Shoulder surgeon is looking at shoulder arthroplasty data to try to determine risks for complications and revisions in shoulder replacement cases

Leveraging Data in Shoulder Arthroplasty

The goal of shoulder arthroplasty is to improve comfort and function for a variety of degenerative conditions. Shoulder surgeons who engage an increasingly complex array of clinical problems must understand the factors that may negatively impact results and lead to a higher risk of complications. A better understanding of risk factors will help not only educate patients about potential adverse outcomes, but it also leads to improved ways to mitigate complications by addressing their root cause where possible.

Outpatient shoulder arthroplasty patient laying in hospital bed

Inpatient vs Outpatient Shoulder Arthroplasty

Thomas Obermeyer, MD, reviews a comparison study of readmissions and complications in inpatient and outpatient settings for patients 65 years and older. Read his thoughts on reevaluating shoulder arthroplasty as an inpatient-only procedure in our latest blog post.

image of the world's first machine learning measure called smart score

The World’s First Machine Learning-Derived Outcome Measure

Shoulder Arthroplasty Smart Score: The World’s First Machine Learning-Derived Outcome Measure | Surgeons and researchers worldwide can now quantify shoulder patient outcomes with a new, more efficient measure called “Smart Score”.

Computer screen is showing Predict+, which is a machine learning tool that helps to better predict patient outcomes

Using Machine Learning to Predict Patient Outcomes

Teaming up with KenSci, a data science company located in Seattle, Wash., Exactech has been at the forefront of using ML to better predict outcomes and complications after shoulder arthroplasty. This work is based on Exactech’s clinical database which includes over 11,000 patient visits from 35 centers around the world–all using a standardized data collection tool that records information on demographics, diagnosis, comorbidities, preoperative function, implant information and post-operative function at multiple time points. Predict+ was built on ML algorithms which established a 19-input minimal feature set that was most highly predictive of outcomes and complications after anatomic or reverse shoulder arthroplasty.

The image points out the glenoid part of the shoulder construct where superior glenoid wear can occur.

What About Superior Erosion?

Stephanie Muh, MD Read Complete Study: Reverse Total shoulder Arthroplasty with a Superior Augmented Glenoid Component for Favard Type – E1, E2 and E3 Glenoids Superior glenoid wear is often…
Managing patient expectation for external rotation after reverse shoulder arthroplasty

Managing Expectations for External Rotation After RSA

Joseph King, MD Read complete study: The influence of preoperative external rotation weakness or stiffness on reverse total shoulder arthroplasty Improvement in external rotation following Reverse Shoulder Arthroplasty (RSA) is an…