AUTHOR=Leal Lisiane Freitas , Osorio-de-Castro Claudia Garcia Serpa , Souza Luiz Júpiter Carneiro de , Ferre Felipe , Mota Daniel Marques , Ito Marcia , Elseviers Monique , Lima Elisangela da Costa , Zimmernan Ivan Ricardo , Fulone Izabela , Carvalho-Soares Monica Da Luz , Lopes Luciane Cruz 

TITLE=Data Sources for Drug Utilization Research in Brazil—DUR-BRA Study

JOURNAL=Frontiers in Pharmacology

VOLUME=Volume 12 - 2021

YEAR=2022

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2021.789872

DOI=10.3389/fphar.2021.789872

ISSN=1663-9812

ABSTRACT=Background
In Brazil, studies that map electronic healthcare databases in order to assess their suitability for use in pharmacoepidemiologic research are lacking. We aimed to identify, catalogue, and characterize Brazilian data sources for Drug Utilization Research (DUR).
Methods
This study is part of the project entitled, “Publicly Available Data Sources for Drug Utilization Research in Latin American (LatAm) Countries.” Brazilian health experts gathered to map secondary administrative data from healthcare organizations that might provide information related to medication use. A multi-phase approach including internet search of institutional government websites, traditional bibliographic databases, and experts’ input was used for mapping the data sources. The reviewers searched, screened and selected the data sources independently; disagreements were resolved by consensus. Data sources were grouped into (i) automated databases; (ii) Electronic Medical Records (EMR); (iii) national surveys or datasets; (iv) adverse event reporting systems; and (v) others. Each data source was characterized by accessibility, geographic granularity, setting, type of data (aggregate or individual-level), and years of coverage. 
Results
A total of 62 data sources were identified and screened; 38 were fully characterized. We grouped 23 (60%) as automated databases, four (11%) as adverse event reporting systems, four (11%) as EMRs, three (8%) as national surveys or datasets, and four (11%) as other types. Eighteen (47%) were classified as publicly and conveniently accessible online; providing information at national level. Data coverage lasted five years or more for most data sources. Individual and aggregated-level data were found, but no information about population covered was provided. Drug coding was not uniform; each data source has its own coding system, depending on the purpose of data. 
Conclusions
There are several types of data sources for DUR in Brazil, but a uniform system for drug classification and data quality evaluation does not exist. The extent of population covered by year is unknown. Our comprehensive and structured inventory reveals a need for full characterization of these data sources.