Surgical Risk Prediction Suite (SRPS)

SRPS consists of a set of risk prediction tools that use data from a patient’s electronic health record (EHR) and customizable risk thresholds to identify healthy and at-risk surgery candidates and surfaces the data into existing workflows. The resulting patient stratification information enables providers to proactively modulate the appropriate levels of care to each patient in an individualized and personalized manner. SRPS is currently available for three high-volume orthopaedic surgery use cases: total hip, knee, and shoulder arthroplasty.

The SRPS algorithm was developed by the Duke Predictive Modeling Team within Duke Orthopaedic Surgery and operationalized by the digital health specialists at Pattern Health. Validation partners at Rush/Midwest Orthopaedics and New York University Orthopaedic Surgery have additionally conducted, or are in the process of completing, independent validations of SRPS.

SRPS provides value to systems operating on value-based or fee-for-service reimbursement models.