Using the American College of Surgeons’ National Surgical Quality Improvement Program (ACS-NSQIP) Database to Teach Data Exploration, Statistical Analysis, and Clinical Inference to Residents and Medical Students

Background Large, rigorously collected clinical registries can ground the teaching of data‐driven decision making to trainees. The American College of Surgeons’ National Surgical Quality Improvement Program (ACS-NSQIP) is one of the world’s most granular surgical datasets. Objective To provide educators with a step by step framework for using ACS-NSQIP as an educational tool for data exploration, statistical analysis, and clinical inference. Methods We synthesized published experience with NSQIP based curricula, user guides, and quality improvement (QI) initiatives, and distilled best practices into a modular curriculum mapped to core competencies. Results We outline eight sequential teaching modules—from dataset acquisition to QI implementation—supported by example exercises, assessment strategies, and guidance on governance, software, and common pitfalls. Conclusions ACS-NSQIP affords an authentic, scalable platform to teach modern quantitative skills in a clinically meaningful context, fostering both statistical literacy and a platform to expand both the data analysis skills and publishing acumen of medical trainees.