Case complexity refers to the degree of clinical, anatomical, or logistical difficulty associated with a surgical procedure. In CUSUM analysis, accounting for case complexity is essential to avoid misinterpreting outcomes as poor performance when they are, in fact, related to inherent risk.

• Patient condition (e.g., coagulopathy, unstable ICP, GCS < 6)
• Anatomical variations or prior surgeries
• Emergency vs. elective setting
• Availability of imaging or neuronavigation
• Need for simultaneous procedures

• High-complexity cases carry higher expected complication rates, which may justify a higher reference value (k).
• Standard CUSUM assumes all cases are equal—this may over-penalize surgeons who handle more complex cases.
• Risk-adjusted CUSUM models incorporate expected risk per case, offering a fairer analysis.

Example:

• Standard case: k = 0.10
• High-complexity case (e.g., coagulopathic trauma): k = 0.20

• Stratify CUSUM charts by case complexity to compare like with like.
• Use risk-adjusted CUSUM, incorporating clinical scores (e.g., ASA, APACHE, Rotterdam CT score).
• Record complexity level per case as a routine variable in your surgical registry or audit tool.

Understanding how complexity affects outcomes helps:

• Set realistic expectations for trainees
• Assign cases appropriately based on skill level
• Avoid unfair comparisons between operators

Adjusting CUSUM inputs to reflect case complexity ensures that the tool remains both accurate and equitable in measuring performance.