A new population-based risk stratification tool was developed and validated for predicting mortality, hospital...

Area of Science:

• Public Health
• Epidemiology
• Health Services Research

Background:

• Population-based risk stratification is crucial for predicting patient outcomes.
• Existing tools may not adequately capture the complexity of chronic conditions and their impact on mortality and healthcare utilization.

Purpose of the Study:

• To develop and validate a novel population-based risk stratification tool, the Chronic Related Score (CReSc).
• To assess the CReSc's ability to predict 5-year mortality, hospital admissions, and healthcare costs.
• To investigate the relationship between CReSc and socioeconomic factors like income.

Main Methods:

• Developed the CReSc using Cox model coefficients from 5.4 million National Health Service (NHS) beneficiaries in Italy's Lombardy Region.
• Validated the CReSc on an independent sample of 2.7 million NHS beneficiaries.
• Assessed predictive performance using discrimination (Area Under the Curve) and calibration, and investigated secondary endpoints and income correlation.

Main Results:

• The CReSc demonstrated good predictive performance with an Area Under the ROC Curve of 0.730 for 5-year mortality.
• The tool showed improved reclassification of risk (44% to 52%) compared to existing scores and exhibited remarkable calibration.
• Increasing CReSc was associated with higher rates of mortality, hospital admissions, and healthcare costs, with higher income groups showing a better CReSc profile.

Conclusions:

• The developed Chronic Related Score (CReSc) is a validated tool for predicting mortality, hospital admissions, and healthcare costs in a large population.
• The CReSc has the potential for significant clinical and operational impact in managing patient risk and resource allocation.
• Risk stratification using CReSc may reveal socioeconomic disparities in health outcomes.