Monitoring Health Status: Development and Preliminary Validation of a Personal Health Index Using the International...

Area of Science:

• Health Informatics
• Biostatistics
• Rehabilitation Science

Background:

• Effective health monitoring is crucial for personalized care and health assessment.
• Personal health indices and profiles summarize an individual's health status.
• Global standardization of health metrics is hindered by diverse data practices.

Purpose of the Study:

• To present a novel model for computing personal health indices and profiles.
• To utilize the International Classification of Functioning, Disability and Health (ICF) framework.
• To provide standardized and interpretable health metrics from heterogeneous datasets.

Main Methods:

• Developed a recursive algorithm based on the ICF's hierarchical structure.
• Incorporated time decay and linkage reliability for data weighting.
• Validated the model using data from 505 individuals and statistical correlation analyses.

Main Results:

• The computed health index correlated positively with self-assessed health (EuroQol Visual Analogue Scale) and negatively with pain.
• Sensitivity analysis confirmed model robustness and predictable behavior.
• The model demonstrated resilience in handling missing or incomplete data.

Conclusions:

• The proposed model provides a flexible, scientifically grounded approach for personal health indices within the ICF framework.
• It facilitates integration of diverse health data and visual representation for clinical and personal use.
• Potential applications include health monitoring, rehabilitation planning, and health informatics.