Paper
Thursday, July 22, 2004
The Right Nurse and the Right Environment Improve System Outcomes
Donna Thomson, BScN, MScN1, Linda O'Brien-Pallas, RN, PhD2, Linda McGillis Hall, RN, PhD2, Sping Wang, PhD3, Xiaoqiang Li, PhD4, and Raquel M Meyer, RN, PhD, Student5. (1) St. Peter's Hospital, University of Toronto, Hamilton, ON, Canada, (2) Faculty of Nursing, University of Toronto, Toronto, ON, Canada, (3) Nursing Effectiveness, Utilization and Outcomes Research Unit, University of Toronto, Toronto, ON, Canada, (4) Nursing Effectiveness, Utilization & Outcomes Research Unit, University of Toronto, Toronto, ON, Canada, (5) NRU, University of Toronto, Toronto, ON, Canada
Objective: This paper describes how system inputs and throughputs influence P/U, delay/completion of nursing interventions, absenteeism, length of stay, quality of nursing and patient care, and cost per Resource Intensity Weight (RIW). Design: As above in Patient Outcomes Population, Sample, Setting: In total 8113 patient days of data and as above Concepts and variables measured: As described in Abstract 1 Methods: As described in Abstract 2 Results: One of the most interesting findings in this study is the level of nursing P/U at which cost and quality indicators begin to decline. This study suggests that better cost outcomes can be achieved when unit staffing allows utilization rates around 85% ± 5%. Lower costs per RIW were associated with increased use of step-down units, care by nurses with clinical expertise, and physically healthier nurses. Higher costs per RIW were more likely when surgical patients attended pre-operative and post-operative education. The ratings of quality of nursing care were influenced by nurses’ ratings of quality of patient care, job satisfaction, ratings of clinical expertise, frequency of shift change, and quality of nurse-physician relationships. The ratings of patient care quality were influenced by the proportion of RN worked hours, nurses with BScN or above, number of interventions delayed, ratings of clinical expertise, degree of autonomy, and ratings of quality of nursing care. P/U was influenced by the proportions of emotionally exhausted and mentally healthy nurses on the unit, nurse patient ratio, pure cardiology patient mix, more time needed to provide care, and autonomy. Conclusion: Nurses who are clinical experts, healthy, satisfied and BScN prepared and enough nurses to meet demand will lower cost and increase quality. Implication: Staffing with right number and type of nurses will create better system outcomes.
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