BOOK
Crash Course Evidence-Based Medicine: Reading and Writing Medical Papers - E-Book
(2013)
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Book Details
Abstract
Crash Course – your effective everyday study companion PLUS the perfect antidote for exam stress! Save time and be assured you have all the information you need in one place to excel on your course and achieve exam success.
A winning formula now for over 15 years, each volume has been fine-tuned to make your life easier. Especially written by junior doctors – those who understand what is essential for exam success – with all information thoroughly checked and quality assured by expert Faculty Advisers, the result is a series of books which exactly meets your needs and you know you can trust.
This essential new addition to the series clearly brings together the related disciplines of evidence-based medicine, statistics, critical appraisal and clinical audit – all so central to current study and to modern clinical practice. It starts with the basics that every student needs to know and continues into sufficient detail to satisfy anyone contemplating their own research studies. Excel in Student Selected Component (SSC) assessments and that dreaded evidence-based medicine and statistics exam! Ensure you know how to prepare the highest quality reports and maximize your chances of getting published.
If you are not sure:
- why you need to know the standard deviation of a sample
- when to use a case-control study and when a cohort study
- what to say to your patient who asks about the benefits and harms of a drug
- how to argue the case for the inclusion of a drug on the hospital formulary
- how to make audit and quality improvement work for you,
…then this groundbreaking book is for you! Answer these and hundreds of other questions and lay a foundation for your clinical practice that will inform every consultation over a lifetime in medicine.
Table of Contents
| Section Title | Page | Action | Price |
|---|---|---|---|
| Front Cover | Cover | ||
| Crash Course: Evidence-Based Medicine: Reading and Writing Medical Papers | iii | ||
| Copyright | iv | ||
| Series editor foreword | v | ||
| Prefaces | vii | ||
| Acknowledgements | ix | ||
| Dedication | xi | ||
| Contents | xiii | ||
| Chapter 1: Evidence-based medicine | 1 | ||
| WHAT IS EVIDENCE-BASED MEDICINE? | 1 | ||
| FORMULATING CLINICAL QUESTIONS | 1 | ||
| IDENTIFYING RELEVANT EVIDENCE | 2 | ||
| Sources of information | 2 | ||
| The search strategy | 3 | ||
| Search terms | 3 | ||
| Reviewing the search strategy | 4 | ||
| Expanding your results | 4 | ||
| Limiting your results | 4 | ||
| Documentation of the search strategy | 4 | ||
| CRITICALLY APPRAISING THE EVIDENCE | 4 | ||
| Critical appraisal | 4 | ||
| Hierarchy of evidence | 6 | ||
| ASSESSING THE RESULTS | 6 | ||
| IMPLEMENTING THE RESULTS | 6 | ||
| EVALUATING PERFORMANCE | 6 | ||
| CREATING GUIDELINE RECOMMENDATIONS | 7 | ||
| Chapter 2: Handling data | 9 | ||
| TYPES OF VARIABLES | 9 | ||
| Nominal variable | 9 | ||
| Ordinal variable | 9 | ||
| Interval variable | 10 | ||
| Ratio variable | 10 | ||
| Quantitative (numerical) data | 10 | ||
| Discrete variable | 10 | ||
| Continuous variable | 10 | ||
| Qualitative (categorical) data | 10 | ||
| DISPLAYING THE DISTRIBUTION OF A SINGLE VARIABLE | 11 | ||
| Frequency distributions | 11 | ||
| Displaying frequency distributions | 11 | ||
| Bar chart | 11 | ||
| Pie chart | 12 | ||
| Histogram | 13 | ||
| DISPLAYING THE DISTRIBUTION OF TWO VARIABLES | 13 | ||
| Numerical versus numerical variables | 14 | ||
| Categorical versus categorical variables | 14 | ||
| Numerical versus categorical variables | 14 | ||
| Box and whisker plot | 14 | ||
| Bar chart | 15 | ||
| Dot plot | 15 | ||
| DESCRIBING THE FREQUENCY DISTRIBUTION: CENTRAL TENDENCY | 15 | ||
| The arithmetic mean | 15 | ||
| The mode | 16 | ||
| The median | 16 | ||
| DESCRIBING THE FREQUENCY DISTRIBUTION: VARIABILITY | 16 | ||
| The range | 17 | ||
| The inter-quartile range | 17 | ||
| Percentiles | 17 | ||
| The standard deviation | 17 | ||
| Population standard deviation | 17 | ||
| Sample standard deviation | 17 | ||
| THEORETICAL DISTRIBUTIONS | 18 | ||
| Probability distributions | 18 | ||
| The rules of probability | 18 | ||
| Mutually exclusive events | 18 | ||
| Independent events | 18 | ||
| Defining probability distributions | 18 | ||
| Continuous probability distributions | 18 | ||
| The normal (Gaussian) distribution | 19 | ||
| Reference range | 19 | ||
| `Standard´ normal distribution | 20 | ||
| Other continuous probability distributions | 20 | ||
| Discrete probability distributions | 20 | ||
| Skewed distributions | 20 | ||
| Positively skewed distributions | 20 | ||
| Negatively skewed distributions | 20 | ||
| TRANSFORMATIONS | 20 | ||
| The logarithmic transformation | 21 | ||
| The geometric mean | 21 | ||
| Calculating the anti-log | 22 | ||
| The square transformation | 22 | ||
| CHOOSING THE CORRECT SUMMARY MEASURE | 22 | ||
| Chapter 3: Investigating hypotheses | 23 | ||
| HYPOTHESIS TESTING | 23 | ||
| The null and alternative hypotheses | 23 | ||
| CHOOSING A SAMPLE | 23 | ||
| Accuracy versus precision | 24 | ||
| Accuracy | 24 | ||
| Precision | 24 | ||
| EXTRAPOLATING FROM ` SAMPLE´ TO `POPULATION´ | 24 | ||
| Standard error of the mean | 24 | ||
| Standard error versus standard deviation | 25 | ||
| Confidence interval for the mean | 25 | ||
| Confidence interval versus reference range | 26 | ||
| Confidence interval for a proportion | 26 | ||
| The effect of simvastatin on stroke risk | 27 | ||
| What is a large sample? | 28 | ||
| COMPARING MEANS AND PROPORTIONS: CONFIDENCE INTERVALS | 28 | ||
| Confidence interval for the difference between two independent means | 28 | ||
| Confidence interval for the difference between paired means | 29 | ||
| Confidence interval for the difference between two independent proportions | 30 | ||
| Plotting error bars | 30 | ||
| THE P-VALUE | 31 | ||
| Statistical hypothesis testing | 31 | ||
| Calculating the P-value | 31 | ||
| One-tail versus two-tail P-values | 32 | ||
| STATISTICAL SIGNIFICANCE AND CLINICAL SIGNIFICANCE | 32 | ||
| Interpreting small P-values (P<0.05) | 32 | ||
| Chapter 4: Systematic review and meta-analysis | 41 | ||
| WHY DO WE NEED SYSTEMATIC REVIEWS? | 41 | ||
| Rationale for systematic reviews | 41 | ||
| Traditional reviews | 41 | ||
| Principles and conduct of systematic reviews | 42 | ||
| Developing a systematic review: steps 1-3 | 42 | ||
| EVIDENCE SYNTHESIS | 42 | ||
| META-ANALYSIS | 42 | ||
| Why do a meta-analysis? | 42 | ||
| Combining estimates in a meta-analysis | 42 | ||
| Heterogeneity | 43 | ||
| Tests for evidence of heterogeneity | 43 | ||
| Estimating the degree of heterogeneity | 43 | ||
| Investigating sources of heterogeneity | 43 | ||
| Calculating the pooled estimate in the absence of heterogeneity | 43 | ||
| Fixed-effects meta-analysis | 43 | ||
| Dealing with heterogeneity | 44 | ||
| Not performing a meta-analysis | 44 | ||
| Random-effects meta-analysis | 44 | ||
| Subgroup analysis | 44 | ||
| Fixed-effects versus random-effects meta-analysis | 45 | ||
| Sensitivity analysis | 45 | ||
| PRESENTING META-ANALYSES | 45 | ||
| EVALUATING META-ANALYSES | 45 | ||
| Interpreting the results | 45 | ||
| Bias in meta-analyses | 46 | ||
| Production of evidence | 46 | ||
| Dissemination of evidence | 46 | ||
| Publication bias | 47 | ||
| Detecting publication bias | 47 | ||
| Other causes of funnel plot asymmetry | 47 | ||
| Preventing publication bias | 47 | ||
| ADVANTAGES AND DISADVANTAGES | 48 | ||
| KEY EXAMPLE OF A META-ANALYSIS | 48 | ||
| REPORTING A SYSTEMATIC REVIEW | 49 | ||
| Chapter 5: Research design | 53 | ||
| OBTAINING DATA | 53 | ||
| INTERVENTIONAL STUDIES | 53 | ||
| OBSERVATIONAL STUDIES | 54 | ||
| CLINICAL TRIALS | 55 | ||
| Types of clinical trials | 55 | ||
| Clinical trial phases | 56 | ||
| Pre-clinical trials | 56 | ||
| Phase I trials | 56 | ||
| Phase II trials | 56 | ||
| Phase III trials | 56 | ||
| Phase IV trials | 56 | ||
| BRADFORD-HILL CRITERIA FOR CAUSATION | 57 | ||
| Strength of association | 58 | ||
| Consistency | 58 | ||
| Specificity | 58 | ||
| Temporal sequence | 58 | ||
| Biological gradient (dose-response) | 58 | ||
| Biological plausibility | 58 | ||
| Coherence | 58 | ||
| Reversibility (experimental evidence) | 59 | ||
| Analogy | 59 | ||
| CHOOSING THE RIGHT STUDY DESIGN | 59 | ||
| Using the hierarchy of evidence | 59 | ||
| WRITING UP A RESEARCH STUDY | 59 | ||
| Title | 60 | ||
| Abstract | 60 | ||
| Introduction | 61 | ||
| Methods | 61 | ||
| Results | 62 | ||
| Discussion | 62 | ||
| References | 62 | ||
| Journal articles | 63 | ||
| Books | 63 | ||
| Chapters in books | 63 | ||
| Websites | 63 | ||
| Dissertations and theses | 63 | ||
| Verbal materials: interviews | 63 | ||
| Unpublished material: lecture notes | 63 | ||
| Chapter 6: Randomised controlled trials | 65 | ||
| WHY CHOOSE AN INTERVENTIONAL STUDY DESIGN? | 65 | ||
| PARALLEL RANDOMISED CONTROLLED TRIAL | 65 | ||
| Study design | 65 | ||
| Inclusion/exclusion criteria | 66 | ||
| Choice of comparator | 67 | ||
| Sample size | 67 | ||
| The outcome measure | 67 | ||
| Ethical issues | 68 | ||
| Clinical equipoise | 68 | ||
| Informed consent | 68 | ||
| Randomisation | 69 | ||
| Methods of randomisation | 69 | ||
| Simple randomisation | 69 | ||
| Block randomisation | 69 | ||
| Stratified randomisation | 69 | ||
| Minimisation | 69 | ||
| Allocation sequence concealment | 70 | ||
| Blinding | 70 | ||
| CONFOUNDING, CAUSALITY AND BIAS | 70 | ||
| Confounding | 70 | ||
| Causality | 71 | ||
| Bias | 71 | ||
| Selection bias | 71 | ||
| Bias associated with randomisation: random sequence generation bias and allocation of intervention bias | 71 | ||
| Bias during study implementation: contamination bias | 72 | ||
| Bias during study implementation: loss-to-follow-up bias | 72 | ||
| Measurement bias | 72 | ||
| Random misclassification bias | 72 | ||
| Non-random misclassification bias | 73 | ||
| Performance bias | 73 | ||
| Detection bias | 73 | ||
| Recall bias | 73 | ||
| Interviewer bias | 73 | ||
| INTERPRETING THE RESULTS | 73 | ||
| Interim analysis | 74 | ||
| Adjusting for confounders | 74 | ||
| Intention to treat analysis | 74 | ||
| Efficacy versus effectiveness | 75 | ||
| Sensitivity analysis | 75 | ||
| Subgroup analysis | 75 | ||
| Numbers needed to treat for benefit and harm | 75 | ||
| NNTB example | 75 | ||
| NNTH example | 76 | ||
| TYPES OF RANDOMISED CONTROLLED TRIALS | 76 | ||
| Two or more parallel groups | 76 | ||
| Cross-over trial | 76 | ||
| Factorial trial | 77 | ||
| Cluster trial | 77 | ||
| Superiority versus equivalence trials | 77 | ||
| Superiority trial | 77 | ||
| Equivalence trial | 77 | ||
| ADVANTAGES AND DISADVANTAGES | 78 | ||
| KEY EXAMPLE OF A RANDOMISED CONTROLLED TRIAL | 78 | ||
| REPORTING A RANDOMISED CONTROLLED TRIAL | 78 | ||
| Chapter 7: Cohort studies | 83 | ||
| STUDY DESIGN | 83 | ||
| INTERPRETING THE RESULTS | 84 | ||
| Risk | 84 | ||
| Risk ratios | 84 | ||
| Confidence interval for a risk ratio | 84 | ||
| Risk difference | 86 | ||
| Risk ratio versus risk difference | 86 | ||
| CONFOUNDING, CAUSALITY AND BIAS | 86 | ||
| Confounding | 86 | ||
| Causality | 87 | ||
| Bias | 87 | ||
| Selection bias | 88 | ||
| Bias during study implementation: loss-to-follow-up bias | 88 | ||
| Participation bias: non-response bias | 88 | ||
| Eligible population inappropriately defined: healthy worker effect bias | 88 | ||
| Ascertainment bias: healthcare access bias | 89 | ||
| Measurement bias | 89 | ||
| Random misclassification bias | 89 | ||
| Non-random misclassification bias | 89 | ||
| Performance bias: follow-up bias | 89 | ||
| Detection bias: diagnostic suspicion bias | 89 | ||
| Recall bias: rumination bias and exposure suspicion bias | 89 | ||
| Interviewer bias: observer expectation bias and apprehension bias | 90 | ||
| ADVANTAGES AND DISADVANTAGES | 90 | ||
| KEY EXAMPLE OF A COHORT STUDY | 90 | ||
| Chapter 8: Case-control studies | 93 | ||
| STUDY DESIGN | 93 | ||
| Case definition | 93 | ||
| Case selection | 94 | ||
| Control selection | 95 | ||
| Matching | 95 | ||
| Measuring exposure status | 95 | ||
| INTERPRETING THE RESULTS | 96 | ||
| Odds and odds ratio | 97 | ||
| Calculating the odds ratio | 97 | ||
| Interpreting the odds ratio | 97 | ||
| Confidence interval for an odds ratio | 97 | ||
| Odds ratio versus risk ratio | 97 | ||
| CONFOUNDING, CAUSALITY AND BIAS | 99 | ||
| Confounding | 99 | ||
| Causality | 99 | ||
| Bias | 99 | ||
| Selection bias | 99 | ||
| Eligible population inappropriately defined: hospital admission rate bias | 99 | ||
| Eligible population inappropriately defined: exclusion bias and inclusion bias | 100 | ||
| Eligible population inappropriately defined: overmatching bias | 100 | ||
| Participation bias: non-response bias | 101 | ||
| Detection bias | 101 | ||
| Ascertainment bias: incidence-prevalence bias | 101 | ||
| Ascertainment bias: healthcare access bias | 102 | ||
| Ascertainment bias: migration bias | 102 | ||
| Measurement bias | 102 | ||
| Random misclassification bias | 102 | ||
| Non-random misclassification bias | 102 | ||
| ADVANTAGES AND DISADVANTAGES | 102 | ||
| KEY EXAMPLE OF A CASE- CONTROL STUDY | 102 | ||
| Chapter 9: Measures of disease occurrence and cross-sectional studies | 105 | ||
| MEASURES OF DISEASE OCCURRENCE | 105 | ||
| Prevalence | 105 | ||
| Incidence risk | 105 | ||
| Incidence rate | 106 | ||
| Calculating person-time | 106 | ||
| When does a person become a case? | 107 | ||
| Prevalence versus incidence | 108 | ||
| STUDY DESIGN | 109 | ||
| Descriptive cross-sectional studies | 109 | ||
| Analytical cross-sectional studies | 109 | ||
| Selecting a representative sample | 110 | ||
| Repeated cross-sectional studies | 110 | ||
| INTERPRETING THE RESULTS | 110 | ||
| Prevalence | 110 | ||
| Prevalence odds ratio | 111 | ||
| Prevalence ratio | 111 | ||
| Prevalence odds ratio versus prevalence ratio | 111 | ||
| CONFOUNDING, CAUSALITY AND BIAS | 112 | ||
| Confounding | 112 | ||
| Causality | 112 | ||
| Bias | 112 | ||
| Selection bias | 112 | ||
| Participation bias: non-response bias | 113 | ||
| Ascertainment bias: incidence-prevalence bias | 113 | ||
| Ascertainment bias: healthcare access bias | 113 | ||
| Ascertainment bias: migration bias | 113 | ||
| Measurement bias | 113 | ||
| Random misclassification bias | 114 | ||
| Non-random misclassification bias | 114 | ||
| ADVANTAGES AND DISADVANTAGES | 114 | ||
| KEY EXAMPLE OF A CROSS-SECTIONAL STUDY | 114 | ||
| Chapter 10: Ecological studies | 117 | ||
| STUDY DESIGN | 117 | ||
| Levels of measurement | 117 | ||
| Levels of inferences | 117 | ||
| Types of ecological studies | 118 | ||
| Time trend studies | 118 | ||
| Geographical studies | 118 | ||
| Mixed design | 118 | ||
| Data collection | 118 | ||
| INTERPRETING THE RESULTS | 118 | ||
| Scatter plots and correlation coefficients | 119 | ||
| Regression analysis | 119 | ||
| Discussing the findings of a mixed design study | 119 | ||
| SOURCES OF ERROR IN ECOLOGICAL STUDIES | 119 | ||
| Ecological fallacy | 119 | ||
| Within-group bias | 121 | ||
| Confounding by group | 121 | ||
| Effect modification by group | 121 | ||
| Confounders and modifiers | 122 | ||
| Causality | 122 | ||
| ADVANTAGES AND DISADVANTAGES | 122 | ||
| Individual-level studies versus group-level studies | 122 | ||
| Design limitations of individual-level studies | 122 | ||
| Measurement limitations of individual-level studies | 123 | ||
| KEY EXAMPLE OF AN ECOLOGICAL STUDY | 123 | ||
| Relationship between socioeconomic status and mortality after an acute myocardial infarction | 123 | ||
| Chapter 11: Case report and case series | 125 | ||
| BACKGROUND | 125 | ||
| CONDUCTING A CASE REPORT | 125 | ||
| Preparation | 125 | ||
| Structuring a medical case report | 125 | ||
| Abstract | 126 | ||
| Introduction | 126 | ||
| Case presentation | 126 | ||
| Discussion | 126 | ||
| Conclusion | 126 | ||
| References | 126 | ||
| CONDUCTING A CASE SERIES | 127 | ||
| CRITICAL APPRAISAL OF A CASE SERIES | 127 | ||
| ADVANTAGES AND DISADVANTAGES | 127 | ||
| KEY EXAMPLES OF CASE REPORTS | 127 | ||
| The first cardiac transplantation | 127 | ||
| Multiple myeloma | 128 | ||
| KEY EXAMPLE OF A CASE SERIES | 128 | ||
| Thalidomide and congenital abnormalities | 128 | ||
| Chapter 12: Qualitative research | 129 | ||
| STUDY DESIGN | 129 | ||
| What is qualitative research? | 129 | ||
| Qualitative versus quantitative research methods | 129 | ||
| Methods of data collection | 130 | ||
| Participant observation | 130 | ||
| In-depth interviews | 130 | ||
| Focus groups | 131 | ||
| Sampling | 131 | ||
| Purposive sampling | 131 | ||
| Quota sampling | 131 | ||
| Snowball sampling | 131 | ||
| Maximum variation sampling | 132 | ||
| Negative sampling | 132 | ||
| ORGANISING AND ANALYSING THE DATA | 132 | ||
| Organising the data | 132 | ||
| Analysing the data | 132 | ||
| VALIDITY, RELIABILITY AND TRANSFERABILITY | 132 | ||
| Validity | 132 | ||
| Reliability | 133 | ||
| Transferability | 133 | ||
| ADVANTAGES AND DISADVANTAGES | 133 | ||
| KEY EXAMPLE OF QUALITATIVE RESEARCH | 133 | ||
| Chapter 13: Confounding | 135 | ||
| WHAT IS CONFOUNDING? | 135 | ||
| ASSESSING FOR POTENTIAL CONFOUNDING FACTORS | 135 | ||
| Association with exposure | 136 | ||
| The confounder causes the exposure | 136 | ||
| The confounder is a result from the exposure | 136 | ||
| The confounder is related to the exposure with a non-causal association | 136 | ||
| Association with disease | 137 | ||
| CONTROLLING FOR CONFOUNDING FACTORS | 137 | ||
| Design stage | 137 | ||
| Randomisation | 137 | ||
| Restriction | 137 | ||
| Matching | 137 | ||
| Analysis stage | 138 | ||
| Stratified analysis | 138 | ||
| Mathematical modelling | 138 | ||
| REPORTING AND INTERPRETING THE RESULTS | 138 | ||
| KEY EXAMPLE OF STUDY CONFOUNDING | 139 | ||
| Chapter 14: Screening, diagnosis and prognosis | 141 | ||
| SCREENING, DIAGNOSIS AND PROGNOSIS | 141 | ||
| DIAGNOSTIC TESTS | 141 | ||
| EVALUATING THE PERFORMANCE OF A DIAGNOSTIC TEST | 142 | ||
| Sensitivity and specificity | 142 | ||
| Using sensitivity and specificity to make clinical decisions | 144 | ||
| False positives and false negatives | 144 | ||
| Positive and negative predictive values | 144 | ||
| THE DIAGNOSTIC PROCESS | 145 | ||
| Pre-test probability | 145 | ||
| Post-test probability | 145 | ||
| Estimating the post-test probability using predictive values | 145 | ||
| Estimating the post-test probability using likelihood ratios | 147 | ||
| EXAMPLE OF A DIAGNOSTIC TEST USING PREDICTIVE VALUES | 148 | ||
| Case 1: Low pre-test probability/low prevalence | 149 | ||
| Case 2: Equivocal pre-test probability/high prevalence | 150 | ||
| Case 3: High pre-test probability/high prevalence | 150 | ||
| BIAS IN DIAGNOSTIC STUDIES | 150 | ||
| Spectrum bias | 150 | ||
| Verification bias | 150 | ||
| Partial verification bias | 151 | ||
| Differential verification bias | 151 | ||
| Loss-to-follow-up bias | 151 | ||
| Reporting bias | 152 | ||
| SCREENING TESTS | 152 | ||
| Diagnostic tests versus screening tests | 152 | ||
| Screening programmes | 152 | ||
| Screening programme evaluation | 153 | ||
| Selection bias | 153 | ||
| Length time bias | 153 | ||
| Lead-time bias | 154 | ||
| EXAMPLE OF A SCREENING TEST USING LIKELIHOOD RATIOS | 155 | ||
| PROGNOSTIC TESTS | 155 | ||
| Prognostic studies | 156 | ||
| Measuring prognosis | 157 | ||
| Morbidity | 157 | ||
| Mortality | 157 | ||
| Chapter 15: Statistical techniques | 159 | ||
| CHOOSING APPROPRIATE STATISTICAL TESTS | 159 | ||
| Data analysis goal | 159 | ||
| Type of variable | 159 | ||
| Data distribution | 160 | ||
| Gaussian versus non-Gaussian distributions | 160 | ||
| When to choose a non-parametric test | 160 | ||
| Sample size matters | 160 | ||
| COMPARISON OF ONE GROUP TO A HYPOTHETICAL VALUE | 161 | ||
| COMPARISON OF TWO GROUPS | 161 | ||
| Chi-squared test and Fisher's exact test | 163 | ||
| COMPARISON OF THREE OR MORE GROUPS | 163 | ||
| MEASURES OF ASSOCIATION | 163 | ||
| Chapter 16: Clinical audit | 167 | ||
| INTRODUCTION TO CLINICAL AUDIT | 167 | ||
| Clinical governance | 167 | ||
| What is clinical audit? | 167 | ||
| Clinical audit versus clinical research | 167 | ||
| Similarities between audit and research | 167 | ||
| Differences between audit and research | 168 | ||
| PLANNING THE AUDIT | 169 | ||
| Identifying a topic | 169 | ||
| Sources of inspiration | 169 | ||
| Formulating the audit question | 169 | ||
| CHOOSING THE STANDARDS | 169 | ||
| AUDIT PROTOCOL | 170 | ||
| DEFINING THE SAMPLE | 170 | ||
| DATA COLLECTION | 171 | ||
| ANALYSING THE DATA | 171 | ||
| EVALUATING THE FINDINGS | 171 | ||
| Standards achieved | 171 | ||
| Standards not achieved | 172 | ||
| IMPLEMENTING CHANGE | 172 | ||
| EXAMPLE OF A CLINICAL AUDIT | 172 | ||
| Audit question | 172 | ||
| The standards | 172 | ||
| The sample | 173 | ||
| Data collection | 173 | ||
| Analysing data | 173 | ||
| Evaluating performance | 173 | ||
| Implementing change | 174 | ||
| Chapter 17: Quality improvement | 175 | ||
| QUALITY IMPROVEMENT VERSUS AUDIT | 175 | ||
| THE MODEL FOR QUALITY IMPROVEMENT | 175 | ||
| THE AIM STATEMENT | 175 | ||
| Writing the statement | 175 | ||
| Example | 176 | ||
| Statement | 176 | ||
| Dimensions for improvement | 176 | ||
| MEASURES FOR IMPROVEMENT | 177 | ||
| Types of measures | 177 | ||
| Outcome measures | 177 | ||
| Process measures | 177 | ||
| Balancing measures | 177 | ||
| Chapter 18: Economic evaluation | 183 | ||
| WHAT IS HEALTH ECONOMICS? | 183 | ||
| Background | 183 | ||
| Efficiency | 183 | ||
| Technical efficiency | 183 | ||
| Productive efficiency | 183 | ||
| Allocative efficiency | 183 | ||
| Opportunity costs | 184 | ||
| Economic evaluation | 184 | ||
| ECONOMIC QUESTION AND STUDY DESIGN | 185 | ||
| Economic question | 185 | ||
| Costs | 185 | ||
| Study design | 185 | ||
| COST-MINIMISATION ANALYSIS | 185 | ||
| Clinical equivalence | 186 | ||
| What is clinical equivalence? | 186 | ||
| Demonstrating clinical equivalence | 186 | ||
| Superiority trials | 186 | ||
| Equivalence trials | 186 | ||
| Non-inferiority trials | 186 | ||
| COST-UTILITY ANALYSIS | 187 | ||
| Health utilities | 188 | ||
| Direct measurement of utilities | 188 | ||
| Visual analogue scale | 188 | ||
| Time trade-off | 188 | ||
| Standard gamble | 189 | ||
| Which valuation method is best? | 189 | ||
| Public versus patients | 189 | ||
| Indirect measurement of utilities | 190 | ||
| Quality-adjusted life years (QALYs) | 190 | ||
| Example 1: QALY - intervention A versus intervention B (Fig.18.8) | 190 | ||
| Example 2: QALY - intervention C versus intervention D (Fig.18.9) | 190 | ||
| Implementing QALYs | 190 | ||
| The net monetary benefit statistic | 192 | ||
| Advantages and disadvantages of a cost-utility analysis | 192 | ||
| COST-EFFECTIVENESS ANALYSIS | 193 | ||
| Independent interventions | 193 | ||
| Mutually exclusive interventions | 193 | ||
| The cost-effectiveness plane | 195 | ||
| Advantages and disadvantages of a cost-effectiveness analysis | 195 | ||
| COST-BENEFIT ANALYSIS | 195 | ||
| SENSITIVITY ANALYSIS | 196 | ||
| One-way sensitivity analysis | 196 | ||
| Multi-way sensitivity analysis | 196 | ||
| Probabilistic sensitivity analysis | 196 | ||
| Chapter 19: Critical appraisal checklists | 199 | ||
| CRITICAL APPRAISAL | 199 | ||
| Clinical question | 199 | ||
| Study design | 199 | ||
| Ethical issues | 199 | ||
| Study population | 199 | ||
| Study methods | 200 | ||
| Data analysis | 200 | ||
| Confounding and bias | 200 | ||
| Discussion | 200 | ||
| SYSTEMATIC REVIEWS AND META-ANALYSES | 202 | ||
| RANDOMISED CONTROLLED TRIALS | 202 | ||
| DIAGNOSTIC STUDIES | 203 | ||
| QUALITATIVE STUDIES | 204 | ||
| Chapter 20: Crash course in statistical formulae | 205 | ||
| DESCRIBING THE FREQUENCY DISTRIBUTION | 205 | ||
| EXTRAPOLATING FROM `SAMPLE´ TO `POPULATION´ | 205 | ||
| STUDY ANALYSIS | 205 | ||
| TEST PERFORMANCE | 205 | ||
| ECONOMIC EVALUATION | 205 | ||
| Chapter 21: Careers in academic medicine | 209 | ||
| CAREER PATHWAY | 209 | ||
| Academic Foundation Programme (AFP) | 209 | ||
| Academic clinical fellowship (ACF) | 209 | ||
| Academic clinical lectureship (ACL) | 209 | ||
| GETTING INVOLVED | 210 | ||
| What is my career path to date? | 210 | ||
| What inspired me to embark upon an academic career? | 210 | ||
| What do I like about being a clinical academic? | 211 | ||
| What challenges have I faced? | 211 | ||
| Advice for someone considering a career in academic medicine | 211 | ||
| PROS AND CONS | 211 | ||
| References | 213 | ||
| Chapter 3 | 213 | ||
| Chapter 4 | 213 | ||
| Chapter 6 | 213 | ||
| Chapter 7 | 213 | ||
| Chapter 8 | 213 | ||
| Chapter 9 | 213 | ||
| Chapter 10 | 213 | ||
| Chapter 11 | 213 | ||
| Chapter 12 | 213 | ||
| Chapter 13 | 214 | ||
| Chapter 14 | 214 | ||
| Self-assessment | 215 | ||
| Single best answer (SBA) questions | 217 | ||
| Extended matching questions (EMQs) | 225 | ||
| SBA answers | 233 | ||
| EMQ answers | 239 | ||
| Further reading | 245 | ||
| Chapter 1 | 245 | ||
| Chapter 2 | 245 | ||
| Chapter 3 | 245 | ||
| Chapter 4 | 245 | ||
| Chapter 5 | 245 | ||
| Chapter 6 | 245 | ||
| Chapter 7 | 245 | ||
| Chapter 8 | 246 | ||
| Chapter 9 | 246 | ||
| Chapter 10 | 246 | ||
| Chapter 11 | 246 | ||
| Chapter 12 | 246 | ||
| Chapter 13 | 246 | ||
| Chapter 14 | 246 | ||
| Chapter 15 | 246 | ||
| Chapter 16 | 246 | ||
| Chapter 17 | 246 | ||
| Chapter 18 | 246 | ||
| Chapter 19 | 247 | ||
| Chapter 21 | 247 | ||
| Glossary | 249 | ||
| Index | 253 |