Utilizing a Human Factors Nursing Worksystem Improvement Framework to Increase Nurses' Time at the Bedside and Enhance Safety.

OBJECTIVE: The aim of this study is to increase nurses' time for direct patient care and improve safety via a novel human factors framework for nursing worksystem improvement. BACKGROUND: Time available for direct patient care influences outcomes, yet worksystem barriers prevent nurses adequate time at the bedside. METHODS: A novel human factors framework was developed for worksystem improvement in 3 units at 2 facilities. Objectives included improving nurse efficiency as measured by time-and-motion studies, reducing missing medications and subsequent trips to medication rooms and improving medication safety. RESULTS: Worksystem improvement resulted in time savings of 16% to 32% per nurse per 12-hour shift. Requests for missing medications dropped from 3.2 to 1.3 per day. Nurse medication room trips were reduced by 30% and nurse-reported medication errors fell from a range of 1.2 to 0.8 and 6.3 to 4.0 per month. CONCLUSIONS: An innovative human factors framework for nursing worksystem improvement provided practical and high priority targets for interventions that significantly improved the nursing worksystem.

Meta-analysis of fall-risk tools in hospitalized adults.

OBJECTIVE: The aim of the study was to identify which fall-risk tool is most accurate for assessing adults in the hospital setting. BACKGROUND: Falls can have physical, emotional, social, and financial consequences. Risk assessment affords the first opportunity in prevention. METHODS: To standardize the use of a fall-risk tool across the Baylor Health Care System, nurse executives undertook a meta-analysis of published research on fall-risk assessment tools used with adult inpatients. RESULTS: Both random-effects and fixed-effects models showed that Morse Fall Scale had significantly higher sensitivity than St Thomas's Risk Assessment Tool (STRATIFY). Specificity of Morse Fall Scale was significantly lower than that of STRATIFY with the fixed-effects model, but the random-effects model showed the opposite. Morse Fall Scale had a significantly higher Youden index than STRATIFY with the fixed-effects model (P = .001), but the result from random-effects model indicated no significant difference (P = .117). The sensitivity, specificity, and Youden index fell within the 95% confidence intervals. CONCLUSIONS: Meta-analysis is a useful methodology for evaluating current evidence when variation exists in the literature.