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Evaluation of nurse staffing levels and outcomes under the government – recommended staffing levels in Korea
Author(s) -
Yu Soyoung,
Kim Tae Gon
Publication year - 2015
Publication title -
journal of nursing management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.925
H-Index - 76
eISSN - 1365-2834
pISSN - 0966-0429
DOI - 10.1111/jonm.12155
Subject(s) - overtime , staffing , nursing , government (linguistics) , medicine , nursing management , unit (ring theory) , business , psychology , linguistics , philosophy , mathematics education , political science , law
Aim This study aimed to evaluate registered nurse staffing levels and outcomes enforced by the current Korean nursing regulations. Background Registered nurse staffing levels are closely related to patient and nurse outcomes. Thus, the government's policy regarding nursing staffing has a practical impact, and better policies could lead to more appropriate nurse staffing. The actual evaluation of the government‐recommended staffing levels in Korea is paramount for the establishment of a realistic and effective system that promotes quality care and patient safety. Method The participating hospital operated under the government‐recommended staffing levels (Grade 2 of the Graded Fee of Nursing Management Inpatient System). For unit‐level evaluations, one surgical unit was chosen and its staffing level was changed by assigning one additional registered nurse for 6 months. Length of hospitalisation, incidents of death, overtime hours and nursing job performance were measured prior to and after the addition of the extra staff. Result After 6 months, the length of patient hospitalisation and registered nurse overtime hours reduced and nurse job performance scores in the unit analysed improved. Conclusions and implications for nursing management The results demonstrated that increasing the number of registered nurses beyond the current government‐recommended staffing level improves patient and nurse outcomes. This indicates the importance and value of empirically assessing the need for changes in the recommended nurse staffing levels to develop appropriate, realistic and effective policies.