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Required reading in many medical and healthcare institutions, How to Read a Paper is a clear and wide-ranging introduction to evidence-based medicine and healthcare, helping readers to understand its central principles, critically evaluate published data, and implement the results in practical settings. Author Trisha Greenhalgh guides readers through each fundamental step of inquiry, from searching the literature to assessing methodological quality and appraising statistics.
How to Read a Paper addresses the common criticisms of evidence-based healthcare, dispelling many of its myths and misconceptions, while providing a pragmatic framework for testing the validity of healthcare literature. Now in its sixth edition, this informative text includes new and expanded discussions of study bias, political interference in published reports, medical statistics, big data and more.
Offers user-friendly guidance on evidence-based healthcare that is applicable to both experienced and novice readers
Authored by an internationally recognised practitioner and researcher in evidence-based healthcare and primary care
Includes updated references, additional figures, improved checklists and more
How to Read a Paper is an ideal resource for healthcare students, practitioners and anyone seeking an accessible introduction to evidence-based healthcare.
Autorentext
TRISHA GREENHALGH, OBE, FMedSci is Professor of Primary Care Health Sciences, Nuffield Department of Primary Care Health Sciences, Medical Sciences Division, University of Oxford, UK.
Klappentext
The bestselling guide to evidence-based medicine and healthcare
Required reading in many medical and healthcare institutions, How to Read a Paper is a clear and wide-ranging introduction to evidence-based medicine and healthcare, helping readers to understand its central principles, critically evaluate published data, and implement the results in practical settings. Author Trisha Greenhalgh guides readers through each fundamental step of inquiry, from searching the literature to assessing methodological quality and appraising statistics.
How to Read a Paper addresses the common criticisms of evidence-based healthcare, dispelling many of its myths and misconceptions, while providing a pragmatic framework for testing the validity of healthcare literature. Now in its sixth edition, this informative text includes new and expanded discussions of study bias, political interference in published reports, medical statistics, big data and more.
Zusammenfassung
Required reading in many medical and healthcare institutions, How to Read a Paper is a clear and wide-ranging introduction to evidence-based medicine and healthcare, helping readers to understand its central principles, critically evaluate published data, and implement the results in practical settings. Author Trisha Greenhalgh guides readers through each fundamental step of inquiry, from searching the literature to assessing methodological quality and appraising statistics.
How to Read a Paper addresses the common criticisms of evidence-based healthcare, dispelling many of its myths and misconceptions, while providing a pragmatic framework for testing the validity of healthcare literature. Now in its sixth edition, this informative text includes new and expanded discussions of study bias, political interference in published reports, medical statistics, big data and more.
Inhalt
Foreword to the first edition by Professor Sir David Weatherall xii
Preface to the sixth edition xiv
Preface to the first edition xvi
Acknowledgements xviii
Chapter 1 Why read papers at all? 1
Does 'evidencebased medicine' simply mean 'reading papers in medical journals'? 1
Why do people sometimes groan when you mention evidencebased healthcare? 4
Before you start: formulate the problem 11
Exercises based on this chapter 13
References 14
Chapter 2 Searching the literature 16
What are you looking for? 17
Levels upon levels of evidence 18
Synthesised sources: systems, summaries and syntheses 19
Preappraised sources: synopses of systematic reviews and primary studies 22
Specialised resources 23
Primary studies tackling the jungle 23
Onestop shopping: federated search engines 25
Asking for help and asking around 26
Online tutorials for effective searching 26
Exercises based on this chapter 27
References 27
Chapter 3 Getting your bearings: what is this paper about? 29
The science of 'trashing' papers 29
Three preliminary questions to get your bearings 31
Randomised controlled trials 35
Cohort studies 38
Casecontrol studies 40
Crosssectional surveys 41
Case reports 41
The traditional hierarchy of evidence 42
Exercises based on this chapter 43
References 43
Chapter 4 Assessing methodological quality 45
Was the study original? 45
Whom is the study about? 46
Was the design of the study sensible? 47
Was bias avoided or minimised? 49
Was assessment 'blind'? 53
Were preliminary statistical questions addressed? 54
A note on ethical considerations 57
Summing up 58
Exercises based on this chapter 59
References 60
Chapter 5 Statistics for the nonstatistician 62
How can nonstatisticians evaluate statistical tests? 62
Have the authors set the scene correctly? 64
Paired data, tails and outliers 69
Correlation, regression and causation 71
Probability and confidence 73
The bottom line 75
Summary 77
Exercises based on this chapter 77
References 78
Chapter 6 Papers that report trials of drug treatments and other simple interventions 79
'Evidence' and marketing 79
Making decisions about therapy 82
Surrogate endpoints 82
What information to expect in a paper describing a randomised controlled trial: the CONSORT statement 86
Getting worthwhile evidence from pharmaceutical representatives 86
Exercises based on this chapter 89
References 89
Chapter 7 Papers that report trials of complex interventions 92
Complex interventions 92
Ten questions to ask about a paper describing a complex intervention 94
Exercises based on this chapter 99
References 100
Chapter 8 Papers that report diagnostic or screening tests 101
Ten men in the dock 101
Validating diagnostic tests against a gold standard 102
Ten questions to ask about a paper that claims to validate a diagnostic or screening test 107
Likelihood ratios 111
Clinical prediction rules 113
Exercises based on this chapter 114
References 115
Chapter 9 Papers that summarise other papers (systematic reviews and metaanalyses) 117
When is a review systematic? 117
Evaluating systematic reviews 120
Metaanalysis for the nonstatistician 125
Explaining heterogeneity 130
New approaches to systematic review 132
Exercises based on this chapter 133 Referen…