Predict+ is designed to inform surgeons about the possible patient outcomes after shoulder arthroplasty, based on clinical experience documented within a large database of single-shoulder prosthesis outcomes

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US Patent Issued for Exactech's Predict+. (Credit: Exactech, Inc.)

Exactech has secured the US patent for its machine learning-based software, Predict+, which predicts patient-specific outcomes after shoulder replacement surgery.

Predict+ is a data-driven, clinical decision support tool and the first software of its kind to use machine learning to predict individual patient outcomes after shoulder replacement surgery.

Launched in November 2020, the solution was designed to inform surgeons about the possible patient outcomes after shoulder arthroplasty.

Its insights are based on clinical experience documented within a large database of single-shoulder prosthesis outcomes from more than 15,000 patients.

Exactech extremities senior vice president Chris Roche said: “Predict+ is a novel application of orthopaedic clinical research and data science and represents a significant, value-creating advancement to the surgeon-patient preoperative consultation process related to shoulder arthroplasty.

“This granted patent strengthens Exactech’s leadership position in the orthopaedic applications of artificial intelligence and features several broad claims which cover future innovations and expands Exactech’s intellectual property portfolio.”

Exactech developed Predict+ in partnership with Advata, an analytics software company focused on patient outcomes and healthcare management.

With the solution, the surgeon inputs as few as 19 data points about a patient and within seconds, the software predicts the patient’s potential outcomes, including pain, function, and range of motion.

The software also compares predictive results for anatomic and reverse shoulder arthroplasty at multiple post-operative timepoints.

In addition, Predict+ is said to help surgeons to identify factors that impact the outcome predictions, such as the patient losing weight, quitting smoking, and completing pre-habilitation.

It aggregates the outcomes within the database, allowing surgeons and patients to compare their personalised predictions with the clinical experience, said the company.

Advata research and machine learning vice president Vikas Kumar said: “Predict+ delivers personalised, evidence-based predictions that objectively quantify the risk and benefit that an individual patient may experience after anatomic and reverse shoulder replacement, aligning patient and surgeon expectations for shared decision making.”