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Revista de la Universidad Industrial de Santander. Salud

versão impressa ISSN 0121-0807versão On-line ISSN 2145-8464

Resumo

DAZA S, Genaro; CASTANEDA, Jhon Jairo  e  CASTANO, Jorge Iván. Data analytics platform for population characterization and cardiovascular risk assessment in patients from the west-center of Colombia. Rev. Univ. Ind. Santander. Salud [online]. 2022, vol.54, e311.  Epub 20-Out-2022. ISSN 0121-0807.  https://doi.org/10.18273/saluduis.54.e:22042.

Introduction:

Cardiovascular diseases are the leading cause of death in the world. Countless research has been directed towards the prediction of cardiovascular risk, in order to avoid the threat. Furthermore, the implementation automated data analysis tools have been sought to allow for information to be made readily available, not only to administrative and managerial staff, but also to clinical staff to improve the control of pathologies.

Objective:

To build a tool for the characterization of the population and the evaluation of cardiovascular risk in patients from central-western Colombia.

Materials and methods:

The construction of a platform for the analysis of sociodemographic and clinical data is proposed. The overall platform design model is evolutionary development, which intertwines specification, development, and validation activities. The platform presents a Vista-Controller model, which allows the creation of dynamic templates distributed in access modules controlled by user profiles.

Results:

The automated calculation of cardiovascular disease risk and the issuance of early warnings were implemented, which improved the management of clinical processes, as well as support for administrative decision-making, through the creation of two interactive modules on the platform.

Conclusions:

The union of clinical, administrative and engineering knowledge allowed the consolidation of a tool that contributes to the monitoring and traceability of patients, which guides the prioritization of possible interventions that impact the health of patients.

Palavras-chave : Cardiovascular diseases; Risk factors; Data science; Technological development; Colombia.

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