The Charlson Comorbidity Index: A System for Identifying Patients with High Future Healthcare Costs

Background & Unmet Need

• Health costs in the U.S. have been rising significantly, at a pace that is unsustainable
• To have the best chance of reducing costs, interventions must target those patients who are most likely to incur future high costs
• Previous work by the Congressional Budget Office determine that multiple chronic conditions was the best predictor of sustained high costs
• However, there is no consensus about the criteria to define multiple chronic diseases and the definition varies considerably between studies
• Unmet Need: Method to define and categorize patients with multiple comorbidities to improve predictions of high healthcare cost producers

Technology Overview

• The Technology: Application of the Charlson Comorbidity Index (CCI) to identify patients who will incur high future healthcare costs
• The CCI was originally developed to predict survival, and is a measure of aggregate chronic disease burden
• Here, the CCI was used to predict health costs in the subsequent year, performing as well as prior cost and Diagnostic Cost Group (DCG) in identifying patients in the top 5% or 10%
• As the comorbidity index increased, total yearly costs increased significantly (P<.001)
• The CCI may therefore be used prospectively to identify patients who are likely to incur high costs, and aid in the development of cost mitigation strategies

Technology Applications

• Predicts and identifies patients who will incur high future healthcare costs and high futures rates of hospitalization
• Enables optimal healthcare resource management to control costs

Technology Advantages

• Demonstrated ability to predict high healthcare utilizers
• Allows healthcare systems to intervene early to help patients better manage chronic conditions