical context8.3 General observations about outcome utilities8.4 Determining outcome utilities - Underlying conceptsEpilogueBibliographyCHAPTER 9 OUTCOME UTILITIES - CLINICAL APPLICATIONS9.1 A parametric model for outcome utilities9.2 Incorporating risk attitudes into clinical policies9.3 Helping patients communicate their preferencesCHAPTER 10 OUTCOME UTILITIES - ADJUSTING FOR THE QUALITY OF LIFE10.1 Example - Why the quality of life matters.10.2 Quality-lifetime tradeoff models10.3 Quality-survival tradeoff models10.4 What does it all mean? - An extended exampleEpilogueBibliographyCHAPTER 11 SURVIVAL MODELS - REPRESENTING UNCERTAINTY ABOUT THE LENGTH OF LIFE11.1 Survival model basics11.2 Medical example - Survival after breast cancer recurrence11.3 Exponential Survival Model11.4 Actuarial survival modelsEpilogueBibliographyCHAPTER 12 Markov Models -Structure12.1 Markov model basics12.2 Determining transition probabilities12.3 Markov model analysis - An overviewEpilogueBibliographyCHAPTER 13 SELECTION AND INTERPRETATION OF DIAGNOSTIC TESTS13.1 Four principles of decision making13.2 The threshold probability for treatment13.3 Threshold probabilities for testing13.4 Clinical application of the threshold model of decision making13.5 Accounting for the disutility of undergoing a test13.6 Sensitivity analysis13.7 Decision curves analysisCHAPTER 14 MEDICAL DECISION ANALYSIS IN PRACTICE: ADVANCED METHODS11.1 An overview of advanced modeling techniques11.2 Use of medical decision-making concepts to analyze a policy problem:the cost-effectiveness of screening for HIV11.3 Use of medical decision-making concepts to analyze a clinical diagnosticproblem: strategies to diagnose tumors in the lung11.4 Calibration and validation of decision models11.5 Use of complex models for individual-patient decision makingCHAPTER 15 COST-EFFECTIVENESS ANALYSIS15.1 The clinician's conflicting roles: patient advocate, member of society, and entrepreneur15.2 Cost-effectiveness analysis: a method for comparing management strategies15.3 Cost-benefit analysis: a method for measuring the net benefit of medical services15.4 Methodological best practices for cost-effectiveness analysis15.5 Reference case for cost-effectiveness analysis15.6 Impact inventory for cataloguing consequences15.7 Measuring the health effects of medical care15.8 Measuring the costs of medical care15.9 Interpretation of cost-effectiveness analysis and use in decision making15.10 Limitations of cost-effectiveness analysis

O autorze

Harold C. Sox is Emeritus Professor of Medicine and of The Dartmouth Institute at Dartmouth Medical School, USA. Douglas K. Owens is general internist and a Senior Investigator at the Center for Health Care Evaluation at the VA Health Care System, Palo Alto, USA and a Professor of Medicine and of Health Research and Policy at Stanford University, USA. Michael Higgins is Consulting Associate Professor at the Stanford Center for Biomedical Informatics Research, Palo Alto, USA.