Research, Evidence-Based Practice, and Quality Improvement
Core concepts
Understand evidence-based practice as the integration of best evidence, clinical expertise, and patient values. Know levels of evidence, study designs (RCT, cohort, case-control, cross-sectional, case series), and threats to validity (bias, confounding, blinding). Interpret statistics: sensitivity, specificity, likelihood ratios, positive and negative predictive values, effect size, confidence intervals, p-values, number needed to treat, and odds ratios. Understand quality improvement methods (PDSA, root cause analysis, outcome measurement) and how to apply evidence to practice.
Traps
Questions test whether you can distinguish statistical from clinical significance and interpret diagnostic test properties correctly. Watch for misuse of sensitivity versus specificity and confusion between likelihood ratios and predictive values. Do not equate a small p-value with a large effect.
Rule of thumb
Ask three questions of any study: is it valid, what are the results, and do they apply to my patient? Use likelihood ratios to update probability after a test.
Worked example
A screening test with high sensitivity and low specificity is best for ruling out disease when negative; a highly specific test is best for ruling in disease when positive. A positive result on a sensitive test still requires confirmation.