6 research outputs found

    Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

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    Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

    Estimation of quality of experience (QoE) in e-Health ecosystems

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    This article proposes a framework to design and implement e- Health interventions in a comprehensive manner. We draw on complexity science to study the interplay of the ecosystem, the behavior and interactions among its agents. We provide a platform to estimate the Quality of Experience (QoE) to assess the relationship between technology and human factors involved in e-Health projects. Our aim is to estimate QoE in e-Health ecosystems from the perspective of complexity by adopting a methodology that uses fuzzy logic to study the behavior of the ecosystem’s agents. We apply the proposed framework to a remote diagnosis case by means of an ultrasound probe through a satellite link. Despite the ambiguities for determining QoE, the experiment demonstrates the applicability of the framework and allows to stressing the importance of human factors in the implementation of e-Health projects

    Estimation of quality of experience (QoE) in e-Health ecosystems

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    This article proposes a framework to design and implement e- Health interventions in a comprehensive manner. We draw on complexity science to study the interplay of the ecosystem, the behavior and interactions among its agents. We provide a platform to estimate the Quality of Experience (QoE) to assess the relationship between technology and human factors involved in e-Health projects. Our aim is to estimate QoE in e-Health ecosystems from the perspective of complexity by adopting a methodology that uses fuzzy logic to study the behavior of the ecosystem’s agents. We apply the proposed framework to a remote diagnosis case by means of an ultrasound probe through a satellite link. Despite the ambiguities for determining QoE, the experiment demonstrates the applicability of the framework and allows to stressing the importance of human factors in the implementation of e-Health projects.En este artículo se propone un marco de referencia para diseñar e implementar intervenciones de e-Salud de una manera integral. Recurrimos a la ciencia de la complejidad para estudiar la interacción de los agentes del ecosistema. Para ello, proporcionamos una plataforma para estimar la Calidad de Experiencia (o QoE, por sus siglas en inglés) para evaluar la relación entre la tecnología y los factores humanos que intervienen en los proyectos de e-Salud. Nuestro objetivo es estimar la QoE en los ecosistemas de e-Salud desde la perspectiva de la complejidad mediante la adopción de una metodología que utiliza la lógica difusa para estudiar el comportamiento de los agentes del ecosistema. Aplicamos el marco propuesto a un caso de diagnóstico remoto por medio de una sonda de ultrasonido a través de un enlace por satélite. A pesar de las ambigüedades involucradas en la determinación de calidad de la experiencia, el experimento demuestra la aplicabilidad del marco de referencia propuesto y permite subrayar la importancia de los factores humanos en la implementación de proyectos de e-Salud

    Candida bloodstream infections in intensive care units: analysis of the extended prevalence of infection in intensive care unit study

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    To provide a global, up-to-date picture of the prevalence, treatment, and outcomes of Candida bloodstream infections in intensive care unit patients and compare Candida with bacterial bloodstream infection. DESIGN: A retrospective analysis of the Extended Prevalence of Infection in the ICU Study (EPIC II). Demographic, physiological, infection-related and therapeutic data were collected. Patients were grouped as having Candida, Gram-positive, Gram-negative, and combined Candida/bacterial bloodstream infection. Outcome data were assessed at intensive care unit and hospital discharge. SETTING: EPIC II included 1265 intensive care units in 76 countries. PATIENTS: Patients in participating intensive care units on study day. INTERVENTIONS: None. MEASUREMENT AND MAIN RESULTS: Of the 14,414 patients in EPIC II, 99 patients had Candida bloodstream infections for a prevalence of 6.9 per 1000 patients. Sixty-one patients had candidemia alone and 38 patients had combined bloodstream infections. Candida albicans (n = 70) was the predominant species. Primary therapy included monotherapy with fluconazole (n = 39), caspofungin (n = 16), and a polyene-based product (n = 12). Combination therapy was infrequently used (n = 10). Compared with patients with Gram-positive (n = 420) and Gram-negative (n = 264) bloodstream infections, patients with candidemia were more likely to have solid tumors (p < .05) and appeared to have been in an intensive care unit longer (14 days [range, 5-25 days], 8 days [range, 3-20 days], and 10 days [range, 2-23 days], respectively), but this difference was not statistically significant. Severity of illness and organ dysfunction scores were similar between groups. Patients with Candida bloodstream infections, compared with patients with Gram-positive and Gram-negative bloodstream infections, had the greatest crude intensive care unit mortality rates (42.6%, 25.3%, and 29.1%, respectively) and longer intensive care unit lengths of stay (median [interquartile range]) (33 days [18-44], 20 days [9-43], and 21 days [8-46], respectively); however, these differences were not statistically significant. CONCLUSION: Candidemia remains a significant problem in intensive care units patients. In the EPIC II population, Candida albicans was the most common organism and fluconazole remained the predominant antifungal agent used. Candida bloodstream infections are associated with high intensive care unit and hospital mortality rates and resource use
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