Background: Nurse staffing levels are an important working condition issue for nurses and believed to be a determinant of the quality of nursing care and patient outcomes.
Objectives: To examine the effects of nurse staffing on adverse events, morbidity, mortality, and medical costs.
Methods: Using two existing databases, the study sample included 232 acute care California hospitals and 124,204 patients in 20 surgical diagnosis-related groups. The adverse events included patient fall/injury, pressure ulcer, adverse drug event, pneumonia, urinary tract infection, wound infection, and sepsis. Multilevel analysis was employed to examine, simultaneously, the effects of nurse staffing and patient and hospital characteristics on patient outcomes.
Results: Three statistically significant relationships were found between nurse staffing and adverse events. An increase of 1 hour worked by registered nurses (RN) per patient day was associated with an 8.9% decrease in the odds of pneumonia. Similarly, a 10% increase in RN Proportion was associated with a 9.5% decrease in the odds of pneumonia. Providing a greater number of nursing hours per patient day was associated with a higher probability of pressure ulcers. The occurrence of each adverse event was associated with a significantly prolonged length of stay and increased medical costs. Patients who had pneumonia, wound infection or sepsis had a greater probability of death during hospitalization.
Conclusion: Patients are experiencing adverse events during hospitalization. Care systems to reduce adverse events and their consequences are needed. Having appropriate nurse staffing is a significant consideration in some cases.
Sung-Hyun Cho, PhD, MPH, RN, is Chief Researcher, Korea Institute for Health and Social Affairs, Seoul.
Shaké Ketefian, EdD, RN, FAAN, is Professor, University of Michigan School of Nursing, Ann Arbor.
Violet H. Barkauskas, PhD, RN, FAAN, is Associate Professor, University of Michigan School of Nursing, Ann Arbor.
Dean G. Smith, PhD, is Professor, University of Michigan School of Public Health, Ann Arbor.
Accepted for publication September 16, 2002.
This project was supported by grant number R03 HS11397 from the Agency for Healthcare Research and Quality.
The authors thank Dr. Edward Rothman, Professor of Statistics and Director, and Ms. Kathy Welch, Statistical Consultant, at the Center for Statistical Consultation and Research, University of Michigan, for their assistance in the statistical analysis.
Corresponding author: Sung-Hyun Cho, Korea Institute for Health and Social Affairs, Department of Health Policy, San 42-14 Bulgwang-dong Eunpyeong-gu Seoul, Korea 122-705 (e-mail: email@example.com).