4.2 Article

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

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CADERNOS DE SAUDE PUBLICA
卷 39, 期 5, 页码 -

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CADERNOS SAUDE PUBLICA
DOI: 10.1590/0102-311XPT173922

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Drug Utilization; Anti-bacterial Agents; Pharmacoepidemiology; Health Information Systems; Data Accuracy

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The Brazilian National System of Controlled Product Management (SNGPC) stores and analyzes data on the dispensing of manufactured and compounded drugs, including controlled and antimicrobial drugs. The study assessed the quality of SNGPC data on manufactured antibiotics and proposed their use in drug utilization research (DUR). Despite vulnerabilities in data quality, the SNGPC provides valuable insights into community use of antimicrobials and controlled drugs.
The Brazilian National System of Controlled Product Management (SNGPC) stores data on the dispensing of manufactured and compounded drugs and pharmaceutical inputs, whether con-trolled 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 retro-spective 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 dimen-sion unreported was systematically identified in the variables active ingredient, sex, age and ICD-10. The amount of vials/bottles and pack-ages 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 out-side 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.

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