Mestrado em Saúde Coletiva

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http://repositorio.ufes.br/handle/10/17586

Nível: Mestrado Acadêmico
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Navegando Mestrado em Saúde Coletiva por Autor "Almeida, Veronica da Fonseca"

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    Apoio digital sobre interações medicamentosas: qualificando a assistência farmacêutica
    (Universidade Federal do Espírito Santo, 2021-07-07) Almeida, Veronica da Fonseca; Primo, Cândida Caniçali; https://orcid.org/0000000151412898; http://lattes.cnpq.br/4739920753105018; https://orcid.org/0000-0003-0733-7346; http://lattes.cnpq.br/0482525670881235; Esposti, Carolina Dutra Degli; https://orcid.org/0000000181027771; http://lattes.cnpq.br/7465412734380334; Gonçalves, Rita de Cássia Ribeiro; https://orcid.org/0000000193522454; http://lattes.cnpq.br/6525693905417002
    Introduction: Electronic prescription has played a significant role in public health services, reducing adverse events and medication errors, helping health professionals to prevent errors, improving adherence to drug treatment and qualifying pharmaceutical assistance in primary care. Objective: Implement improvements in the drug prescription system of Rede Bem-Estar, describe and evaluate drug interactions of drugs contained in the system and Implement the drug interaction alert functionality in the Rede Bem-Estar system. Method: This is an implementation research (Implementation Science), which was developed in three stages: 1) Description and evaluation of the 2,119 drug interactions contained in the system by the researchers following the criteria of the Micromedex, Lexicomp and Memed databases, 2) Evaluation of interactions by a group of pharmacists in three rounds, 3) Implementation of drug interaction alert by the technology team. Results: Of the 2,119 database interactions, 1,277 were excluded, which were not included in the Micromedex, Lexicomp and Memed databases. The 842 interactions were classified according to severity, with 520 IMs being severe type, 261 IMs being classified as moderate and 61 being mild. After the first round of pharmacist evaluation, 64 interactions were excluded and the contraindicated classification was included. Thus, interactions were reclassified, leaving 61.1% (n=475) as severe; 30.2% (n=235) moderate; 5.3% (n=41) mild and 3.5% (n=27) contraindicated. In the second round of evaluation, of the 842 interactions, 792 were considered relevant, with 60.7% (n=481) of the severe type, 30.9% (n=245) moderate, 4.9% (n=39) mild and 3.4% (n=27) contraindicated. In the third round of evaluation, the bank had 531 interactions, being (n=331) 62.3% of the Serious type; (n=162) 30.5% Moderate; (n=31) 3.2% Contraindicated, (n=21) 4% of the Mild type. In the implementation, the technology team included the interaction bank in the electronic prescription system and when the professional prescribes the drug, it automatically generates an interaction alert on the side of the screen informing the level of severity of the interaction against the combination of medications prescribed by the healthcare professional. Conclusion: the implementation of the drug interaction alert is a tool to support clinical decision and can reduce the risk of adverse drug reactions, promoting patient safety, reducing prescription errors and adverse events, with a positive impact on the quality of prescription.