JMIR Publications

ABSTRACT

Background:

Rare diseases are conditions characterized by having a low prevalence in the general population, but collectively, it is estimated that they can affect up to 10% of the world population. Thus, rare diseases have a significant impact on public health systems worldwide. However, data, information, and knowledge regarding diagnoses, processes, and treatments for such diseases generally do not have a validated structuration available for use in different health services, making exchanging and reusing informational elements a complex task. Thus, investigating a minimum data set for ​​rare diseases is the central aspect to consider in this study.

Objective:

This systematic review aims to identify the minimum data sets used for RDs in healthcare networks worldwide. Subsequently, analyze such findings against the Brazilian Policy for Comprehensive Care for People with Rare Diseases and the World Health Organization guidelines and recommendations. To suggest a general minimum data set for rare diseases to improve the standardization and interoperability of data about diagnostic and care processes in the rare diseases area.

Methods:

For this systematic review, we used the Population, Concept, and Context methodology to define the guiding question of the review, which seeks to identify and map the variables used in the minimum datasets in healthcare networks worldwide. Subsequently, we used the research question to create the search strategy according to the MeSH descriptors. We inserted the search strategy defined in the chosen databases to select the first set of studies. We screened these studies through their abstract and, after that, through the full-text reading phase. Considering the established eligibility criteria, we finalized the selection stage of the review studies. Subsequently, we extract data and information from these articles in a structured way, using synthesis and analysis methods, to answer the research question. Throughout the process, we used the Prisma Checklist to ensure the quality of each step of this study.

Results:

Initially, we identified 407 studies from the selected databases. After all screening steps, 20 studies were included in the systematic review. These studies encompass 8 different study designs. Most of the datasets identified and mapped came from projects on the European continent. Results referring to America and Asia were also found. The variables used in rare disease records worldwide were identified and extracted. Subsequently, we used data science methods and clinical experience to structure and recommend a fundamental minimum standardized dataset for use in rare disease patient records in healthcare networks.

Conclusions:

This study is a techno-social contribution that aims to consolidate a consistent information base for registering rare disease patients in health networks. To improve the ability to represent the real health scenario in each context of rare diseases. In addition to facilitating information sharing, health planning, and decision-making. Clinical Trial: CRD42021221593