Research, Evidence, and Quality Improvement
What to master
Understand study designs, levels of evidence, and basic statistics: measures of central tendency and dispersion, confidence intervals, p-values, effect size, and number needed to treat. Know the difference between internal and external validity, and between statistical and clinical significance. Be familiar with quality improvement methods such as PDSA cycles and the role of audit and feedback.
Traps questions use
Questions often test whether a statistically significant result is clinically meaningful, or whether a study design supports a causal claim. Watch for confusion between reliability and validity, or between a systematic review and a single randomized trial when both are options. Another trap is assuming a large sample guarantees generalizability.
Worked rule of thumb
Ask three questions of any study: Was it designed to answer this question? Are the results precise and clinically meaningful? Do they apply to my patient? A p-value tells you about the probability of the data under the null, not the size or importance of the effect - always check the effect size and confidence interval.