Power and sample size
SECONDARY
The overall effectiveness of the intervention will be evaluated based on the primary outcome measure, total MRP count. Based on our previous medication safety studies in SCC, we anticipate enrolling 80% of eligible participants and collecting data from ≥ 80% of enrolled participants at the 90-day follow up. We will approach 463 potential participants and enroll 371 to achieve a final analytic sample size of 296 children and their parents. This will provide > 90% power at the 2-sided 0.05 significance level to detect a 1.0 difference between study arms in MRP count, which is sufficient to detect clinically meaningful changes demonstrated by our pilot data. If there is some degree of contamination between the intervention arms due to clinicians seeing patients in both arms, the study will maintain 80% power to detect a significant mean difference in the primary outcome; this assumes a dilution of the treatment effect of 15% (i.e., that the difference in mean outcomes between treatment arms is attenuated to 0.85). These calculations assume a standard deviation in the MRP outcome of 2.6 as determined through prior work in this area. The proposed sample size will also provide adequate power to detect clinically important changes in quantitative secondary outcomes at the 2-sided 0.05 significance level. Assuming a correlation of 0.4 within patients, the study will have 80% power to detect a difference between study arms in mean change of a) PRO-Sx symptom scores by 3.1 points and b) counts of acute healthcare utilization by 0.8–1.1 visits. These calculations assume a correlation of each outcome within patients of 0.4.To achieve implementation fidelity aims using audiotaped visits, additional sample size and power calculations were performed. With a total of 50 audiotaped visits per study arm, the study will have 80% power to detect a 0.23 difference in proportions if fidelity in the pMTM group is 90%. The study will also have 80% power to detect a mean difference of 2.8 min if the standard deviation of the length of the conversation is 5 min. Correlation within providers will be accounted for by a mixed effects model’s random intercept.