Population Health, Epidemiology and Evidence-Based Practice
Population health, epidemiology and evidence-based practice tests incidence and prevalence, diagnostic test properties, study design, bias, critical appraisal, outbreak investigation and social determinants. The exam expects numerical reasoning and a clear distinction between association and causation.
Core rules
- Incidence is new cases per population at risk per time; prevalence is existing cases at a point or period.
- Sensitivity is the proportion of diseased people who test positive; specificity is the proportion of non-diseased who test negative.
- Positive predictive value depends on prevalence; a highly specific test can still have a low PPV in a low-prevalence population.
- Randomised trials best assess interventions; cohort studies assess prognosis; case-control studies suit rare outcomes.
- Appraise bias, confounding, confidence intervals and whether outcomes are patient-important.
Worked example
A test has sensitivity 90% and specificity 95%; prevalence is 1%. In 10,000 people, 100 have disease, 90 test positive; 9,900 do not, and 495 falsely test positive. PPV is 90/585, about 15%. Reasoning: most positives are false positives when prevalence is low.
Traps
Confusing sensitivity with PPV; ignoring prevalence; treating surrogate outcomes as proof; and confusing statistical significance with clinical importance.