Show pageBacklinksCite current pageExport to PDFBack to top This page is read only. You can view the source, but not change it. Ask your administrator if you think this is wrong. ===== Cumulative Sum at Case ===== The **cumulative sum at case** (CUSUM value) represents the running total of deviations from the expected performance level up to a specific case number. In a binary outcome model (e.g., success = 0, complication = 1), the CUSUM at each case is calculated using the formula: ''Cₙ = max(0, Cₙ₋₁ + (Xₙ - k))'' Where: * ''Cₙ'' = cumulative sum at case ''n'' * ''Cₙ₋₁'' = cumulative sum at the previous case * ''Xₙ'' = actual outcome of the current case (0 or 1) * ''k'' = target complication rate (e.g., 0.1 for 10%) ==== Interpretation of the CUSUM Value ==== * A **CUSUM of 0** means performance is matching or better than expected. * A **rising CUSUM** indicates more complications than expected. * A **declining or flat CUSUM** suggests improving or consistent performance. ==== Case-by-Case Example ==== If the target complication rate ''k'' is 0.1 and the outcome sequence is: * Case 1: success → ''C₁ = max(0, 0 + (0 - 0.1)) = 0'' * Case 2: complication → ''C₂ = max(0, 0 + (1 - 0.1)) = 0.9'' * Case 3: success → ''C₃ = max(0, 0.9 + (0 - 0.1)) = 0.8'' The curve visually builds a story of performance across cases, and the **CUSUM value at each case becomes a snapshot of deviation** from target performance. ==== Why It Matters ==== Tracking the cumulative sum at each case: * Enables real-time feedback * Helps detect early deviations from the expected outcome rate * Facilitates monitoring during training and protocol changes * Supports objective decision-making in quality assurance cumulative_sum_at_case.txt Last modified: 2025/04/08 18:07by 127.0.0.1