Research, Evidence-Based Medicine, and Quality Improvement
Domain focus
This domain tests evidence appraisal, study design, test characteristics, and quality improvement. The exam expects you to apply evidence to emergency decisions and to improve systems rather than blame individuals.
Core rules
- Formulate a PICO question: population, intervention, comparison, outcome.
- Appraise design and bias: randomization, blinding, allocation concealment, follow-up, confounders, and confidence intervals.
- Sensitivity and specificity: high sensitivity makes a negative test useful to rule out disease (SnNout); high specificity makes a positive test useful to rule in disease (SpPin). Predictive values depend on pretest probability.
- Likelihood ratios summarize test performance and update pretest probability.
- QI: use PDSA cycles, audit measures, and root-cause analysis; focus on systems, not blame.
Worked example
A new troponin assay has sensitivity 98% and specificity 90%. In a low-pretest-probability patient, a negative result makes ACS unlikely because high sensitivity gives a useful negative test. In a high-pretest-probability patient, a positive result still needs clinical correlation because specificity is not perfect. Reasoning: test performance must be interpreted with pretest probability, not in isolation.
Traps
Confusing sensitivity with positive predictive value, ignoring pretest probability, and accepting surrogate outcomes as patient-important are common. In QI, changing multiple variables at once prevents attribution of effect.