Foundations of Independent Practice (FIP)
What to master
FIP tests the physician as a systems thinker. Know study design and measures: incidence vs prevalence, relative risk vs odds ratio, attributable risk, number needed to treat/harm, sensitivity/specificity, predictive values, and how prevalence changes PPV/NPV. Review confidence intervals, p-values, type I/II error, power, intention-to-treat, randomization, blinding, and bias (selection, recall, lead-time, length, confounding). Understand screening principles and the difference between screening and diagnostic testing. Ethics and law are high yield: informed consent and decision-making capacity, assent, confidentiality and its exceptions, minor consent, surrogate decision-making, advance directives, research ethics, malpractice elements, error disclosure, and mandatory reporting. Patient safety and quality improvement include PDSA cycles, root-cause analysis, just culture, Swiss-cheese models, handoffs, and teach-back/shared decision-making. Health disparities and social determinants shape both risk and management.
Traps
Questions often ask for the "next best step" when the answer is a communication or systems action, not a laboratory test. Do not confuse sensitivity with positive predictive value. Capacity is decision-specific, not global. In quality improvement, avoid blaming an individual for a systems error. Know which conditions are reportable and when confidentiality must yield.
Worked rule
Sensitivity = TP/(TP+FN); specificity = TN/(TN+FP). A highly sensitive test is best for ruling out disease when negative (SnNOut); a highly specific test is best for ruling in disease when positive (SpPIn). Example: a 95%-sensitive test with a negative result in a low-prevalence setting makes disease unlikely but not impossible; estimate post-test probability rather than assuming zero risk.