Workload Intensity, The Nursing Practice Environment, and Adverse Events

Abstract

Abstract : Purpose: To explore the influence of workload intensity (acuity and admissions, discharges, and transfers; ADT) and the nursing practice environment on the relationship between nurse staffing and patient and nurse outcomes. Design: Secondary analysis of the Military Nursing Outcomes Database. Methods: Data included staffing, workload, and outcomes at the shift level, annual nurse-reported practice environment and job satisfaction data, and annual unit-level pressure ulcer prevalence data. Sample: The dataset contained 111,500 shifts, 1,586 nurses and 1,643 patients from 57 units of 13 hospitals. Analysis: Data mining, generalized estimating equations, Cox proportional hazards modeling, and Bayesian hierarchical (nested) linear models were used. Findings: Workload intensity had an effect on the relationships between staffing and adverse events; the magnitude and direction differed by event type and staffing measure. Hospital acquired pressure ulcers (HAPUs) were significantly associated with licensed practical nurse (LPN) care hours three days prior to HAPU discovery; this relationship was partially mediated by ADT. Only in the top tercile practice environments was the staffing and HAPU relationship demonstrated. When controlling for acuity and ADT, total nursing care hours per patient per shift remained associated with shift level adverse events in medical-surgical and critical care (CC) units. ADT, but not acuity, was significantly associated with all adverse events, and neither mediated staffing. Needlesticks were not associated with staffing, ADT nor acuity. Nurse job satisfaction was strongly, but inversely, associated with total nursing care hours per patient shift (TNCHPPS) and had a strong, positive relationship with the practice environment. There was no relationship between job satisfaction and ADT or acuity in multivariate analysis. Implications for Military Nursing: Tracking workload is essential to understanding how staffing affects outcomes.