Project Details
Description
Objective 1: Determine the patient cohorts to use, the variables to incorporate, and the observation window.
to. Analysis of available information and integration of sources.
b. Study of possible patient cohorts and observation windows.
c. Analysis of clinical indicators of disease monitoring.
Objective 2: Determination and estimation of the appropriate statistical model for making the predictions.
to. Definition of risk factors.
b. Training and testing of machine learning models.
c. Analysis of results and validation by experts.
Objective 3: Incorporate the model into the SISCAC system
to. Socialization and appropriation of the tool in the institutionality of the CAC.
to. Analysis of available information and integration of sources.
b. Study of possible patient cohorts and observation windows.
c. Analysis of clinical indicators of disease monitoring.
Objective 2: Determination and estimation of the appropriate statistical model for making the predictions.
to. Definition of risk factors.
b. Training and testing of machine learning models.
c. Analysis of results and validation by experts.
Objective 3: Incorporate the model into the SISCAC system
to. Socialization and appropriation of the tool in the institutionality of the CAC.
Keywords
Health economics, Statistical model, Diabetes.
| Status | Finished |
|---|---|
| Effective start/end date | 7/15/21 → 12/31/21 |
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
Main Funding Source
- National
Location
- Bogotá D.C.
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Prizes
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Reconocimiento de IPS y EPS para el fortalecimiendo de la gestión del riesgo
Rodriguez Lesmes, Paul Andres (Recipient), Apr 2022
Prize