Moderator: Shay Bess, MD
Predictive analytics are increasingly employed by medical systems to evaluate patients and improve clinical care outcomes. This instructional course will provide a methodological overview of techniques used to employ predictive analytics to medical databases, and share research findings from the International Spine Study Group and the European Spine Study Group designed to improve counseling for adult spinal deformity patients undergoing surgery.
Upon completion of this session, participants should gain strategies to:
- Understand the science of predictive analytics and identify appropriated computer modeling and statistical techniques used for the field of predictive analytics;
- Familiarize with computer-based platforms usable to assess adult spine deformity patients;
- Use predictive analytics to council adult spinal deformity patients on anticipated surgical complications and clinical outcomes;
- Identify platforms usable to generate cost savings for adult spine deformity surgery.
Agenda
Introduction
Shay Bess, MD
Evolving From Risk Stratification to Predictive Models to Improve Outcomes in Adult Spine Deformity Surgery
Christopher P. Ames, MD
Applying Predictive Models to Identify Ideal Spinal Alignment for Adult Spinal Deformity
Virginie Lafage, PhD
Use of Predictive Models to Anticipate Complications in Adult Spine Deformity Surgery
Breto Line, MS
Questions
Faculty
Are Currently Used Patient-Reported Outcome Measures Compatible with Predictive Models for Adult Spine Deformity
Michael P. Kelly, MD
Platforms for Hospital Model Training and Application for Providers and Hospitals
Shay Bess, MD
Applying Predictive Models to Cost Analysis in the Care of Adult Spine Deformity
Jeffrey L. Gum, MD
Closing Comments and Questions
Faculty