Staffing, skill mix and the model of care

Centre for Health Services Management, Faculty of Nursing, Midwifery and Health, University of Technology, Sydney, PO Box 123, Broadway, NSW 2007, Australia.
Journal of Clinical Nursing (Impact Factor: 1.26). 08/2010; 19(15-16):2242-51. DOI: 10.1111/j.1365-2702.2010.03225.x
Source: PubMed


The study aimed to explore whether nurse staffing, experience and skill mix influenced the model of nursing care in medical-surgical wards.
Methods of allocating nurses to patients are typically divided into four types: primary nursing, patient allocation, task assignment and team nursing. Research findings are varied in regard to the relationship between these models of care and outcomes such as satisfaction and quality. Skill mix has been associated with various models, with implications for collegial support, teamwork and patient outcomes.
Secondary analysis of data collected on 80 randomly selected medical-surgical wards in 19 public hospitals in New South Wales, Australia during 2004-2005.
Nurses (n = 2278, 80.9% response rate) were surveyed using The Nursing Care Delivery System and the Nursing Work Index-Revised. Staffing and skill mix was obtained from the ward roster and other data from the patient record. Models of care were examined in relation to these practice environment and organisational variables.
The models of nursing care most frequently reported by nurses in medical-surgical wards in this study were patient allocation (91%) and team nursing (80%). Primary nursing and task based models were unlikely to be practised. Skill mix, nurse experience, nursing workload and factors in the ward environment significantly influenced the model of care in use. Wards with a higher ratio of degree qualified, experienced registered nurses, working on their 'usual' ward were more likely to practice patient allocation while wards with greater variability in staffing levels and skill mix were more likely to practice team nursing.
Models of care are not prescriptive but are varied according to ward circumstances and staffing levels based on complex clinical decision making skills.
Variability in the models of care reported by ward nurses indicates that nurses adapt the model of nursing care on a daily or shift basis, according to patients' needs, skill mix and individual ward environments.

Download full-text


Available from: Michael Anthony Roche, May 12, 2014
  • Source
    • "Moreover, a consistently high workload of RNs increases the risks of nosocomial complications, wound and central-line infections, patient falls, pressure ulcers, medication errors and urinary tract infections (Weissman et al. 2007, Garrett 2008, Dall et al. 2009). However, Duffield et al. (2010) criticised such research on the basis that adverse outcomes of particular relevance to nurses, such as falls and medication errors, cannot be reliably captured in most large datasets drawn from administrative information. Hence, there is a need to use versatile data sources and collection methods in further studies. "
    [Show abstract] [Hide abstract]
    ABSTRACT: To investigate the relationships between nursing activities, nurse staffing and adverse patient outcomes in hospital settings as perceived by registered nurses in Finland and the Netherlands and to compare the results obtained in the two countries. Previous research indicates that a higher proportion of registered nurses in the staff mix results in better patient outcomes. Knowledge of the relationship between nurse staffing and adverse patient outcomes is crucial to optimise the management of professional nursing resources and patient care. A cross-sectional, descriptive questionnaire survey. Registered nurses employed in hospitals in Finland (n = 535) and the Netherlands (n = 334), with overall response rates of 44·9% and 33·4%, respectively, participated. The patient-to-nurse ratio was on average 8·74:1 and did not vary significantly between the countries. However, there were fewer registered nurses and significantly more licensed practical nurses among the Dutch hospital staff than the Finnish staff. In addition, Finnish nurses performed non-nursing and administrative activities more frequently than the Dutch nurses and reported more dissatisfaction with the availability of support services. Frequencies of patient falls were related to the patient-to-nurse ratio in both countries. Finnish participants reported the occurrence of adverse patient outcomes more frequently. Significant associations were found between nurse staffing and adverse patient outcomes in hospital settings. Compared with the Netherlands, in Finland, nurses appear to have higher workloads, there are higher patient-to-nurse ratios, and these adverse staffing conditions are associated with higher rates of adverse patient outcomes. The findings provide valuable insights into the potential effects of major changes or reductions in nursing staff on the occurrence of adverse patient outcomes in hospital settings.
    Journal of Clinical Nursing 12/2011; 21(11-12):1584-93. DOI:10.1111/j.1365-2702.2011.03956.x · 1.26 Impact Factor
  • Source
    Wells · Ellis ·

  • [Show abstract] [Hide abstract]
    ABSTRACT: Coding, costing, and accounting for nursing care requirements in Australian public and private hospitals lacks systematic research. Nurse costing for two nurse staffing allocation methods--nurse patient ratios and a computerized nurse dependency management system--were compared. Retrospective nursing workload management data were obtained from hospital information systems in 21 acute care public and private hospitals in Australia and New Zealand. Descriptive statistics, cost analysis, and cost modeling were conducted for 103,269 shifts of nursing care. The comparison of costs for nursing staff by nurse-patient ratios and by a computerized nurse dependency management system demonstrated differences. The provision of nursing care using the computerized nurse dependency management system was, overall, lower in cost than for nurse-patient ratios.
    Nursing economic$ 11/2011; 30(6):347-55. · 0.80 Impact Factor
Show more