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This paper is in the following e-collection/theme issue:

Research Letter (149) mHealth in a Clinical Setting (1224) Safety and Error Prevention in Health (338) Quality Improvement (384) Formative Evaluation of Digital Health Interventions (5404) Alarm Fatigue (34) Nursing in a Hospital Setting (246)

Published on in Vol 10 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/91321, first published .
Two nurses in hijab and masks use a computer displaying the SafiNurse patient safety application.

AI-Based Patient Safety Incident Reporting System for Nurses (SAFE-Nurse): Development and Validation Study

AI-Based Patient Safety Incident Reporting System for Nurses (SAFE-Nurse): Development and Validation Study

Authors of this article:

Nindya Febriyani Putri1 Author Orcid Image ;   Rini Rachmawaty1, 2 Author Orcid Image ;   Nuurhidayat Jafar3 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Nindya Febriyani Putri   1 , BSN, RN, MN ;   Rini Rachmawaty   1, 2 , BSN, RN, MN, PhD ;   Nuurhidayat Jafar   3 , BSN, RN, MN, PhD

1 Nursing Management & Healthcare Quality Research Group, Faculty of Nursing, Hasanuddin University, Makassar, Indonesia

2 Department of Nursing Management, Faculty of Nursing, Hasanuddin University, Makassar, Indonesia

3 Department of Community Nursing, Faculty of Nursing, Hasanuddin University, Makassar, Indonesia

Corresponding Author:

  • Rini Rachmawaty, BSN, RN, MN, PhD
  • Nursing Management & Healthcare Quality Research Group
  • Faculty of Nursing, Hasanuddin University
  • Jl. Perintis Kemerdekaan KM. 10
  • Makassar 90245
  • Indonesia
  • Phone: 62 81213916730
  • Email: rini.rachmawaty@unhas.ac.id