Data Sources for Drug Utilization Research in Latin American countries - a cross-national study: DASDUR-LATAM Study

Real-world treatment patterns of rheumatoid arthritis in Brazil: analysis of DATASUS national administrative claims data for pharmacoepidemiology studies (2010-2020)

Our study assessed DATASUS as a potential source for pharmacoepidemiologic studies in rheumatoid arthritis (RA) in the Brazilian population focusing on treatment patterns and determinants of initiating or switching to a novel therapy. This was a descriptive database study of RA patients with at least one claim of RA and ≥ 2 claims of disease-modifying anti-rheumatic drug (DMARD); conventional synthetic (cs), biologic (b) or targeted synthetic (ts) DMARD with more than 6 months of follow-up from 01-Jan-2010 to 31-Dec-2020. Analyses were stratified for SUS-exclusive and SUS+ private user cohorts. We identified 250,251 patients with RA in DATASUS: mean age of 58.4 years, majority female (83%) and white (58%). 62% were SUS-exclusive and 38% SUS+ private. Most common bDMARDs were adalimumab and etanercept. Age (adjusted odds ratio 1.78 [50+]; 95% CI 1.57-2.01), SUS exclusive status (0.53; 0.47-0.59), distance to clinic [160+ km] (0.57; 0.45-0.72), and pre-index csDMARD claims (1.23; 1.08-1.41) were independent predictors of initiating a novel oral tsDMARD. Switching from bDMARD to tsDMARD, associations were similar, except for the direction of associations for SUS exclusive status (adjusted hazard ratio 1.10; 1.03-1.18), distance to clinic (1.18; 1.03-1.35), and number of previous bDMARD (0.15; 0.14-0.16). DATASUS is a source suitable for treatment-related analyses in RA reflecting the public health system in Brazil.

[Data processing of the Brazilian National System of Controlled Product Management for drug utilization research with antimicrobials]

The Brazilian National System of Controlled Product Management (SNGPC) stores data on the dispensing of manufactured and compounded drugs and pharmaceutical inputs, whether controlled and antimicrobial, based on the records of private pharmacies and drugstores. This study assessed the quality of SNGPC data from the dispensing records of manufactured antibiotics, aiming to propose their use in drug utilization researchs (DURs), with a descriptive and retrospective design, analyzing the raw dataset of the SNGPC from January 2014 to December 2020. A total of 475,805,207 drug-dispensing records were collected. On average, antibiotics corresponded to 54.5% of the total records. The quality dimension "unreported" was systematically identified in the variables "active ingredient", "sex", "age" and "ICD-10". The amount of vials/bottles and packages ranged from one to 536 units and the amount of pharmaceutical inputs dispensed, from one to 7,500 units. Results show that 25% of the records exceed an individual therapy and the SNGPC has no critical mechanism to avoid dispensations outside the therapeutic standard for the class. Despite vulnerabilities due to data quality, which can be overcome, the SNGPC allows for the construction of different analytical plans, involving time and other aggregations, in the analysis of community use of antimicrobials and controlled drugs, which makes it a powerful source of data for DUR.

Drug utilization research in Peru: Is real-world data available?

Background: Drug utilization research (DUR) is used to provide evidence-based data to inform policies and make decisions. The aim of this study was to map and describe available data sources for drug utilization research in Peru. Methods: We performed a search of data sources providing information on medication use on the website of governmental organizations. We also conducted a literature review using PubMed, LILACs, and BVS. Independently, researchers screened eligible data sources. Data characterization included accessibility, coverage data provider, type of data sources, and setting. We performed a descriptive analysis. Results: We identified seven data sources, CENAFyT, ICI, IDI (SISMED), and ENSUSALUD from MINSA, and CRI-ESSALUD, SGSS/ESSI, and ENSSA from ESSALUD. These presented information on adverse drug reactions (n = 2), drug consumption, and distribution (n = 2), prescription and drug dispensing (n = 1), and surveys addressed to medication users (n = 2). ENSUSALUD was the only data source publicly available. VIGIFLOW and ENSUSALUD have a national granularity from the public and private sectors. The setting of the data sources was both hospital and ambulatory care. Two data sources have individual-level data on adverse drug reactions and one on prescriptions. Four studies on drug utilization research in Peru were derived from ENSUSALUD. Conclusion: In Peru, few data sources are available for drug utilization research. There is an increased need to monitor medications for decision-making purposes. Local and international initiatives and partnerships of the government with academic institutions and the private sector might be a good strategy to increase the transparency of health data and for supporting decision-making using drug utilization research.

Transparency of data on the value chain of medicines in Argentina, Brazil, and Colombia

Introduction: The transparency of data on the value chain of medicines is crucial for the study and monitoring of the pharmaceutical system. These data may impact medicine pricing negotiations, contribute to patient access to pharmaceutical products, and strengthen health systems. Objective: This study analyzed the national strategies to ensure the transparency of data from medicine cost development to marketing in Argentina, Brazil, and Colombia. Method: A descriptive study was carried out by searching databases, reports, documents, and scientific articles published between January and August 2022 related to rules on transparency and databases, including 1) marketing authorization; 2) pricing; 3) intellectual property; 4) clinical trials; 5) research and development (R&D); and 6) health technology assessment (HTA) of selected biopharmaceuticals. Results: Transparency data, rules, and information are not uniform. The infostructures (organizational capacity for collecting and distributing information) regarding the pharmaceutical value chain in these three countries face limitations in appropriate measures to publicly share data and evidence, including pre-clinical data, clinical data, and costs. None of the countries require transparency about data on research and development costs. All three countries present similar publicization of data on marketing authorization and intellectual property, with some differences. The significant limitations in Argentina include the absence of formal price regulation and data on the volume of medicine purchased and respective amounts paid. Among the three countries, Brazil showed a higher degree of information transparency, perhaps due to the legal regulation that guarantees citizens access to information of public interest. Brazil also stands out in terms of the public availability of HTA reports and pricing, in addition to the highest volume of information. In contrast, Colombia has in place a decree that allows 5 years of trial data exclusivity for new medicines, an act contrary to data transparency. Despite the different stages of transparency, no country has evidenced a robust use of these data in public policy decision-making. Conclusion: The results reinforce the presence of information asymmetry between stakeholders, data fragmentation, data gaps and overlap, and difficulty in comparing available data across the three countries and the use of these data nationally to produce evidence.

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

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: The present study is part of the project entitled, “Publicly Available Data Sources for Drug Utilization Research in Latin American (LatAm) Countries.” A network of Brazilian health experts was assembled 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 the following categories: 1) automated databases; 2) Electronic Medical Records (EMR); 3) national surveys or datasets; 4) adverse event reporting systems; and 5) others. Each data source was characterized by accessibility, geographic granularity, setting, type of data (aggregate or individual-level), and years of coverage. We also searched for publications related to each data source.

Results: A total of 62 data sources were identified and screened; 38 met the eligibility criteria for inclusion and 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. Most of them offered more than 5 years of comprehensive data coverage, and presented data at both the individual and aggregated levels. No information about population coverage was found. Drug coding is not uniform; each data source has its own coding system, depending on the purpose of the data. At least one scientific publication was found for each publicly available data source.

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.