Felipe Ocampo, Engineer at the Clinical Research Center, participated in the Qualinn event with the conference: “Optimization of machine learning algorithms for the prediction of non-attendances in outpatient appointments, in the Internal Medicine department.”
The automation process presented is based on performing a statistical analysis to identify the variables that influence patient no-shows and then consolidating the artificial intelligence model to accurately validate this information. To carry out this machine learning process, the institution considers variables such as clinical and sociodemographic characteristics, among others.
“We are in the validation phase so that the Hospital can implement it. Basically, we consolidated an artificial intelligence model that allows us to identify potential patients who will not attend their medical appointment (in Internal Medicine). While the Fundación Valle del Lili It has multiple strategies to guarantee assistance; a way has been sought to make them more focused or segmented on a specific population.”Ocampo indicates.
The implementation of this model aims to achieve personalized predictions, optimize communication channels, reduce financial losses, and integrate with the institution's current strategies. It also seeks to reduce patient no-shows.
