Tailor-made proficiency curves in laparoscopic hysterectomy: enhancing patient safety using CUSUM analysis

Abstract

The objective of this study is to develop a risk-adjusted real-time quality control system in laparoscopic hysterectomy with respect to blood loss, operative time and adverse events in order to signal derailing surgical performance in a timely fashion. Based on prior research, uterus weight, body mass index, number of surgeons, prior abdominal surgery, and type of laparoscopic hysterectomy were identified as significant covariates predicting successful surgical outcome. Cumulative sum (CUSUM) analysis, a model based on dichotomous input (success or “failure”), was selected as a predictive tool for performance analysis. Cutoff values were set at blood loss <200 mL and operative time <120 min and no adverse event. Risk-adjusted CUSUM graphs were constructed. In order to detect progressive failure rates (odds ratio 2.0 compared to average) in surgical performance (for blood loss, operative time, and adverse events) within 20 procedures, as a result, surgeons with average clinical outcomes will be flagged once in every 70–75 procedures (median) without justified derailing performance. With proposed validated and risk-adjusted CUSUM graphs, gynecologists are able to continuously monitor their surgical performance in laparoscopic hysterectomy. Consequently, this identifies suboptimal factors, which allow improvement of their surgical outcomes (by means of adjustment) and further enhancement of patient safety.