===== Sensitivity to Change ===== One of the key strengths of CUSUM analysis is its high **sensitivity to change**—the ability to detect small, progressive shifts in performance that may not be obvious in traditional audits or aggregate statistics. ==== What It Means ==== **Sensitivity to change** refers to how quickly and accurately a monitoring tool can: * Detect emerging trends (positive or negative) * Reflect real-time variations in performance * Alert clinicians to subtle but meaningful deviations from expected outcomes ==== CUSUM vs. Traditional Monitoring ==== | Feature | CUSUM | Traditional Audit | |----------------------------|--------------------------------|-----------------------------| | Tracks performance case-by-case | ✅ Yes | ❌ No (often monthly or quarterly) | | Detects early drift | ✅ High sensitivity | ❌ Low sensitivity | | Suitable for small sample sizes | ✅ Yes | ❌ Needs large numbers | | Graphical representation | ✅ Intuitive curve | ❌ Summary statistics only | ==== Why It Matters in Neurosurgery ==== In procedures like **ICP monitor placement**, even small changes in complication rate can have serious consequences. CUSUM allows for: * Rapid feedback during early learning phases * Early warnings before a statistically significant problem arises * Detection of **both improvements** (learning curve) and **declines** (fatigue, system failure) ==== Clinical Application Example ==== * A shift from 10% to 15% complication rate over 10 cases may not be statistically significant. * However, CUSUM would detect the **trend immediately**, showing an upward curve and potentially triggering a visual alert level. ==== Summary ==== High sensitivity to change makes CUSUM ideal for: * **Trainee monitoring** * **Procedure standardization** * **Rapid quality assurance cycles** This feature enables timely interventions, supports continuous improvement, and ultimately enhances patient safety.