Peer-Reviewed Publication
J Med Internet Res2026;28e84444.May 26, 2026Journal Article
Large Language Model-Generated Patient Instructions for Prescriptions in Primary Health Care: Preclinical Algorithm Validation.
Zilma Silveira Nogueira Reis1, Elisa Tuler Albergaria2, Adriana Silvina Pagano3, Eura Martins Lage4, Flávia Ribeiro de Oliveira4, Cristiane Dos Santos Dias4, Juliana Almeida Oliveira4, Gláucia Miranda Varella Pereira4, Isaias Jose Ramos de Oliveira4, Érico Franco Mineiro5, Igor Carvalho Lima Oliveira5, Davi Dos Reis de Jesus2, Antônio Pereira de Souza Júnior2, Igor de Carvalho Gomes6, Rodrigo André Cuevas Gaete6, Ricardo Cruz-Correia7, Leonardo Rocha2
1Health Informatics Center, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
2Computer Science Department, Universidade Federal de São João Del Rei, São João Del Rei, Brazil.
3Arts Faculty, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
4Department of Physiotherapy, School of Physical Education, Physiotherapy and Occupational Therapy, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
5School of Architecture, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
6National Secretary of Primary Care of the Brazilian Ministry of Health, Brasilia, Brazil.
7MEDCIDS, Porto University, Porto, Portugal.
Abstract
BACKGROUND: The application of generative artificial intelligence to simplify medication use instructions has the potential to enhance people's health by improving treatment adherence.
OBJECTIVE: We evaluated the performance of large language models (LLMs) in generating medication usage instructions to complement prescriptions in primary health care.
METHODS: This randomized, blinded experimenta…
Create a free account to keep reading
Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.
Want unlimited research access? See Pro plans