# Utilizing the International Classification of Functioning, Disability and Health (ICF) in forming a personal health index

**Authors:** Ilkka Rautiainen, Lauri Parviainen, Veera Jakoaho, Sami Äyrämö, Jukka-Pekka Kauppi  
**arXiv:** [2304.06143](https://arxiv.org/abs/2304.06143)  
**Date:** 2023-03-30  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2304.06143v1/

## Key points

- Proposal for a new model to monitor individuals' health status by calculating a personal health index
- Challenge of attributing changes in health to various factors such as physical illness, psychological well-being, and social aspects
- Suggestion to use the International Classification of Functioning, Disability and Health (ICF) as the central framework for constructing the personal health index
- Incorporation of comprehensive framework to capture multiple dimensions of health including physical, psychological, and social factors
- Ability to handle incomplete and heterogeneous data sets collected using different techniques
- Leveraging ICF as a common language for describing functioning, disability, and health to ensure consistency and comparability across diverse data sources
- Validation of the model's effectiveness through comparison with self-assessed health measures during rehabilitation
- Practical applicability of the proposed model for monitoring and evaluating individuals' well-being.

## Summary

We propose a new model for comprehensively monitoring the health status of individuals by calculating a personal health index. This is particularly challenging as changes in a person's functioning and health can be attributed to various factors, including physical illness, psychological well-being, and social aspects. To address this challenge, we suggest utilizing the International Classification of Functioning, Disability and Health (ICF) developed by the World Health Organization as the central framework for constructing a personal health index. The ICF provides a structured and standardized classification system that covers all relevant aspects affecting an individual's health. By incorporating this comprehensive framework into our model, we aim to capture and evaluate multiple dimensions of health in a unified manner. This approach allows us to consider not only physical conditions but also psychological and social factors that contribute to overall well-being. One key advantage of our model is its ability to handle incomplete and heterogeneous data sets collected using different techniques. We recognize that global standardization of health status measurement procedures is difficult due to variations in standards and practices across countries. For example, different clinics may use different health questionnaires or operate in different languages. Therefore, simply concatenating data sets from separate clinics is not feasible. By leveraging the ICF as a common language for describing functioning, disability, and health, our model enables the integration of diverse data sources while maintaining consistency and comparability. This ensures that the personal health index reflects an accurate representation of an individual's overall health status regardless of variations in data collection methods. To validate the effectiveness of our proposed model, we compared the calculated personal health index with two self-assessed health measures provided by individuals undergoing rehabilitation. The results indicate that our model yields valid outcomes in terms of assessing an individual's health status. This suggests that our proposed model has practical applicability for monitoring and evaluating individuals' well-being. In conclusion, our refined summary highlights how our proposed model addresses the challenge of comprehensively monitoring individuals' health status by calculating a personal health index. By incorporating the ICF framework and accommodating diverse data sets, our model provides a standardized and comprehensive approach to assessing overall health. The validation results further support the practical applicability of our model in practice.