Professionalism, Ethics, Patient Safety and Research Methods
Ethics and professionalism
The four principles are autonomy, beneficence, non-maleficence and justice. Valid consent requires capacity, adequate information and voluntariness; in a life-threatening emergency, treatment proceeds under necessity. Confidentiality yields only to public interest, notifiable disease reporting or a court order. Duty of candour requires prompt disclosure of harm, and honesty about error is both an ethical and a regulatory obligation.
Patient safety
Adverse events usually reflect systems failure rather than individual wickedness - the Swiss cheese model and human-factors analysis. Practical defences include the WHO surgical safety checklist, structured handover (SBAR), correct site marking, elimination of retained instruments, VTE prophylaxis and attention to fatigue and hierarchy.
Research methods and biostatistics
Know the hierarchy: systematic reviews and randomised trials above cohort, case-control and cross-sectional studies. Bias may be selection, information or confounding; randomisation and blinding address these, and analysis should be by intention to treat. A p value is the probability of the observed data (or more extreme) assuming the null hypothesis is true - not the probability that the null is true. Sensitivity detects disease; specificity excludes it; predictive values depend on prevalence. Number needed to treat is the reciprocal of absolute risk reduction.
Worked example: a test with 90% sensitivity and 95% specificity in a population with 10% prevalence. In 1000 people, 100 have disease: 90 true positives and 10 false negatives; of 900 healthy, 45 are false positives. Positive predictive value = 90/135 ≈ 67%, negative predictive value = 855/865 ≈ 99%. The same test in a 1% prevalence population would give a PPV near 15%.
Trap: relative risk reduction sounds impressive while absolute reduction and NNT determine real clinical value.