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Workload Intensity, The Nursing Practice Environment, and Adverse Events
Final rept. 1 Sep 2010-31 Aug 2014
ALABAMA UNIV IN BIRMINGHAM
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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.
APPROVED FOR PUBLIC RELEASE