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GeoAsma project: Clinical Decision Support System for the Management of Asthma Patients


Although for decades there have been multiple studies on the association of asthma with factors such as weather conditions, pollution, pollen and the social condition of patients, the GeoAsma project aims to advance the study of environmental factors that influence the health of asthmatic patients by combining BigData technology and data mining analysis, Geographic Information Systems and open data provided by official sources with data from the Electronic Health Record of the Andalusian Health System, that provides healthcare services to more than 8,000,000 citizens.

This project aims to study through data mining techniques and multilevel analysis the influence of clinical and environmental factors: pollen level, air pollution, atmospheric conditions and social determinants in more than 800,000 asthmatic patients during the last 15 years in Andalusia, the southernmost region of Spain. It is expected that the results of this study will serve to define predictive models that will help professionals and patients in our region to make decisions.

After the validation of the models, a decision support system will be implemented in a web platform and in a mobile application. Its impact on the reduction of exacerbations, control, quality of life and resource consumption of asthmatic patients will be analysed. This evaluation will be carried out through a pilot with 214 patients with a follow-up period of 12 months with asthma in the hospitals participating in this proposal.


The Geoasthma project aims to define and evaluate a decision support system for professionals and patients based on the analysis of the influence of clinical and environmental characteristics on the population of asthmatic patients in Andalusia.

Starting Hypotheses

Big Data techniques for analyzing the influence of clinical and environmental factors on the population of asthmatic patients in our region can generate predictive models of exacerbation risk in these patients. The implementation of these predictive models in a decision support system for professionals, including a measure of exacerbation risk, could assist clinical professionals in making decisions that reduce the risk of exacerbation and improve disease control in asthmatic patients. Applying recommendations for asthmatic patients based on the analysis of pollen levels and real-time atmospheric conditions will help reduce their risk of exacerbation and improve disease control.


The GeoAsma project leverages the technology developed in the GeoHealth (PI19/01092) and Breath (PI20/01755) projects to define predictive models associated with the level of exacerbation risk in asthmatic patients and implement these models in a decision support system and a mobile application for the patient.




Development of the Geoasthma Project

The development of the project consists of several distinct phases:

Phase 1. Retrospective Study

Initially, a retrospective study will be conducted on the evolution of the population of asthmatic patients treated in Andalusia over the last 15 years. This study will combine data obtained from patients’ medical records with environmental data such as pollen levels, pollution levels, atmospheric data, etc. This study will help define predictive models for asthma exacerbation episodes.

Phase 2. Validation of Predictive Models

Subsequently, a 6-month study will be carried out to validate the predictive models in collaboration with the Allergology Unit. This study will assess the sensitivity and specificity of the predictive models defined in a real-world setting.

Phase 3. Pilot and Evaluation of the Decision Support System

Finally, to evaluate the intervention, a 12-month pilot will be conducted to assess the impact on the quality of life and disease control of implementing a mobile application and a decision support system incorporating the predictive models. This multicenter study will involve the collaboration of 7 different centers in Andalusia.


The Geoasthma project has been funded through the Research Projects call of the Ministry of Health and Consumer Affairs in 2020.

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