AI Article Synopsis

  • The study analyzed the impact of nurse staffing on the length of hospital stays for patients in acute care units, focusing on potential non-linear relationships.
  • The research used data from over 35,000 patient episodes and 381 nurses, collected in 2008 from a Finnish university hospital, and applied Bayesian modeling for analysis.
  • Findings indicated that the ideal skill mix of nurses (65-80% Registered Nurses) is associated with shorter patient stays, highlighting the importance of flexible staffing over fixed models to improve care outcomes.

Article Abstract

Aims: This study sought to analyse relationships between nurse staffing and patients' length of stay in acute care units and to determine whether non-linear relationships exist between variables.

Background: Healthcare systems are complex and it could be assumed that they comprise non-linear associations. However, current planning and evaluation of nurse staffing are based primary on linear reasoning.

Design: This quantitative study adopted a retrospective longitudinal design.

Method: Retrospective register data, consisting of information relating to 35,306 patient episodes and administrative information concerning 381 nurses, were used. Data were collected in 2009 from 20 somatic inpatient units at a university hospital in Finland as a monthly time series of 2008 data and analysed using Bayesian dependency modelling.

Results: Patients' acuity was the most important agent that connected all eleven variables in the dependency network of nurse staffing and short length of stay. Non-linear associations were found between short length of stay and the proportion of Registered Nurses. Skill mix consisting of an average proportion of Registered Nurses (65-80%) was conducive to a short length of stay and predicted a 66% likelihood of short length of stay. Higher and lower percentages of Registered Nurses predicted lower likelihood of short length of stay.

Conclusion: Flexible nurse staffing is preferable to fixed staffing to provide patients with shorter length of stay in acute care units. In the present research, the Bayesian method revealed non-linear relationships between nurse staffing and patient and care outcomes.

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Source
http://dx.doi.org/10.1111/jan.12550DOI Listing

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