Analysis of Intensive Care Unit Nursing Clinical Judgment and Selection of Nursing Diagnosis for Cerebral Hemorrhage.


Journal

Computers, informatics, nursing : CIN
ISSN: 1538-9774
Titre abrégé: Comput Inform Nurs
Pays: United States
ID NLM: 101141667

Informations de publication

Date de publication:
01 10 2023
Historique:
pubmed: 11 7 2023
medline: 11 7 2023
entrez: 11 7 2023
Statut: epublish

Résumé

Few nursing informatics studies focus on selecting nursing diagnoses for critical patients. The absence of data about nursing clinical judgment in the care of patients with cerebral hemorrhage greatly hinders research progress in evidence-based care. A stratified, retrospective study analyzed 115 electronic "intelligent" nursing information system nurse assessments and nursing diagnoses. Data were documented from April 2019 to November 2020 for critically ill patients admitted with cerebral hemorrhage in a 10-bed medical ICU at a 1500-bed tertiary facility, Henan Honliv Hospital, in Henan Province, China. In the selection of nursing diagnoses among nurses of stratified competencies (novice to expert), novice and experienced nurses were found to have significant variances in selecting nursing diagnoses for critically ill patients with cerebral hemorrhage. Novice nurses more frequently selected the Activity Intolerance Risk diagnosis as an initial diagnosis ( P = .025). Experienced nurses selected the Fluid Volume Excess Risk diagnosis more frequently ( P = .003). Consequently, nursing information systems are important in evaluating professional practice. The access to structured, standardized nursing data for the complete nursing process enables nurse managers to comprehensively analyze the nursing care given to patients, the distribution of patient nursing diagnoses, and the status of patient care risks.

Identifiants

pubmed: 37432107
doi: 10.1097/CIN.0000000000001023
pii: 00024665-202310000-00009
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

789-795

Informations de copyright

Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.

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Auteurs

Lei Yang (L)

Author Affiliations: Henan Honliv Hospital, Changyuan, Henan Province (Mr Yang, Ms Xu, Mr Ji, Ms Wang, Ms Cao, and Mr, Dr Chong); and ZhongWei Institute of Nursing Information, Beijing (Mr Wu), People's Republic of China.

Classifications MeSH