Digital health for the End TB strategy: from linked data integration to a better evidence-based decision making

• Grant number: 20/01975-9
• Support Opportunities: Research Grants - eScience and Data Science Program - Regular Program Grants
• Start date: October 01, 2020
• End date: March 31, 2024
• Field of knowledge: Interdisciplinary Subjects
• Principal Investigator: Domingos Alves
• Grantee: Domingos Alves
• Host Institution: Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated researchers: Aline Aparecida Monroe ; Antonio Ruffino Netto ; Kumar Abhishek ; Lariza Laura de Oliveira ; Mauro Niskier Sanchez ; Newton Shydeo Brandão Miyoshi ; Rafael Mello Galliez ; Rubia Laine de Paula Andrade ; Tereza Cristina Scatena Villa ; Valdes Roberto Bollela
• Associated scholarship(s): 22/02683-7 - Training and implementation management at DRS XIII and HCFMRP-USP, BP.TT; 22/00021-7 - CONECTB: integration Mechanisms for Tuberculosis, BP.IC; 22/00020-0 - DSS-TB: decision support system for Tuberculosis, BP.IC; 21/05070-3 - RE-AIM approach for analyzing implementation research in the context of Tuberculosis, BP.PD; 21/01961-0 - Study and application of machine learning techniques unsupervised in the analysis of undesirable outcomes in the treatment of Tuberculosis, BP.MS

Abstract

Integrated care for people affected by tuberculosis requires not only the implementation of basic prevention and care actions but also the strengthening of integration between the different health services, programs, and existing care levels. These levels resolution varies according to financial resources, technical, human and infrastructure services that are part of the health care network. Given this scenario, it is imperative to develop Health Information Systems that can contribute to the activities of epidemiological surveillance and monitoring of tuberculosis patients. Such a system will allow registering, monitoring and evaluating the patient and their respective contacts, storing from the most basic information to data on treatment, examinations, and hospitalizations. Therefore, we need the development of an information system for services provided to the community, in order to facilitate data collection, reduce losses and enable better analysis, visualization and information handling. This way, the treatment and evolution of the disease can be monitored more precisely by the professionals involved. It is expected to support health professionals in the 26 municipalities that are part of the Ribeirão Preto Regional Health Department, enabling access and monitoring of data with greater ease, speed and efficiency. This will be done in collaboration with the epidemiological surveillance team in the region, taking into account the diversity of situations found in each municipality. Respecting legal issues advocated by the Ministry of Health and W3C recommendations, all tasks will be supported by Semantic Web techniques. Thus, the system will be adapted to meet the needs of the region and allow interoperability with other systems, besides the incorporation of forecasting models to provide a decision support module for health professionals and managers. (AU)

Scientific publications

(4)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

LIMA, VINICIUS COSTA; RIJO, RUI PEDRO CHARTERS LOPES; BERNARDI, FILIPE ANDRADE; COLOMBO FILHO, MARCIO ELOI; BARBOSA-JUNIOR, FRANCISCO; PELLISON, FELIPE CARVALHO; GALLIEZ, RAFAEL MELLO; KRITSKI, AFRANIO LINEU; ALVES, DOMINGOS. REDbox: a comprehensive semantic framework for data collection and management in tuberculosis research. SCIENTIFIC REPORTS, v. 13, n. 1, p. 14-pg., 2023-05-11. (20/01975-9)

CARVALHO, ISABELLE; NEIVA, MARIANE BARROS; BRANDAO MIYOSHI, NEWTON SHYDEO; CREPALDI, NATHALIA YUKIE; BERNARDI, FILIPE ANDRADE; LIMA, VINICIUS COSTA; DOS SANTOS, KETLIN FABRI; DE ANDRADE MIOTO, ANA CLARA; MOZINI, MARIANA TAVARES; GALLIEZ, RAFAEL MELLO; et al. Knowledge Discovery in Databases: Comorbidities in Tuberculosis Cases. COMPUTATIONAL SCIENCE - ICCS 2022, PT III, v. 13352, p. 11-pg., 2022-01-01. (22/00020-0, 20/01975-9)

LIMA, VINICIUS COSTA; BERNARDI, FILIPE ANDRADE; ALVES, DOMINGOS; KRITSKI, AFRANIO LINEU; GALLIEZ, RAFAEL MELLO; CHARTERS LOPES RIJO, RUI PEDRO. A Permissioned Blockchain Network for Security and Sharing of De-identified Tuberculosis Research Data in Brazil. METHODS OF INFORMATION IN MEDICINE, v. 59, n. 06, p. 205-218, DEC 2020. (20/01975-9)

LIMA, VINICIUS COSTA; ALVES, DOMINGOS; BERNARDI, FILIPE ANDRADE; RIJO, RUI PEDRO CHARTERS LOPES. Security approaches for electronic health data handling through the Semantic Web: A scoping review. SEMANTIC WEB, v. 14, n. 4, p. 14-pg., 2023-01-01. (22/02683-7, 20/01975-9)