Creation of an infrastructure for visual analytics in medicine using information extracted from electronic health record

• Grant number: 16/23707-0
• Support Opportunities: Regular Research Grants - Overhead for Research and Education Network of the State of São Paulo
• Duration: February 01, 2017 - March 31, 2018
• Field of knowledge: Engineering - Biomedical Engineering - Bioengineering
• Principal Investigator: Marco Antonio Gutierrez
• Grantee: Marco Antonio Gutierrez
• Host Institution: Instituto do Coração Professor Euryclides de Jesus Zerbini (INCOR). Hospital das Clínicas da Faculdade de Medicina da USP (HCFMUSP). Secretaria da Saúde (São Paulo - Estado). São Paulo , SP, Brazil

Abstract

In the last 20 years, the deployment of Electronic Health Record (EHR) systems has been growing fast in Brazil. This new way of handling healthcare data allowed huge advances in storage, retrieval and sharing of patient information. Several benefits result from the use of EHRs; perhaps, the most important of them is possibility to view all patient data in real time at the point of care. In addition, medical researchers have now a huge amount of data that can be easily handled, which can help the generation of new knowledge based on increasingly robust statistics with benefits to the general population. On the other side, the access to a growing number of information can make the processes of data analysis more difficult. The difficulty is caused in part by the problem of information overload, which is a result from the current possibility of data collection and storage at a faster rate than the human ability to use this data for decision-making. The speed to collect and store data increases rapidly with each new advance in information and communication technologies. The possibility of losing relevant information is very large in the midst of such huge amount of data. The Heart Institute is a Healthcare Institution that after developing its own EHR - named SI3 - has a huge amount of data about patient care, which is a potentially rich source of information for obtaining new knowledge. Digital health data includes all textual information associated with the patient's history, images (mostly three-dimensional sets), videos and signals, genomic data and biometric sensors that gather data over long periods. Visual Analytics is discipline that emerged as a way to address the problems caused by information overload. It provides an integrated computational approach that combines visualization, human factors, and data analysis. It can be applied as an external help to filter, analyze and visualize data. This project proposes the creation of an infrastructure - based on a platform specific for processing large volumes of data - for development and use of VA tools. The long-term goal is to allow clinical research and applications for patient care from SI3 data (AU)