Sox, Harold C., Jr. (USA Geisel School of Medicine at Dartmouth), Michael C. Higgins (Stanford Unive Biomedical Informatics Research, Douglas K. Owens (USA Stanford University)

Medical Decision Making

• Broschiertes Buch

Produktbeschreibung

MEDICAL DECISION MAKING

Detailed resource showing how to best make medical decisions while incorporating clinical practice guidelines and decision support systems

Sir William Osler, a legendary physician of an earlier era, once said, "Medicine is a science of uncertainty and an art of probability." In Osler's day, and now, decisions about treatment often cannot wait until the diagnosis is certain. Medical Decision Making is about how to make the best possible decision given that uncertainty. The book shows how to tailor decisions under uncertainty to achieve the best outcome based on published evidence, features of a patient's illness, and the patient's preferences.

Medical Decision Making describes a powerful framework for helping clinicians and their patients reach decisions that lead to outcomes that the patient prefers. That framework contains the key principles of patient-centered decision-making in clinical practice.

Since the first edition of Medical Decision Making in 1988, the authors have focused on explaining key concepts and illustrating them with clinical examples. For the Third Edition, every chapter has been revised and updated.

Written by four distinguished and highly qualified authors, Medical Decision Making includes information on:
_ How to consider the possible causes of a patient's illness and decide on the probability of the most important diagnoses.
_ How to measure the accuracy of a diagnostic test.
_ How to help patients express their concerns about the risks that they face and how an illness may affect their lives.
_ How to describe uncertainty about how an illness may change over time.
_ How to construct and analyze decision trees.
_ How to identify the threshold for doing a test or starting treatment
_ How to apply these concepts to the design of practice guidelines and medical policy making.

Medical Decision Making is a valuable resource for clinicians, medical trainees, and students of decision analysis who wish to fully understand and apply the principles of decision making to clinical practice.

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Produktdetails

• Verlag: Wiley & Sons / Wiley-Blackwell
• Artikelnr. des Verlages: 1W119627800
• 3. Aufl.
• Seitenzahl: 368
• Erscheinungstermin: 27. Februar 2024
• Englisch
• Abmessung: 272mm x 214mm x 17mm
• Gewicht: 998g
• ISBN-13: 9781119627807
• ISBN-10: 111962780X
• Artikelnr.: 67830256

Autorenporträt

Harold C. Sox is Emeritus Professor of Medicine and of the Dartmouth Institute at Geisel School of Medicine at Dartmouth, USA. Michael C. Higgins is Adjunct Professor at the Stanford Center for Biomedical Informatics Research, Stanford University, USA. Douglas K. Owens is a general internist and Professor and Chair of the Department of Health Policy, School of Medicine, and Director of Stanford Health Policy, Freeman-Spogli Institute for International Studies, Stanford University, USA. Gillian Sanders Schmidler is Professor of Population Health Sciences and Medicine at Duke University and Deputy Director of the Duke-Margolis Institute for Health Policy, Durham, USA.

Inhaltsangabe

Foreword xi

Preface xiii

1 Introduction 1

1.1 How may I be thorough yet efficient when considering the possible causes of my patient's problems? 1

1.2 How do I characterize the information I have gathered during the medical interview and physical examination? 1

1.3 How do I interpret new diagnostic information? 3

1.4 How do I select the appropriate diagnostic test? 4

1.5 How do I choose among several risky treatment alternatives? 4

2 Differential diagnosis 5

2.1 An introduction 5

2.2 How clinicians make a diagnosis 5

2.3 The principles of hypothesis- driven differential diagnosis 8

2.4 An extended example 14

Bibliography 16

3 Probability: quantifying uncertainty 18

3.1 Uncertainty and probability in medicine 18

3.2 How to determine a probability 21

3.3 Sources of error in using personal experience to estimate the probability 23

3.4 The role of empirical evidence in quantifying uncertainty 30

3.5 Limitations of published studies of disease prevalence 35

3.6 Taking the special characteristics of the patient into account when determining probabilities 36

Bibliography 37

4 Interpreting new information: Bayes' theorem 38

4.1 Introduction 38

4.2 Conditional probability defined 40

4.3 Bayes' theorem 41

4.4 The odds ratio form of Bayes' theorem 45

4.5 Lessons to be learned from using Bayes' theorem 50

4.6 The assumptions of Bayes' theorem 52

4.7 Using Bayes' theorem to interpret a sequence of tests 54

4.8 Using Bayes' theorem when many diseases are under consideration 55

Bibliography 57

5 Measuring the accuracy of clinical findings 58

5.1 A language for describing test results 58

5.2 The measurement of diagnostic test performance 62

5.3 How to measure diagnostic test performance: a hypothetical example 67

5.4 Pitfalls of predictive value 69

5.5 How to perform a high quality study of diagnostic test performance 70

5.6 Spectrum bias in the measurement of test performance 74

5.7 When to be concerned about inaccurate measures of test performance 79

5.8 Test results as a continuous variable: the ROC curve 81

5.9 Combining data from studies of test performance: the systematic review and meta- analysis 87

A.5.1 Appendix: derivation of the method for using an ROC curve to choose the definition of an abnormal test result 89

Bibliography 91

6 Decision trees - representing the structure of a decision problem 93

6.1 Introduction 93

6.2 Key concepts and terminology 93

6.3 Constructing the decision tree for a hypothetical decision problem 96

6.4 Constructing the decision tree for a medical decision problem 103

Epilogue 112

Bibliography 112

7 Decision tree analysis 113

7.1 Introduction 113

7.2 Folding- back operation 114

7.3 Sensitivity analysis 126

Epilogue 133

Bibliography 133

8 Outcome utility - representing risk attitudes 134

8.1 Introduction 134

8.2 What are risk attitudes? 135

8.3 Demonstration of risk attitudes in a medical context 136

8.4 General observations about outcome utilities 147

8.5 Determining outcome utilities - underlying concepts 151

Epilogue 157

Bibliography 158

9 Outcome utilities - clinical applications 159

9.1 Introduction 159

9.2 A parametric model for outcome utilities