Search

Objective: To develop a nurse staffing prediction model and evaluate deviation from predicted nurse staffing as a contributor to patient outcomes., Data Sources: Secondary data collection conducted 2017-2018, using the California Office of Statewide Health Planning and Development and the California Perinatal Quality Care Collaborative databases. We included 276 054 infants born 2008-2016 and cared for in 99 California neonatal intensive care units (NICUs)., Study Design: Repeated-measures observational study. We developed a nurse staffing prediction model using machine learning and hierarchical linear regression and then quantified deviation from predicted nurse staffing in relation to health care-associated infections, length of stay, and mortality using hierarchical logistic and linear regression., Data Collection Methods: We linked NICU-level nurse staffing and organizational data to patient-level risk factors and outcomes using unique identifiers for NICUs and patients., Principal Findings: An 11-factor prediction model explained 35 percent of the nurse staffing variation among NICUs. Higher-than-predicted nurse staffing was associated with decreased risk-adjusted odds of health care-associated infection (OR: 0.79, 95% CI: 0.63-0.98), but not with length of stay or mortality., Conclusions: Organizational and patient factors explain much of the variation in nurse staffing. Higher-than-predicted nurse staffing was associated with fewer infections. Prospective studies are needed to determine causality and to quantify the impact of staffing reforms on health outcomes., (© Health Research and Educational Trust.)

Objectives: To describe the variation across neonatal intensive care units (NICUs) in missed nursing care in disproportionately black and non-black-serving hospitals. To analyze the nursing factors associated with missing nursing care., Data Sources/study Setting: Survey of random samples of licensed nurses in four large U.S. states., Study Design: This was a retrospective, secondary analysis of 1,037 staff nurses in 134 NICUs classified into three groups based on their percent of infants of black race. Measures included the average patient load, individual nurses' patient loads, professional nursing characteristics, nurse work environment, and nursing care missed on the last shift., Data Collection: Survey data from a Multi-State Nursing Care and Patient Safety Study were analyzed (39 percent response rate)., Principal Findings: The patient-to-nurse ratio was significantly higher in high-black hospitals. Nurses in high-black NICUs missed nearly 50 percent more nursing care than in low-black NICUs. Lower nurse staffing (an additional patient per nurse) significantly increased the odds of missed care, while better practice environments decreased the odds., Conclusions: Nurses in high-black NICUs face inadequate staffing. They are more likely to miss required nursing care. Improving staffing and workloads may improve the quality of care for the infants born in high-black hospitals., (© Health Research and Educational Trust.)

Objective: To determine if hospital-level disparities in very low birth weight (VLBW) infant outcomes are explained by poorer hospital nursing characteristics., Data Sources: Nurse survey and VLBW infant registry data., Study Design: Retrospective study of 8,252 VLBW infants in 98 Vermont Oxford Network hospital neonatal intensive care units (NICUs) nationally. NICUs were classified into three groups based on their percent of infants of black race. Two nurse-sensitive perinatal quality standards were studied: nosocomial infection and breast milk., Data Collection: Primary nurse survey (N = 5,773, 77 percent response rate)., Principal Findings: VLBW infants born in high-black concentration hospitals had higher rates of infection and discharge without breast milk than VLBW infants born in low-black concentration hospitals. Nurse understaffing was higher and practice environments were worse in high-black as compared to low-black hospitals. NICU nursing features accounted for one-third to one-half of the hospital-level health disparities., Conclusions: Poorer nursing characteristics contribute to disparities in VLBW infant outcomes in two nurse-sensitive perinatal quality standards. Improvements in nursing have potential to improve the quality of care for seven out of ten black VLBW infants who are born in high-black hospitals in this country., (© Health Research and Educational Trust.)

Objective: To examine the effect of nursing practice environments on outcomes of hospitalized cancer patients undergoing surgery., Data Sources: Secondary analysis of cancer registry, inpatient claims, administrative and nurse survey data collected in Pennsylvania for 1998-1999., Study Design: Nurse staffing (patient to nurse ratio), educational preparation (proportion of nurses holding at least a bachelor's degree), and the practice environment (Practice Environment Scale of the Nursing Work Index) were calculated from a survey of nurses and aggregated to the hospital level. Logistic regression models predicted the odds of 30-day mortality, complications, and failure to rescue (death following a complication)., Principal Findings: Unadjusted death, complication, and failure to rescue rates were 3.4, 35.7, and 9.3 percent, respectively. Nurse staffing and educational preparation of registered nurses were significantly associated with patient outcomes. After adjusting for patient and hospital characteristics, patients in hospitals with poor nurse practice environments had significantly increased odds of death (odds ratio, 1.37; 95 percent confidence interval, 1.07-1.76) and of failure to rescue (odds ratio, 1.48; 95 percent confidence interval, 1.07-2.03). Receipt of care in National Cancer Institute-designated cancer centers significantly decreased the odds of death, which can be explained partly by better nurse practice environments., Conclusions: This study is one of the first to examine the predictive validity of the National Quality Forum's endorsed measure of the nurse practice environment. Improvements in the quality of nurse practice environments could reduce adverse outcomes for hospitalized surgical oncology patients.