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Bridging Gaps with Generative AI: Enhancing Hypertension Monitoring Through Patient and Provider Insights.
Andreadis, Katerina; Rodriguez, Danissa V; Zakreuskaya, Anastasiya; Chen, Ji; Gonzalez, Javier; Mann, Devin.
Afiliação
  • Andreadis K; New York University Grossman School of Medicine, New York, USA.
  • Rodriguez DV; New York University Grossman School of Medicine, New York, USA.
  • Zakreuskaya A; New York University Grossman School of Medicine, New York, USA.
  • Chen J; Machine Learning and Data Analytics Lab, Univerity Erlangen-Nuremberg, Germany.
  • Gonzalez J; MCIT Department of Health Informatics, New York University Langone Health, New York, USA.
  • Mann D; MCIT Department of Health Informatics, New York University Langone Health, New York, USA.
Stud Health Technol Inform ; 316: 939-943, 2024 Aug 22.
Article em En | MEDLINE | ID: mdl-39176946
ABSTRACT
This study introduces a Generative Artificial Intelligence (GenAI) assistant designed to address key challenges in Remote Patient Monitoring (RPM) for hypertension. After a comprehensive needs assessment from clinicians and patients, we identified pivotal issues in RPM data management and patient engagement. The GenAI RPM assistant integrates a patient-facing chatbot, clinician-facing smart summaries, and automated draft portal messages to enhance communication and streamline data review. Validated through six rounds of testing and evaluations by ten participants, the initial prototype was positively received, highlighting the importance of personalized interactions. Our findings demonstrate GenAI's potential to improve RPM by optimizing data management and enhancing patient-provider communication.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Hipertensão Limite: Humans Idioma: En Revista: Stud Health Technol Inform Assunto da revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Hipertensão Limite: Humans Idioma: En Revista: Stud Health Technol Inform Assunto da revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos