Accepted for/Published in: JMIR Research Protocols
Date Submitted: Oct 7, 2020
Date Accepted: Dec 15, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
RARASnet: Mapping, infrastructure and data analysis for the Brazilian Network of Rare Diseases - a Study Protocol
ABSTRACT
Background:
A rare disease is a medical condition with low prevalence in the general population, but that collectively can affect up to 10% of the population. Thus, rare diseases have a significant impact on the healthcare system, and health professionals must be familiar with the diagnosis, management, and treatment.
Objective:
To provide health indicators regarding the rare diseases in Brazil, and to create a network of reference centers with health professionals from different regions of the country, the RARASnet proposes to map, analyze and communicate all the data regarding the infrastructure of the centers, and the patient's evolution or needs. The focus of the proposed study is to provide all the technical infrastructure and analysis following the World Health Organization and the Brazilian Ministry of Health guidelines.
Methods:
To build this digitized system, we will provide a security framework to assure the privacy and protection of each patient when collecting data. Also, DevOps methodologies will be applied to align software development, infrastructure operation, and quality assurance. After data collection of all information designed by specialists, the computational analysis, modeling, and results will be communicated in scientific research papers and in a digital health observatory.
Results:
The project has several activities and it is in an initial stage. Initially, a survey was applied to all health care centers to understand the technical aspects of each network member such as the existence of computers,technical support staff, and digitized systems. In this survey, we detected that 64% of participating health units have electronic medical records, while 36% have paper records. Therefore, we will have different strategies to access the data from each center.
Conclusions:
The nature of rare disease diagnosis is complex and diverse, and many problems will be faced in the evolution of the project. However, decisions based on data analysis are the best option for the improvement of the rare disease network in Brazil. The creation of the RARASnet, along with all the digitized infrastructure, can improve the accessibility of information and standardization of the rare diseases in the country.
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