The Veteran's Administration (VA), recognizing the potential influence that nurturing interior environments may have on patient well-being, has been designing and constructing mental health settings intended to calm, restore, and revive. Unfortunately, limited research investigates the links between the interior environment and mental health outcomes that can be used for guiding the design for these facilities. This paper seeks to provide a framework for designing person-centered mental health interiors that would be supportive of human factors for a healthcare organization's clinical and operational staff as well as Veterans. The framework is intended to assist healthcare providers in achieving mental health aims through thoughtful, evidence-based, person-centered design. Based on a review of the literature and case study investigations of three VA acute inpatient mental health units in the United States, the framework is comprised of six domains: Involve, Protect, Engage, Comfort, Personalize, and Sustain. These domains, informed by existing credible research and best practices, were vetted through post-hoc analysis of qualitative data gathered from interviews, focus groups, and/or listening sessions conducted with the three sites. The resultant Framework for Designing Person-Centered Mental Health Interiors for Veterans, developed based on the data and methodologies used in conducting this study, is meant as a complementary resource for informing future research, planning, design, and operation of acute inpatient mental health spaces. The research team's aim was to develop an accessible set of evidence-based environmental planning considerations to aid in the prioritization and development of person-centered mental health environments.

This article explores techniques for estimating Hospital Acquired Infection prevention potential through strategic nursing care delivery design and applied fuzzy frameworks. To achieve this, it evaluates the use of Fuzzy Logic directed by King’s Theory of Nursing Goal Attainment for developing a HAI resilience process model. The purpose of this model is to estimate the performance of environment of care safety based on the ability of nurses to moderate risk and respond adaptively to certain types of hospital-onset infections through strategic workflow design. The aim of this proposed approach would be to help nurses and infection control specialists in healthcare settings better understand what accessible Systems Science-based frameworks may be instrumental for analyzing and forecasting infection control systems improvement. The benefit of using Fuzzy Frameworks in nursing workflow and environment of care planning is that it allows for the leveraging of crystalized intelligence nursing staff have about their patient demography and unit-based workflow. This process allows nurse work designers to introduce and test targeted process or physical improvement strategies that make sense for their unique circumstances while providing better insight into how these interventions may work holistically with all relevant environment of care operations. This approach is made more powerful when guided by trusted optimal nursing theoretical perspectives such as King’s Theory of Goal Attainment.

No abstract

There is growing evidence that contact surfaces within healthcare settings can serve as reservoirs for pathogen colonization and spread infectious bacteria to humans. This article aims to demonstrate the use of a Prevention through Design Environment Material Integrative Control (PtD-EMIC) instrument to predict the infection prevention resilience potential of materials commonly used for healthcare contact surfaces. PtD-EMIC is based on fuzzy logic and Adaptive Neural Fuzzy Inference System architecture. Its objective is to serve as a computational design tool that guides the selection and specification of interior materials that may moderate the spread of pathogens in healthcare environments. This objective is accomplished through an applied systems requirement simulation framework that can help guide interior material choice and design for healthcare spaces. The motivation for developing this instrument is to provide a vehicle that can expand healthcare design industry capabilities and interior environment analysis research by using computational approaches to inform interior material selection and design decisions that support healthcare environments’ infection control strategies. The selection and sourcing of embedded data related to relevant and high-use acute care treatment area finishes, the premise of instrument use, precedent research basis, and system architecture, as well as tool validation and demonstration of use, are all discussed. The text explains how using this instrument can facilitate categorization and leveraging interior material performance outcome data for informing safety-critical healthcare design.