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

mHealth in a Clinical Setting (615) Electronic Health Records (1053)

Published on in Vol 7, No 1 (2019): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12041, first published .
Variability in Doctors’ Usage Paths of Mobile Electronic Health Records Across Specialties: Comprehensive Analysis of Log Data

Variability in Doctors’ Usage Paths of Mobile Electronic Health Records Across Specialties: Comprehensive Analysis of Log Data

Variability in Doctors’ Usage Paths of Mobile Electronic Health Records Across Specialties: Comprehensive Analysis of Log Data

Authors of this article:

Ji Yeong Soh1 Author Orcid Image ;   Sang-Hyuk Jung1 Author Orcid Image ;   Won Chul Cha1, 2, 3 Author Orcid Image ;   Mira Kang1, 3, 4 Author Orcid Image ;   Dong Kyung Chang1, 3, 5 Author Orcid Image ;   Jaegon Jung6 Author Orcid Image ;   JeanHyoung Lee3 Author Orcid Image ;   Jong Soo Choi1, 3 Author Orcid Image ;   Kyunga Kim1, 7 Author Orcid Image
Article Authors Cited by (8) Tweetations (4) Metrics

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  6. Van Schalkwyk A, Grobbelaar S, Vermeulen E, Herselman M. A Scoping Review of the Use of Log Data for Evaluating Mobile Apps: Exploring Implications for mHealth Apps. IEEE Access 2022;10:124805 View
  7. Tajika R, Inoue Y, Nakashima K, Yoshimi T, Arimoto N, Fukushige H, Taniura Y, Iwasaki T, Ishii A, Park C. Ward‐Specific Probabilistic Patterns in Temporal Dynamics of Nursing Demand in Japanese Large University Hospital: Implication for Forecasting and Resource Allocation. Journal of Nursing Management 2024;2024(1) View
  8. Tao Y, Zhu R, Wu D. Harnessing the Power of Complementarity Between Smart Tracking Technology and Associated Health Information Technologies: Longitudinal Study. JMIR Formative Research 2024;8:e51198 View