Data Mining to Assist in Strategic Decision Making in CISAM-UPE Telecare

Abstract

This study aimed to enhance the quality of patient care at the Amaury de Medeiros University Health Center, part of the University of Pernambuco (CISAM-UPE). The initiative was based on analyzing patterns in historical telehealth data using Data Science tools and institution-defined parameters to support strategic decision-making, prioritizing care for patients in critical and urgent conditions. Initially, it was necessary to align business interests with data mining objectives and establish success criteria for the models to be developed. The CRISP-DM methodology (Cross Industry Standard Process for Data Mining) was selected as a guide for systematically executing data mining activities. As a result, models were created using specific data mining software and libraries. These models provide essential insights that enable the development of new care strategies, focusing on prioritizing the most critical and urgent cases.