EHR/EMR

Pattern Health Launches Innovative Orthopaedic Risk Assessment Tool

Pattern Health

Pattern Health today announced the latest addition to its digital health Exchange, Surgical Risk Prediction Suite (SRPS). SRPS is a clinical decision support tool authored by Duke Health that helps health systems anticipate and minimize complications and costs for common, high-volume orthopaedic surgery procedures. Now through the Pattern Exchange, SRPS is available for licensing and implementation at any health system or orthopaedic clinic in the United States or Canada.

The suite of risk prediction tools is used by orthopaedic surgeons to navigate medical risk assessment for hip, knee, and shoulder arthroplasty patients. SRPS accomplishes this through algorithms that reference an extensive set of pre- and intra-operative variables from a patient’s record and stratifies patients relative to their individualized risk of specific adverse outcomes. The stratification data allows providers to identify the most appropriate treatment pathway and allocate resources to optimize patients with a high risk of adverse events.

Now powered by Pattern Health’s digital health platform, SRPS can be deployed in a health system’s electronic health record (EHR) workflow. The integrated solution pulls data from a patient’s record and surfaces results conveniently in the EHR. Each provider has the flexibility to customize risk threshold cutoffs based on the particular priorities, resources, and timelines of their organization.

The SRPS algorithms were developed by the Duke Predictive Modeling Team within Duke Orthopaedic Surgery and led by Thorsten M Seyler, MD, PhD, Daniel E Goltz, MD, MBA, and Claire B Howell, MMCi. The suite of predictive tools boasts industry-leading area-under-the-curve (AUC) accuracy scores backed by peer-reviewed publications in leading orthopeadic journals. “Our models were developed and will continue to be improved upon, using over 50,000 historical cases from Duke and other leading academic medical centers. The result is a significantly higher accuracy rate than any other available set of similar clinical decision tools,” notes Dr. Goltz.

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