Laboratory Management, Quality Assurance, and Biostatistics
Laboratory management
Quality has three phases: preanalytical, analytical, and postanalytical. Most errors are preanalytical - mislabeling, wrong tube, hemolysis, delayed transport. Internal quality control monitors daily performance with control materials; external quality assessment (proficiency testing) compares the laboratory with peers. Accreditation bodies (CAP, ISO 15189, JCI) require documented policies, validation, competency assessment, equipment maintenance, and incident reporting.
Management topics include turnaround time, workload, staffing, budgeting, inventory, and lean process improvement. Validation is required before introducing a new test, changing a method, or using a new reagent lot. Audits and root cause analysis close the loop after incidents.
Biostatistics
Sensitivity is the proportion of diseased people who test positive; specificity is the proportion of healthy people who test negative. Positive predictive value depends on prevalence: as prevalence falls, PPV falls and NPV rises. Accuracy is closeness to truth; precision is reproducibility. Random error affects precision; systematic error affects accuracy. Study designs include cross-sectional, case-control, cohort, and randomized trials. P-values indicate statistical significance, not clinical importance; confidence intervals show the range of uncertainty.
Traps
Questions reverse sensitivity and specificity, or assume PPV is fixed. They also confuse precision with accuracy and internal with external QC.
Rule of thumb: a highly sensitive test rules out disease when negative; a highly specific test rules in disease when positive.
Worked example: a test with 95% sensitivity and 90% specificity used in a low-prevalence population has a low PPV, so many positives are false positives.