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

General Articles on Innovation and Technology in Public Health (82) Clinical Informatics in Low-Resource Settings and the Developing World (112) Clinical Informatics (1155) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (636) Electronic Health Records (1175) mHealth in the Developing World/LMICs, Underserved Communities, and for Global Health (631) Big Data for Health Promotion and Health Equity (31) Public Health Data Analytics (84)

Published on in Vol 10 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49127, first published .
Factors Influencing Data Quality in Electronic Health Record Systems in 50 Health Facilities in Rwanda and the Role of Clinical Alerts: Cross-Sectional Observational Study

Factors Influencing Data Quality in Electronic Health Record Systems in 50 Health Facilities in Rwanda and the Role of Clinical Alerts: Cross-Sectional Observational Study

Factors Influencing Data Quality in Electronic Health Record Systems in 50 Health Facilities in Rwanda and the Role of Clinical Alerts: Cross-Sectional Observational Study

Authors of this article:

Hamish S F Fraser1 Author Orcid Image ;   Michael Mugisha2 Author Orcid Image ;   Ian Bacher1 Author Orcid Image ;   Joseph Lune Ngenzi2 Author Orcid Image ;   Christopher Seebregts3, 4 Author Orcid Image ;   Aline Umubyeyi2 Author Orcid Image ;   Jeanine Condo5, 6 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Ghalavand H, Shirshahi S, Rahimi A, Zarrinabadi Z, Amani F. Common data quality elements for health information systems: a systematic review. BMC Medical Informatics and Decision Making 2024;24(1) View
  2. Petit P, Vuillerme N. Leveraging Administrative Health Databases to Address Health Challenges in Farming Populations: Scoping Review and Bibliometric Analysis (1975-2024). JMIR Public Health and Surveillance 2025;11:e62939 View
  3. Sylvain M, Nyabyenda E, Uwase M, Komezusenge I, Ndikumana F, Ngaruye I. Prediction of adverse pregnancy outcomes using machine learning techniques: evidence from analysis of electronic medical records data in Rwanda. BMC Medical Informatics and Decision Making 2025;25(1) View