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Background: The use of remote visual monitoring (RVM) technology as a “telesitter” in hospitals can reduce falls and increase the efficiency of patient observation. Purpose: This study aimed to examine RVM effectiveness as a strategy to decrease patient falls and investigate nurses’ acceptance and perceived usefulness of RVM technology. Methods: Remote visual monitoring was implemented within a health system in the Southeastern United States. Falls data 6 months prior to and postimplementation were analyzed, and 106 nurses completed a survey evaluating their acceptance of the RVM technology. Results: There was a significant 39.15% reduction in falls with injury (P = .006), and 70.6% of the RVM redirections were successful. Nurses’ acceptance and perceived usefulness of RVM were moderate. Conclusion: Implementing RVM has the potential to enhance patient safety by reducing falls with injuries and is considered acceptable and useful by nurses. [ABSTRACT FROM AUTHOR]

Studies show engineering graduates lack critical skills, including the ability to communicate effectively and appropriately in diverse teams. As institutions seek effective and affordable solutions to meet ABET accreditation standards for non-technical skills, we report on an intervention program designed to advance learners' intercultural communication (IComm) skills. We adapted the UNESCO Story Circles methodology (2020) to undergraduate engineering contexts: discipline-specific prompts guide oral exchanges among students, tasking learners to practice IComm principles in teams. The 2021 mixedmethod study tracked 31 students' attitudes toward teamwork and performance in project-based learning. Data sources included three survey instruments, individual project grades, and end-of-semester course evaluations. Results show strong student support for the intervention program across demographics and instructional modalities; improved learner attitudes toward teamwork in post-intervention surveys; improved 2021 end-of-semester course evaluations compared to 2019; and, higher individual grades on the team project. Findings support the use of our intervention program in project-based engineering courses and highlight the importance of guiding engineering students in the intentional practice of IComm principles. [ABSTRACT FROM AUTHOR]

Background Traditional strategies for surveillance of surgical site infections (SSI) have multiple limitations, including delayed and incomplete outbreak detection. Statistical process control (SPC) methods address these deficiencies by combining longitudinal analysis with graphical presentation of data. Methods We performed a pilot study within a large network of community hospitals to evaluate performance of SPC methods for detecting SSI outbreaks. We applied conventional Shewhart and exponentially weighted moving average (EWMA) SPC charts to 10 previously investigated SSI outbreaks that occurred from 2003 to 2013. We compared the results of SPC surveillance to the results of traditional SSI surveillance methods. Then, we analysed the performance of modified SPC charts constructed with different outbreak detection rules, EWMA smoothing factors and baseline SSI rate calculations. Results Conventional Shewhart and EWMA SPC charts both detected 8 of the 10 SSI outbreaks analysed, in each case prior to the date of traditional detection. Among detected outbreaks, conventional Shewhart chart detection occurred a median of 12 months prior to outbreak onset and 22 months prior to traditional detection. Conventional EWMA chart detection occurred a median of 7months prior to outbreak onset and 14 months prior to traditional detection. Modified Shewhart and EWMA charts additionally detected several outbreaks earlier than conventional SPC charts. Shewhart and SPC charts had low false-positive rates when used to analyse separate control hospital SSI data. Conclusions Our findings illustrate the potential usefulness and feasibility of real-time SPC surveillance of SSI to rapidly identify outbreaks and improve patient safety. Further study is needed to optimise SPC chart selection and calculation, statistical outbreak detection rules and the process for reacting to signals of potential outbreaks. [ABSTRACT FROM AUTHOR]

Introduction: Falls with injury are the most prevalent hospital adverse event. The objective of this project was to refine fall risk and prevention icons for a patient-centric bedside toolkit to promote patient and nurse engagement in accurately assessing fall risks and developing a tailored fall prevention plan., Methods: Eighty-eight patients and 60 nurses from 2 academic medical centers participated in 4 iterations of testing to refine 6 fall risk and 10 fall prevention icons. During individual interviews, participants rated their satisfaction with the degree to which that icon represented the concept on a 4-point Likert scale, enabling computation of a Content Validity Index (CVI), and provided comments and suggestions for improvement. After reviewing CVI scores and feedback, the research team consulted with the illustrator to revise the icons., Results: Content Validity Index scores improved after icon modifications. Icons that depicted multiple concepts required further iterations to be acceptable., Discussion: Using icons to depict an accurate and easy-to-interpret fall risk assessment and intervention plan for all care team members including patients and family to follow should lead to improved adherence with that plan and decreased falls., Conclusions: All 16 icons were refined and used to form the basis for a bedside fall prevention toolkit., Competing Interests: The authors disclose no conflict of interest., (Copyright © 2017 Wolters Kluwer Health, Inc. All rights reserved.)