Evidence-Based Practice and Information Mastery: Critical Appraisal

A guide on the method of applying evidence-based practice to combat information overload and help the practitioner locate, evaluate and integrate the best information to improve the quality of care for the patient.

Appraising the Evidence

Critical appraisal is the process of carefully and systematically examining research to judge its trustworthiness, value, and relevance in a particular context. 

When appraising an article, it is necessary to address the following:
  • Quality the methodology should include trials that are randomised and double blind to avoid selection and observer bias)
  •  Validity (trials need to mimic clinical practice, or used in clinical practice, with outcomes that make sense)
  •  Reliability (trials are credible and repeatable)

 There are many checklists and tools to help you in carrying out a critical appraisal of evidence:

These tools were developed by the British NHS Critical Appraisal Skills Programme (CASP) to help with the process of critically appraising specific types of articles.
 A practice guideline is a systematically developed statement designed to assist practitioner and patient decisions about appropriate health care for specific clinical circumstances.
This site provides access to a number of critical appraisal sheets, CATmaker (a computer-assisted critical appraisal tool) as well as other tools.
This site offers links to many resources, broken down by skill level, for clinicians who want to advance their knowledge and abilities related to evidence-based pharmacotherapeutic decision-making.
This site  includes worksheets for appraising different kinds of clinical questions and papers:  diagnosis, economic evaluation, harm, practice guidelines, prognosis, qualitative research, systematic reviews, therapy.

Statistical Reasoning

While this course from Johns Hopkins is aimed at public health, it provides a broad overview of biostatistial methods and concepts, emphasizing interpretation and concepts rather than calculations or mathematical details.  It develops the ability to read the scientific literature to critically evaluate study designs and methods of data analysis, and it introduces basic concepts of statistical inference, including hypothesis testing, p-values, and confidence intervals. Topics include comparisons of means and proportions; the normal distribution; regression and correlation; confounding; concepts of study design, including randomization, sample size, and power considerations; logistic regression, and an overview of some methods in survival analysis.