Big Data Modeling to Predict Platelet Usage and Minimize Wastage in a Tertiary Care System
clinical
prediction
We develop a statistical model using hospital patient data to quantitatively forecast platelet transfusion needs days in advance. Analyzing 29 months of data from Stanford Hospital, the model reduces the platelet expiration rate from 10.5% to 3.2% while maintaining adequate inventory. Nationwide implementation could save approximately $80 million annually.