A modified genetic algorithm (MGA) optimization procedure, alongside time series machine learning (ML) classifiers, is proposed to minimize handovers in a digital twin-based visible light communication (VLC) system. Frequent handovers have a direct impact on the overall performance of the VLC system due to the inherent connection downtime of a handover process. The handover scheme proposed in this article considers the receiver trajectory information to minimize handovers, maintaining the system performance below the forward error correction limit. Simulation results indicate that the proposed scheme outperforms a power-based handover scheme, achieving handover reductions of 42.47%. Therefore, the MGA combined to the ML models approach is an effective means of minimizing handovers, as well as improving overall VLC system performance.
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AIM: Implementation of a locally developed evidence based nursing shift handover blueprint with a bedside-safety-check to determine the effect size on quality of handover.METHODS: A mixed methods design with: (1) an interrupted time series analysis to determine the effect on handover quality in six domains; (2) descriptive statistics to analyze the intercepted discrepancies by the bedside-safety-check; (3) evaluation sessions to gather experiences with the new handover process.RESULTS: We observed a continued trend of improvement in handover quality and a significant improvement in two domains of handover: organization/efficiency and contents. The bedside-safety-check successfully identified discrepancies on drains, intravenous medications, bandages or general condition and was highly appreciated.CONCLUSION: Use of the nursing shift handover blueprint showed promising results on effectiveness as well as on feasibility and acceptability. However, to enable long term measurement on effectiveness, evaluation with large scale interrupted times series or statistical process control is needed.
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OBJECTIVE: Standardization of the handover process is deemed necessary to ensure continuity and safety of care. However, local context is considered of equal importance to improve the handover process. Our objective was to determine what recommendations on standardized shift handover nurses make, if we combine evidence from the literature with the local context of the nurses.DESIGN: A RAND-modified Delphi consensus process that combines evidence from systematic reviews with expert opinion of local nurses and an evaluation of the consensus process with a survey.SETTING: One academic medical center in the Netherlands.PARTICIPANTS: Twenty nurses from surgical, medical, neurological, psychiatric, cardiology, children's and gynecology departments.RESULTS: Four systematic reviews on nursing handover were included to compose provisional recommendations on how, what, where and the preconditions of shift handover. Nurses reached consensus on a final set of 18 recommendations for a nursing shift handover blueprint: how (1 recommendation), what (12 recommendations), where (3 recommendations) and the preconditions (2 recommendations), which were structured with the mnemonic NURSEPASS. The nurses assessed the method as an effective approach to develop a local blueprint.CONCLUSIONS: Evidence-based consensus is a feasible method to combine evidence from the literature with local context. We anticipate that implementation of the resulting tailored blueprint for nursing shift handover will be facilitated due to the method used. Through evaluation of its effectiveness, we intend to add to the body of evidence on development and implementation of effective nursing handover, which is an essential link for continuity and safety of care.
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