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Multicenter Study
Impact of skill mix variations on patient outcomes following implementation of nursing hours per patient day staffing: a retrospective study.
- Di Twigg, Christine Duffield, Alexandra Bremner, Pat Rapley, and Judith Finn.
- School of Nursing and Midwifery, Edith Cowan University, Joondalup, Western Australia, Australia. d.twigg@ecu.edu.au
- J Adv Nurs. 2012 Dec 1; 68 (12): 2710-8.
AimsThis article is a report of a study of the association between skill mix and 14 nursing-sensitive outcomes following implementation of the nursing hours per patient day staffing method in Western Australian public hospitals in 2002, which determined nursing hours by ward category but not skill mix.BackgroundFindings from previous studies indicate that higher nurse staffing levels and a richer skill mix are associated with improved patient outcomes. Measuring skill mix at a hospital level for specific staffing methods and associated nursing-sensitive patient outcomes are important in providing staffing for optimal patient care.DesignThe research design for the larger study was retrospectively analysing patient and staffing administrative data from three adult tertiary hospitals in metropolitan Perth over 4 years.MethodsA subset of data was used to determine the impact of skill mix on nursing-sensitive outcomes following implementation of the staffing method. All patient records (N=103,330) and nurse staffing records (N=73,770) from nursing hours per patient day wards from October 2002-June 2004 following implementation were included.ResultsIncreases in Registered Nurse hours were associated with important decreases in eight nursing-sensitive outcomes at hospital level and increases in three nursing-sensitive outcomes. The lowest skill mix saw the greatest reduction in nursing-sensitive outcome rates.ConclusionsThe skill mix of nurses providing care could impact patient outcomes and is an important consideration in strategies to improve nurse staffing. Levels of hospital nurse staffing and skill mix are important organizational characteristics when predicting patient outcomes.© 2012 Blackwell Publishing Ltd.
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