Big data modeling to predict platelet usage and minimize wastage in a tertiary care system

Source abstract

Significance In modern hospital systems where complicated, severely ill patient populations are the norm, there is currently no reliable way to forecast the use of perishable medical resources to enable a smart and economic way to deliver optimal patient care. We here demonstrate a statistical model using hospital patient data to quantitatively forecast, days in advance, the need for platelet transfusions. This approach can be leveraged to significantly decrease platelet wastage, and, if adopted nationwide, would save approximately 80 million dollars per year. We believe our approach can be generalized to all other aspects of patient care involving timely delivery of perishable medical resources.