Evidence-Based Practice, Quality Improvement, and Care Coordination
This domain tests whether you can appraise evidence, interpret diagnostic statistics, and improve care systematically.
Core rules
- Frame questions with PICO: population, intervention, comparison, outcome.
- Evidence hierarchy: systematic reviews and randomized controlled trials rank above cohort, case-control, and expert opinion; guideline recommendations include strength and certainty.
- Sensitivity = true positives ÷ all with disease; specificity = true negatives ÷ all without disease. Positive predictive value depends on prevalence and answers "if the test is positive, how likely is disease?"
- Number needed to treat = 1 ÷ absolute risk reduction.
- Quality improvement uses the Model for Improvement: aim, measures, and Plan-Do-Study-Act cycles. QI is local improvement; research is generalizable and needs institutional review board approval.
- Care coordination: closed-loop referrals, warm handoffs, shared plans, and follow-up confirmation reduce gaps.
Worked example
A rapid strep test has 85% sensitivity and 95% specificity; clinic prevalence is 30%. PPV = (0.85 × 0.30) ÷ [(0.85 × 0.30) + (0.05 × 0.70)] = 0.255 ÷ 0.290 ≈ 0.88. Reasoning: at higher prevalence, a positive result is more likely true; at very low prevalence, even a specific test yields more false positives.
Traps
Confusing sensitivity with PPV; ignoring prevalence; calling a QI project research; using a single study to change practice; referring without confirming the appointment occurred.