An observational study on the rate of reporting of adverse event on healthcare staff in a mental health setting: An application of Poisson expectation maximisation analysis on nurse staffing data.
count regression
nurse staffing
retention
safety
workforce
Journal
Health informatics journal
ISSN: 1741-2811
Titre abrégé: Health Informatics J
Pays: England
ID NLM: 100883604
Informations de publication
Date de publication:
06 2020
06 2020
Historique:
pubmed:
5
10
2019
medline:
24
7
2021
entrez:
5
10
2019
Statut:
ppublish
Résumé
Evidence highlights the intrinsic link between nurse staffing and expertise, and outcomes for service users of healthcare, and that workforce retention is linked to the clinical and organisational experiences of employees. However, this understanding is less well established in mental health. This study comprises a retrospective observational study carried out on routinely collected data from a large mental healthcare provider. Two databases comprising nurse staffing levels and adverse events were modelled using latent variable methods to account for the presence of multiple underlying behaviours. The analysis reveals a strong dependence of the rate of adverse events on the location and perceived clinical demand of the wards, and a reduction in adverse events where registered nurses exceed 'clinically required levels'. In the first study of its kind, these findings present significant implications for nursing workforce policy and present an opportunity to not only improve safety but potentially impact nurse retention.
Identifiants
pubmed: 31581927
doi: 10.1177/1460458219874637
doi:
Types de publication
Journal Article
Observational Study
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM