===== Traditional Audit ===== A **traditional audit** in surgical practice typically involves the periodic review of outcomes (e.g., monthly, quarterly, or annually) to assess complication rates, adherence to protocols, and performance metrics. While valuable for long-term trend analysis, traditional audits have important limitations when it comes to detecting subtle or early changes in surgical performance. ==== Key Characteristics ==== * **Aggregated data** over time (e.g., number of complications per month) * **Delayed feedback**—results are often available only after the audit cycle ends * **Less responsive** to short-term variability * Often focuses on **statistical significance** rather than **clinical relevance** * Usually conducted by quality assurance or governance teams ==== Common Uses ==== * Institutional benchmarking * Departmental morbidity and mortality (M&M) reports * Accreditation and certification * Guideline compliance review ==== Limitations ==== | Limitation | Impact | |------------------------------------|-------------------------------------------------| | Delayed detection | Complications may accumulate unnoticed | | Insensitivity to small changes | Subtle learning curves or decline go undetected | | No real-time correction | No immediate feedback for the operator | | Aggregated averages mask outliers | Individual trends may be hidden | ==== Why CUSUM Offers an Advantage ==== CUSUM provides a **case-by-case dynamic view**, making it far more sensitive and actionable in scenarios where **early detection** and **individualized monitoring** are essential—such as surgical training, new procedures, or patient safety monitoring. While traditional audits remain useful for **macro-level assessments**, CUSUM fills the gap at the **micro-level**, offering real-time insights and the ability to intervene before trends become problems. ==== Best Practice ==== A robust surgical quality system should combine: * **Traditional audits** for global, institutional performance * **CUSUM analysis** for real-time, individual-level monitoring and early warning