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.

Development of a tool to measure user experience following electronic health record implementation.

OBJECTIVE: The aim of this study was to develop a survey tool to assess electronic health record (EHR) implementation to guide improvement initiatives. BACKGROUND: Survey tools are needed for ongoing improvement and have not been developed for aspects of EHR implementation. METHODS: The Baylor EHR User Experience (UX) survey was developed to capture 5 concept domains: training and competency, usability, infrastructure, usefulness, and end-user support. Validation efforts included content validity assessment, a pilot study, and analysis of 606 nurse respondents. The revised tool was sent to randomly sampled EHR nurse-users in 11 acute care facilities. RESULTS: A total of 1,301 nurses responded (37%). Internal consistency of the survey tool was excellent (Cronbach's α = .892). Survey responses including 1,819 open comments were used to identify and prioritize improvement efforts in areas such as education, support, optimization of EHR functions, and vendor change requests. CONCLUSION: The Baylor EHR UX survey was a valid tool that can be useful for prioritizing improvement efforts in relation to EHR implementation.