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A nursing care classification system for assessing workload and determining optimal nurse staffing in a teaching hospital in C hina: A pre‐post intervention study
Author(s) -
Yu Dongmei,
Ma Yuqin,
Sun Qingwen,
Lu Gendi,
Xu Ping
Publication year - 2015
Publication title -
international journal of nursing practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.62
H-Index - 55
eISSN - 1440-172X
pISSN - 1322-7114
DOI - 10.1111/ijn.12295
Subject(s) - workload , staffing , medicine , nursing , nursing care , patient satisfaction , intervention (counseling) , emergency medicine , computer science , operating system
We aimed to evaluate the effectiveness of a nursing care classification system for re‐assessing nurse workload and determining staffing needs. Adequate bed–nurse ratios help manage hospital cost‐efficiency, quality of care and patient safety. A prospective pre‐post intervention study was conducted from J anuary 2010 to D ecember 2012 in 16 medical‐surgical units of a tertiary teaching hospital. Nursing tasks were classified into four grades of care reflecting actual workload. Units were re‐staffed accordingly and bed–nurse ratios compared with government‐authorized bed–nurse ratios. Patient satisfaction, hospital stays and mortality were evaluated pre‐ and poststaffing changes. Average bed–nurse ratio (1:0.41) exceeded the national standard (1:0.40) in 16 units, but was inadequate in five units. Re‐staffing increased average bed–nurse ratio from 1:0.41 to 1:0.48. Patients' satisfaction increased from 96.9% to 97.6%, and hospital stays decreased significantly. Nursing care classification effectively distributes nurse staffing to match patients' care levels, improving patient outcomes.