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Purpose: To present the social network analysis-based approach used to create a new workspace layout for three hospital services as part of a campus expansion at a large tertiary care public hospital. Objective: To analyze the relationships among service members across four healthcare resilience abilities (monitor, anticipate, respond, and learn) and utilize network metrics to indicate the suitability of a shared workspace layout for the services. Background: The hospital expanded by 70%, providing space for relocating key services-the rapid response team, medical on-call team, and nursing supervision. Initial observations suggested a shared workspace layout based on anecdotal evidence. Method: Stakeholders have reached a consensus on a three-stage process to assess the suitability of a shared workspace layout for these services: first, collecting data on social interactions with a focus on resilience abilities; second, presenting layout alternatives based on sociograms; and third, evaluating these alternatives and devising a strategy for allocating personnel to shifts based on a resilience score derived from social network metrics. Case Study: The examination of social network metrics allowed identifying key individuals contributing to the overall resilience of the three services. Sociograms provided visual representations of how these individuals were spatially distributed within the shared layout. Discussion: The process was designed to shape a resilient layout and incorporated initial data, preferences, and constraints into layout proposals. Additionally, it utilized a resilience score from existing literature to formulate a strategy for staff allocation to shifts, ensuring consistent collective resilience ability across all shifts.

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The demand for mobile e-health technologies (m-health) continues with constant growth, stimulating the technological advancement of such devices. However, the customer needs to perceive the utility of these devices to incorporate them into their daily lives. Hence, this study aims to identify users' perceptions regarding the acceptance of m-health technologies based on a synthesis of meta-analysis studies on the subject in the literature. Using the relations and constructs proposed in the UTAUT2 (Unified Theory of Acceptance and Use of Technology 2) technology acceptance model, the methodological approach utilized a meta-analysis to raise the effect of the main factors on the Behavioral Intention to Use m-health technologies. Furthermore, the model proposed also estimated the moderation effect of gender, age, and timeline variables on the UTAUT2 relations. In total, the meta-analysis utilized 84 different articles, which presented 376 estimations based on a sample of 31,609 respondents. The results indicate an overall compilation of the relations, as well as the primary factors and moderating variables that determine users' acceptance of the studied m-health systems.

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This study aims to (i) propose a demand forecast model for special nutrition materials in the context of health services, and (ii) comparatively evaluate three inventory management and control systems (periodic review, continuous review and mixed) for special nutrition materials. For that, we carried out a case study in a Brazilian public teaching hospital where data and information collection were conducted over a span of 22 months (from January 2018 and were consolidated until October 2019). A six-step approach was followed to propose the demand forecasting models and, later, evaluate the inventory control systems for special nutrition materials. Results indicate that if the organization implements the proposed inventory management method, there could be savings of up to 33% in the stock values managed by the healthcare organization. This research shows the planning and control of special nutrition materials in an integrated manner. Demand forecasting methods have been combined with inventory management to promote systemic improvements to healthcare organization.

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BACKGROUND: Alternative approaches to analyzing and evaluating health care investments in state-of-the-art technologies are being increasingly discussed in the literature, especially with the advent of Healthcare 4.0 (H4.0) technologies or eHealth. Such investments generally involve computer hardware and software that deal with the storage, retrieval, sharing, and use of health care information, data, and knowledge for communication and decision-making. Besides, the use of these technologies significantly increases when addressed in bundles. However, a structured and holistic approach to analyzing investments in H4.0 technologies is not available in the literature. OBJECTIVE: This study aims to analyze previous research related to the evaluation of H4.0 technologies in hospitals and characterize the most common investment approaches used. We propose a framework that organizes the research associated with hospitals' H4.0 technology investment decisions and suggest five main research directions on the topic. METHODS: To achieve our goal, we followed the standard procedure for scoping reviews. We performed a search in the Crossref, PubMed, Scopus, and Web of Science databases with the keywords investment, health, industry 4.0, investment, health technology assessment, healthcare 4.0, and smart in the title, abstract, and keywords of research papers. We retrieved 5701 publications from all the databases. After removing papers published before 2011 as well as duplicates and performing further screening, we were left with 244 articles, from which 33 were selected after in-depth analysis to compose the final publication portfolio. RESULTS: Our findings show the multidisciplinary nature of the research related to evaluating hospital investments in H4.0 technologies. We found that the most common investment approaches focused on cost analysis, single technology, and single decision-maker involvement, which dominate bundle analysis, H4.0 technology value considerations, and multiple decision-maker involvement. CONCLUSIONS: Some of our findings were unexpected, given the interrelated nature of H4.0 technologies and their multidimensional impact. Owing to the absence of a more holistic approach to H4.0 technology investment decisions, we identified five promising research directions for the topic: development of economic valuation methodologies tailored for H4.0 technologies; accounting for technology interrelations in the form of bundles; accounting for uncertainties in the process of evaluating such technologies; integration of administrative, medical, and patient perspectives into the evaluation process; and balancing and handling complexity in the decision-making process.

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The objective of this article is three-fold. First, it aims at identifying the main teaching practices and information and communication technologies (ICTs) used to teach Operations Management (OM) in emerging economies during COVID-19 outbreak. Second, it investigates the effect of contextual characteristics on the adoption level of those teaching practices and ICTs. Third, this study examines the relationship between the adoption of ICTs and OM teaching practices during COVID-19 outbreak. Expectedly, schools around the world have pivoted to online learning and digital classrooms. Thus, OM lecturers and professors located in emerging economies that have been teaching during COVID-19 outbreak were surveyed. The collected data was analyzed through multivariate techniques. Findings indicate that lecturers and professors have been remarkably adopting specific teaching practices and ICTs to teach OM. Nevertheless, when considering the contextual characteristics of the universities, departments, and lecturers/professors, the adoption level of those practices and ICTs may significantly vary, especially depending on subject type and teaching experience. Moreover, we empirically verified that ICTs positively relate with OM teaching practices in emerging economies, although in a much less extent than expected. This research provides OM instructors guidelines to better plan their courses and subjects in face of extreme disruptive moments, such as the one caused by the COVID-19. Understanding how the concurrent utilization of ICTs and teaching practices helps OM programs to continue developing their activities is particularly important for universities located in emerging economies, since they are more likely to struggle with resources scarcity and more financially humble students.