Medical device company Exactech has launched new data-driven, clinical decision support tool, Predict+, which predicts individual patient outcomes after shoulder replacement surgery using machine learning to support surgeon decision making.
Developed in collaboration with AI healthcare platform KenSci, the software has been designed to inform surgeons on the expected outcomes of shoulder arthroplasty.
It uses the clinical experience documented within the single-shoulder prosthesis outcomes database that contains over 10,000 patients.
Exactech Extremities vice-president Chris Roche said: “Predict+ is a new application of clinical research that represents a significant advancement in the patient consultation process.
“Using machine learning analyses, 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 and aligns patient and surgeon expectations in order to improve patient satisfaction.”
The surgeon can enter 19 data points into the software about a patient within minutes. The software can predict the patient’s potential outcomes.
Based on the data from other patients with similar age, gender and prosthesis type, the outcomes include pain and range of motion.
Furthermore, Predict+ compares results for anatomic and reverse shoulder arthroplasty at multiple postoperative time points.
With the help of such analysis, the surgeon can personalise patient treatment by detecting factors that drive the outcome predictions, including modifiable factors like the patient losing weight, quitting smoking, and completing pre-habilitation.
Moreover, the software merges the outcomes and complications within the database for the surgeons and patients to compare the personalised predictions with the clinical experience of similar patients.
Available worldwide on a limited basis, Predict+ supports Exactech’s Equinoxe shoulder and the ExactechGPS guided surgery system.