I am a clinical researcher and orthopedic surgeon and one of my PhD student is starting on the last part of her thesis. Her work is centered around the potential benefits of interprofessional teaching at an orthopedic ward. The study is a retrospective cohort study on register data for hip fracture patients. Our hypothesis is that an interprofessional ward (with medical students and nurse students guided by real doctors and nurses) does not put patient at higher risk for adverse events than a control ward. As the primary outcome variable we have a proxy variable for adverse events; readmission rate at 3 months. The number of patients treated at the interprofessional ward is about 1:4 compared to the control ward.
My question: Assuming a 3-month readmission rate of about 20% (about normal for this patient group) in the control ward, how large a sample size do I need when I aim at detecting a 5% difference in readmission rates? This is for 80% power and $p \le 0.05$.
When performing this calculation as a superiority calculation for proportions in for instance SamplePower 3, I wind up at approximately 500 and 2000 in the interprofessional and control ward, respectively. Is this calculation correct, or should I do a non-inferiority analysis for proportions instead where the minimum clinical difference I am interested in is 5%? I cant find any such non-inferiority calculators where the number of subjects in the two groups are of different numbers, as in this study.