Thursday, July 22, 2004: 4:45 PM-6:15 PM | |||
Evidence-Based Staffing | |||
| Learning Objective #1: Articulate how patient, nurse, and system characteristics and behaviors influence worked hours, productivity of nursing staff; and outcomes for patients, nurses, and the system | |||
| Learning Objective #2: Articulate how multilevel modeling was used to understand the relationships among variables studied and the odds associated with the influence of each independent variable on the outcomes of interest | |||
| Nurse staffing is closely linked to patient outcomes and system effectiveness. A greater understanding of the drivers and outcomes of hospital nurse staffing is essential to meet increasing demands for both cost and quality accountability in health care. Recent Canadian reports highlight the urgent need to identify methods for valid measurement of nursing workload and productivity/utilization (P/U) and to understand their joint impact on patient, nurse and system outcomes, especially in the context of predicted nursing workforce shortages. Prior studies have provided insight on some of the factors that contribute to the need for nurses and the impact of different staffing approaches on patient, provider and system outcomes. Recent evidence suggests that increments of one patient per nurse in acute care hospitals are associated with increases in 30-day mortality (7%), failure-to-rescue (7%), nurse burnout (23%) and job dissatisfaction (15%). The principal objective of this study was to examine the relationships among a number of the variables that influence patient, nurse, and system outcomes in order to provide quality adjusted ranges of nursing P/U and staffing standards for patients receiving cardiac and cardiovascular nursing care. This evidence will inform the development of mechanisms and policies that measure the need for nursing service in light of appropriate staffing and productivity standards. In relation to specific cardiac and cardiology diagnoses, the research questions examined: 1. To what extent do patient, nurse, and system characteristics and behaviors, and environmental complexity measures explain variation in nursing hours of care and patient, nurse, and system outcomes, such as length of stay? 2. At what nurse-patient ratio and with what proportion of Registered Nurse (RN) worked hours are P/U and patient and nurse outcomes improved after controlling for the influence of patient, nurse, organizational and environmental factors? | |||
| Organizer: | Linda O'Brien-Pallas, RN, PhD | ||
| Presenters: | Raquel M. Meyer, RN Sping Wang, PhD Xiaoqiang Li, PhD Linda McGillis Hall, RN, PhD Donna Thomson, BScN, MScN Linda O'Brien-Pallas, RN, PhD | ||
| Are We Staffing Right? A Conceptual Model To Guide Decision-Making Raquel M. Meyer, RN, Linda O'Brien-Pallas, RN, PhD, Donna Thomson, BScN, MScN, Linda McGillis Hall, RN, PhD, Sping Wang, PhD, Xiaoqiang Li, PhD | |||
| The Effect of Work Environment and Nurse Characteristics on Nurse Outcomes Sping Wang, PhD, Linda O'Brien-Pallas, RN, PhD, Donna Thomson, BScN, MScN, Linda McGillis Hall, RN, PhD, Xiaoqiang Li, PhD, Raquel M Meyer, RN, PhD, Student | |||
| The Effect of Work Environment and Nurse Characteristics on Patient Outcomes Linda O'Brien-Pallas, RN, PhD, Donna Thomson, BScN, MScN, Linda McGillis Hall, RN, PhD, Sping Wang, PhD, Xiaoqiang Li, PhD, Raquel M Meyer, RN, PhD, Student | |||
| The Right Nurse and the Right Environment Improve System Outcomes Donna Thomson, BScN, MScN, Linda O'Brien-Pallas, RN, PhD, Linda McGillis Hall, RN, PhD, Sping Wang, PhD, Xiaoqiang Li, PhD, Raquel M Meyer, RN, PhD, Student | |||
| Using Multilevel Modeling to Study the PCDM Xiaoqiang Li, PhD, Linda O'Brien-Pallas, RN, PhD, Donna Thomson, BScN, MScN, Linda McGillis Hall, RN, PhD, Sping Wang, PhD, Raquel M Meyer, RN, PhD, Student | |||
15th International Nursing Research Congress
Sigma Theta Tau International
July 22-24, 2004