Paper
Saturday, July 16, 2005
Nurse Staffing and RN Satisfaction: Evidence From the National Database of Nursing Quality Indicators
Diane K. Boyle, RN, PhD1, Peggy A. Miller, RN, MS1, Byron Gajewski, PhD1, and Nancy Dunton, PhD2. (1) School of Nursing, University of Kansas, Kansas City, KS, USA, (2) NDNQI, Kansas City, KS, USA
Learning Objective #1: Discuss the relationship among RN satisfaction, perceived quality of care, and intent to stay at differing levels of nurse-to-patient staffing ratios |
Learning Objective #2: Discuss implications of findings for policy, administration, quality improvement initiatives, and further research |
Job satisfaction is crucial to retention of Registered Nurses (RNs) and therefore provision of quality patient care. Given the current and growing shortage of RNs, nursing executives, policy makers, and regulatory bodies are challenged to improve the work environment for nurses. Using year 2004 data on nurse staffing and RN satisfaction from the National Database of Nursing Quality Indicators (NDNQI), we examine RN job satisfaction, satisfaction with work environment, perceived quality of care, and intent to stay in the job at differing levels of nurse-to-patient staffing ratios. We hypothesize that higher nurse-to-patient staffing ratios are related to higher RN job satisfaction, higher satisfaction with work environment, higher intent to stay in the current position, and higher perceived quality of care. The sample includes 80,000 RNs in 5,201 patient care units (206 hospitals) across the United States. Data on aspects of RN satisfaction are collected through the annual NDNQI RN Satisfaction Survey, which elicits data on job satisfaction, the work environment, perceived quality of care, intent to stay in the job, certification, education, and experience. RNs eligible to complete the survey are those that spend 50% of time in direct patient care and have a minimum of 3 months employment on the current unit. Corresponding unit staffing data are retrieved from participating NDNQI hospital quarterly reports. We will analyze data using hierarchical structural equation modeling. The first level is the individual RN level and the second is the nursing unit level. While controlling for RN level covariates (e.g., experience, certification) and unit level covariates (e.g., unit type) we will estimate the between unit correlation of RN satisfaction and the nursing staff ratio nursing hours per patient day by type (RN, LPN, and other). Implications of findings for policy, administration, quality improvement initiatives, and further research will be discussed.