Why Hysterectomy Algorithms Diverge from Clinical Practice: A Romanian Cohort Study

Background: Hysterectomy is a prevalent gynecological procedure and ensuring appropriate use of minimally invasive approaches is essential to enhance the value and quality of care. The aim of this study was to investigate the gap between algorithm-guided recommendations and routine surgical practice in a Romanian real-world cohort by identifying non-clinical factors associated with deviation from the algorithm, and assessing its impact on postoperative hospitalization. Methods: This is a retrospective analytical observational study conducted over a 4-year period (2021-2025). The database comprised 961 cases of hysterectomy performed for benign gynecological conditions using laparoscopic, abdominal and vaginal approaches in two tertiary centers. Results: The previously developed decision algorithm was implemented in a selected subgroup of approximately 332 (34.54%) patients, while the remaining 629 (65.45%) hysterectomies were performed according to surgeon preference or institutional resource availability. The mean duration of hospitalization of the entire lot was 6.88 days (SD = 2.70). In laparoscopic surgery, deviation was not associated with prolonged hospitalization, with results indicating a null effect, OR 1.08 (95% CI 0.72-1.62). In contrast, in the abdominal cohort, deviation was strongly associated with prolonged LOS, with OR 2.76 (95% CI 1.75-4.40). Conclusions: Patient-related factors shape the theoretical suitability of a surgical approach, but operator- and institution-related factors determine whether that option is realistically available. Strengthening training in minimally invasive surgery across all clinics could reduce selection bias.