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Mobile application development for improving medication safety in tuberculosis patients: A quasi-experimental study protocol.
Wijayanti, Erlina; Bachtiar, Adang; Achadi, Anhari; Rachmawati, Ummi Azizah; Sjaaf, Amal Chalik; Eryando, Tris; Siregar, Kemal N; Vidiawati, Dhanasari.
Afiliación
  • Wijayanti E; Faculty of Public Health, Universitas Indonesia, Depok, Indonesia.
  • Bachtiar A; Faculty of Medicine, YARSI University, Jakarta, Indonesia.
  • Achadi A; Faculty of Public Health, Universitas Indonesia, Depok, Indonesia.
  • Rachmawati UA; Faculty of Public Health, Universitas Indonesia, Depok, Indonesia.
  • Sjaaf AC; Faculty of Information Technology, YARSI University, Jakarta, Indonesia.
  • Eryando T; Faculty of Public Health, Universitas Indonesia, Depok, Indonesia.
  • Besral; Faculty of Public Health, Universitas Indonesia, Depok, Indonesia.
  • Trihono; Faculty of Public Health, Universitas Indonesia, Depok, Indonesia.
  • Siregar KN; Ministry of Health, Jakarta, Indonesia.
  • Vidiawati D; Faculty of Public Health, Universitas Indonesia, Depok, Indonesia.
PLoS One ; 17(9): e0272616, 2022.
Article en En | MEDLINE | ID: mdl-36070321
The COVID-19 pandemic, the growth of smartphones, and the internet have driven the use of technology for monitoring TB patients. Innovation in management of TB patients is needed to improve treatment outcomes. The study was conducted to obtain a predictive model of medication safety and solution model for at-risk patients, and to improve medication safety through mobile applications. The research was conducted in 4 stages, namely qualitative, quantitative (cross-sectional), qualitative, and quantitative (quasi-experimental, post-test group control design). Data were taken at the Public Health Center in Jakarta, Indonesia. Samples were taken by cluster random sampling. For quantitative research, 2nd phase (n = 114) and 4th phase (n = 96) were analyzed using logistic regression. This study analyzed predictors of medication safety to assist in monitoring patients undergoing treatment. At-risk patients were educated using an algorithm programmed in the application.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tuberculosis / Aplicaciones Móviles / Tratamiento Farmacológico de COVID-19 Tipo de estudio: Observational_studies / Prevalence_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Indonesia Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tuberculosis / Aplicaciones Móviles / Tratamiento Farmacológico de COVID-19 Tipo de estudio: Observational_studies / Prevalence_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Indonesia Pais de publicación: Estados Unidos