Enhancing Value-Based Healthcare with Reconstructability Analysis: Predicting Risk for Hip and Knee Replacements

Abstract

Legislative reforms aimed at slowing growth of US healthcare costs are focused on achieving greater value, defined specifically as health outcomes achieved per dollar spent. To increase value while payments are diminishing and tied to individual outcomes, healthcare must improve at predicting risks and outcomes. One way to improve predictions is through better modeling methods. Current models are predominantly based on logistic regression (LR). This project applied Reconstructability Analysis (RA) to data on hip and knee replacement surgery, and considered whether RA could create useful models of outcomes, and whether these viii-Relating RA to LR .