Patient Blood Management

Reducing perioperative red blood cell unit issue orders, returns, and waste using failure modes and effects analysis

Surgical transfusion has an outsized impact on hospital-based transfusion services, leading to blood product waste and unnecessary costs. In this paper, we describe the design and implementation of a streamlined reliable process for perioperative blood ordering and delivery to reduce red cell waste.

Personalized Surgical Transfusion Risk Prediction Using Machine Learning to Guide Preoperative Type and Screen Orders

20 million patients have surgery in the US every year, and ~ 1 million of those patients require life-saving blood transfusion. Presurgical preparation for transfusion is important to allow for safe and timely transfusion during surgery, but excessive preparation is unfortunately common, costly, and contributes to blood waste. In this paper, we develop a personalized surgical transfusion risk prediction model using a database of 3 million surgical patients, and show that using such a model to guide presurgical type and screen orders can potentially improve patient safety while reducing the number of unnecessary orders. Reproducible code is provided to make predictions for new patients.