Journal article
Nursing Student Errors and Near Misses: Three Years of Data
The Journal of nursing education, v 62(1)
01 Jan 2023
PMID: 36652577
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Background: Understanding the magnitude of errors and near misses in all health care situations is crucial to preventing them from occurring in the future. However, little research is available on the type or extent of nurs-ing student errors in the United States. Method: Nursing student error and near miss data were submitted by more than 200 participating prelicensure nursing programs via a secured online repository. Results: Medication errors represented more than half (58.8%, n = 613) of the total error and near-miss data (n = 1,042) submitted. Errors and near misses were attributed to students not adhering to three major patient safety procedures: checking the pa-tient's identification, checking the patient's allergy status, and following the rights of medication administration. Conclusion: Results indicate collecting data on nursing students'errors and near misses can help nursing programs identify system issues, promote transparency, and make quality improvements. [J Nurs Educ. 2023;62(1):12-19.]
Metrics
Details
- Title
- Nursing Student Errors and Near Misses: Three Years of Data
- Creators
- Josephine Hernandez Silvestre - Natl Council State Boards Nursing, Chicago, IL USANancy Spector - Natl Council State Boards Nursing, Chicago, IL USA
- Publication Details
- The Journal of nursing education, v 62(1)
- Publisher
- Slack Inc
- Number of pages
- 8
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Pediatrics
- Web of Science ID
- WOS:000924934700003
- Scopus ID
- 2-s2.0-85146485626
- Other Identifier
- 991020785757004721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Nursing