The Use and Cost-Effectiveness of Routine Preoperative Blood Typing and Antibody Screening in Hysterectomy for Benign Indications

Study Objective The purpose of this study is to quantify preoperative blood typing and antibody screening (T&S), as well as blood transfusion rates for benign hysterectomies. We also aim to validate and adopt a model by Stanhiser et al. (2017) that predicts transfusion risk in gynecologic surgery. Lastly, we aim to assess the potential cost savings by decreasing T&S testing through application of this model. Design A retrospective cohort study utilizing the de-identified electronic medical record available at Vanderbilt University Medical Center's Synthetic Derivative Database. Setting Risk of transfusion in hysterectomy patients is low (0.3-11%), however T&S is often ordered routinely preoperatively. Identification of patient characteristics associated with risk of transfusion in gynecologic surgery enabled the development of transfusion risk prediction models. These models may help inform value-driven preoperative laboratory testing. Patients or Participants 5617 patients undergoing hysterectomies (vaginal, laparoscopic, robotic-assisted, or by laparotomy) for benign indications from 2000-2016 at a large academic, tertiary care medical center. Interventions N/A Measurements and Main Results A total of 5617 hysterectomies were identified, of which 1478 were performed by laparotomy. The blood transfusion rate was 4.7% (95% confidence interval [CI], 4.2-5.3%). Preoperative T&S was obtained for 53.4% (95% CI, 52.1-54.7%) of patients. Preliminary univariate validation confirmed that transfusion was positively associated with planned laparotomy, history of hypertension, and low hemoglobin (all P Conclusion Preoperative T&S testing occurred in more than half of benign hysterectomy patients, while the blood transfusion rate was 4.7%. There is potential for cost savings by decreasing the use of routine testing by adopting a validated transfusion risk prediction model. Future directions include continued model validation and cost calculations.