Association between symptoms of patients with heart failure and patient outcomes based on electronic nursing records

Seung Yeon Baik, Gi Wook Ryu, Hyangkyu Lee, Siwook Lee, Mona Choi

Research output: Contribution to journalArticlepeer-review

Abstract

We examined the association between symptoms (ie, dyspnea and pain) and patient outcomes (ie, length of stay, 30-day readmission, and death in hospital) among patients with heart failure using EMRs. This was a descriptive study that was conducted from July 1, 2014, to November 30, 2017. Participants were 754 hospitalized patients with heart failure (mean age, 70.62 ± 14.78 years; male-to-female ratio, 1:1.1). Data were analyzed using descriptive statistics, χ2 tests, and logistic regression analyses. Patients' average length of stay was 8.92 ± 13.12 days. Thirty-two patients (4.2%) were readmitted, and 100 patients (13.3%) died during hospitalization. Two-thirds (67.7%) experienced dyspnea, and 367 (48.7%) experienced pain. Symptoms and ICU admission were significantly related to patient outcomes. In the regression analyses, dyspnea, pain, and ICU admission were significantly related to higher-than-average lengths of stay. Dyspnea and ICU admission were related to death in hospital. Information regarding patients' symptoms, which was extracted from records, was a valuable resource in examining the relationship between symptoms and patient outcomes. The use of EMRs may be more advantageous than self-reported surveys when examining patients' symptom and utilizing big data.

Original languageEnglish
Pages (from-to)1027-1034
Number of pages8
JournalCIN - Computers Informatics Nursing
Volume39
Issue number12
DOIs
Publication statusPublished - 2021 Dec 25

Bibliographical note

Funding Information:
G.W.R. received a scholarship from Brain Korea 21 FOUR Project funded by the National Research Foundation (NRF) of Korea, Yonsei University College of Nursing. This research was supported by the Brain Korea 21 FOUR Project funded by the NRF of Korea and funding from Mo-Im Kim Nursing Research Institute, Yonsei University College of Nursing.

Publisher Copyright:
Copyright © 2021 The Authors. Published by Wolters Kluwer Health, Inc.

All Science Journal Classification (ASJC) codes

  • Health Informatics
  • Nursing (miscellaneous)

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