Crash Course Evidence-Based Medicine: Reading and Writing Medical Papers book cover

Crash Course Evidence-Based Medicine: Reading and Writing Medical Papers

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.

Paperback, 272 Pages

Published: August 2013

Imprint: Mosby

ISBN: 978-0-7234-3735-2

Contents

  • 1 Evidence-based medicine

    What is evidence-based medicine?

    Formulating clinical questions

    Identifying relevant evidence

    Critically appraising the evidence

    Assessing the results

    Implementing the results

    Evaluating performance

    Creating guideline recommendations

    2 Handling data

    Types of variables

    Displaying the distribution of a single variable

    Displaying the distribution of two variables

    Describing the frequency distribution: central tendency

    Describing the frequency distribution: variability

    Theoretical distributions

    Transformations

    Choosing the correct summary measure

    3 Investigating hypotheses

    Hypothesis testing

    Choosing a sample

    Extrapolating from ‘sample’ to ‘population’

    Comparing means and proportions: confidence intervals

    The P-value

    Statistical significance and clinical significance

    Statistical power

    4 Systematic review and meta-analysis

    Why do we need systematic reviews?

    Evidence synthesis

    Meta-analysis

    Presenting meta-analyses

    Evaluating meta-analyses

    Advantages and disadvantages

    Key example of a meta-analysis

    Reporting a systematic review

    5 Research design

    Obtaining data

    Interventional studies

    Observational studies

    Clinical trials

    Bradford-Hill criteria for causality

    Choosing the right study design

    Writing up a research study

    6 Randomised controlled trials

    Why choose an interventional study design?

    Parallel randomised controlled trials

    Confounding, causality and bias

    Interpreting the results

    Types of randomised controlled trials

    Advantages and disadvantages

    Key example of a randomised controlled trial

    Reporting a randomised controlled trial

    7 Cohort studies

    Study design

    Interpreting the results

    Confounding, causality and bias

    Advantages and disadvantages

    Key example of a cohort study

    8 Case-control studies

    Study design

    Interpreting the results

    Confounding, causality and bias

    Advantages and disadvantages

    Key example of a case-control study

    9 Measures of disease occurrence and cross-sectional studies

    Measures of disease occurrence

    Study design

    Interpreting the results

    Confounding, causality and bias

    Advantages and disadvantages

    Key example of a cross-sectional study

    10 Ecological studies

    Study design

    Interpreting the results

    Sources of error in ecological studies

    Advantages and disadvantages

    Key example of an ecological study

    11 Case report and case series

    Background

    Conducting a case report

    Conducting a case series

    Critical appraisal of a case series

    Advantages and disadvantages

    Key examples of case reports

    Key example of a case series

    12 Qualitative research

    Study design

    Organising and analysing the data

    Validity, reliability and transferability

    Advantages and disadvantages

    Key example of qualitative research

    13 Confounding

    What is confounding?

    Assessing for potential confounding factors

    Controlling for confounding factors

    Reporting and interpreting the results

    Key example of study confounding

    14 Screening, diagnosis and prognosis

    Screening, diagnosis and prognosis

    Diagnostic tests

    Evaluating the performance of a diagnostic test

    The diagnostic process

    Examples of diagnostic tests

    Bias in diagnostic studies

    Screening tests

    Prognostic tests

    15 Statistical techniques

    Choosing appropriate statistical tests

    Comparison of one group to a hypothetical value

    Comparison of two groups

    Comparison of three or more groups

    Measures of association

    Prediction

    16 Clinical audit

    Introduction to clinical audit

    Planning the audit

    Choosing the standards

    Audit protocol

    Define the sample

    Data collection

    Analysing the data

    Evaluating the findings

    Implementing change

    Example of a clinical audit

    17 Quality improvement

    Quality improvement vs audit

    The model for quality improvement

    The aim statement

    Measures for improvement

    Developing the changes

    The Plan-Do-Study-Act (PDSA) cycle

    Repeating the cycle

    Example of a quality improvement project

    18 Economic evaluation

    What is health economics?

    Economic question and study design

    Cost-minimisation analysis

    Cost-utility analysis

    Cost-effectiveness analysis

    Cost-benefit analysis

    Sensitivity analysis

    19 Critical appraisal checklists

    Critical appraisal

    Systematic reviews and meta-analyses

    Randomised controlled trials

    Diagnostic studies

    Qualitative studies

    20 Crash Course in statistical formulae

    Describing the frequency distribution

    Extrapolating from ‘sample’ to ‘population’

    Study analysis

    Test performance

    Economic evaluation

    21 Careers in academic medicine

    Career pathway

    Getting involved

    Pros and cons

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