You have a list of ten data quality issues reported from five clinical sites, each with different patient volumes, regulatory impact, and required effort. How would you prioritize which issue to address first to meet the upcoming regulatory submission deadline?

Apply the RICE framework: 1) Score each issue for Reach (patients affected), Impact (regulatory risk), Confidence (data certainty), Effort (time/resources). 2) Compute RICE = (Reach × Impact × Confidence) / Effort. 3) Rank issues by score, select the highest, and create a concise action plan with owners, timelines, and monitoring checkpoints. 4) Communicate the rationale to stakeholders and adjust if new high‑priority items emerge. 5) Document decisions for audit trails. (120‑150 words)

I would start by cataloguing each data quality issue and assigning quantitative scores using the RICE framework. Reach would be the number of patients or visits affected; Impact would reflect the regulatory risk or potential to delay the trial; Confidence would gauge the certainty of the issue’s existence; Effort would estimate the time and resources needed to resolve it. I would calculate a RICE score for each item, rank them, and select the highest‑scoring issue as the first priority. I would then draft a brief action plan, assign a site lead, set a realistic timeline, and establish a monitoring checkpoint. Throughout the process, I would communicate the prioritization rationale to stakeholders, ensuring transparency and alignment. If a new critical issue surfaces, I would re‑apply RICE to reassess priorities. This structured, data‑driven approach ensures that the most impactful problems are addressed first while keeping the project on schedule and compliant with regulatory requirements. (175‑200 words)