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

JMIR Theme Issue: COVID-19 Special Issue (2554) Clinical Informatics (1325) Clinical Information and Decision Making (1915) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (698) Machine Learning (2076) Artificial Intelligence (2129) Nursing Records (18) Infectious Diseases (non-STD/STI) (1726) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1542)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53343, first published .
Identification of Predictors for Clinical Deterioration in Patients With COVID-19 via Electronic Nursing Records: Retrospective Observational Study

Identification of Predictors for Clinical Deterioration in Patients With COVID-19 via Electronic Nursing Records: Retrospective Observational Study

Identification of Predictors for Clinical Deterioration in Patients With COVID-19 via Electronic Nursing Records: Retrospective Observational Study

Authors of this article:

Sumi Sung1 Author Orcid Image ;   Youlim Kim2 Author Orcid Image ;   Su Hwan Kim3 Author Orcid Image ;   Hyesil Jung4 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Park S, Sung S, Min Y. A Comparative Study of End-of-Life Care Before and During the COVID-19 Pandemic Using Electronic Nursing Records. CIN: Computers, Informatics, Nursing 2025;43(6) View
  2. Seeiso T, Mhlongo E. Factors promoting eRegister and data use for evidence-based midwifery practice in Lesotho: a qualitative study. BMJ Open 2025;15(11):e093878 View