An unsupervised learning approach to identify immunoglobulin utilization patterns using electronic health records.

The results identified data-driven segmentations of patients with high Ig utilization rates and patients with high risk for short-term inpatient use. Our report is the first on EHR data-driven clustering of Ig utilization patterns. The findings hold the potential to inform demand forecasting and resource allocation decisions during shortages of Ig products.