Dr. Parsons has participated in a multicenter clinical research study that has led to the recent submission of an article in the Journal of Shoulder and Elbow Surgery, entitled, “Risk Factors for Complications and Revision Surgery after Anatomic and Reverse Total Shoulder Arthroplasty.” The goal of this study was to identify factors that may lead to adverse outcome from shoulder replacement. Such factors include demographic factors, medical conditions, prior surgery, preoperative diagnosis, and preoperative function. If surgeons can identify in advance which patients are at a higher risk for postoperative complication, measures can be taken to address modifiable risk factors.
The results of this study are part of a larger project spearheaded by Exactech Inc. to use machine learning to help predict patient-specific outcomes after shoulder replacement by comparing individual patients to age, gender and diagnosis-matched patients from a large clinical database that includes over 10,000 patients who have already undergone surgery. Parsons is one of the surgeons working in collaboration with engineers and data scientists to develop this artificial intelligence technology.
Collectively this research will help to advance outcomes after shoulder replacement by determining ways to optimize patients in advance of surgery. Future work will extend the capability of the machine learning technology to help surgeons plan implant placement and choose the optimal implant configuration that will lead to the best improvement in function.
Parsons, who performed a fellowship in shoulder and elbow surgery, has a specialty interest in shoulder replacement and was the first surgeon in the state to perform a reverse total shoulder in 2004. Over the past 17 years, he has performed over 1,000 standard and reverse shoulder replacements and is one of just 3 surgeons in New Hampshire who are members of the American Shoulder and Elbow Surgeons.