Journal of critical care
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Journal of critical care · Dec 2020
ReviewLinking of global intensive care (LOGIC): An international benchmarking in critical care initiative.
Benchmarking is a common and effective method for measuring and analyzing ICU performance. With the existence of national registries, objective information can now be obtained to allow benchmarking of ICU care within and between countries. ⋯ We showed large differences in the utilization of ICU as well as resources and in outcomes. Despite the need for careful interpretation of differences due to variation in definitions and limited risk adjustment, LOGIC is a growing worldwide initiative that allows access to insightful epidemiologic data from ICUs in multiple databases and registries.
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Journal of critical care · Dec 2020
Review Meta AnalysisWhat factors predict length of stay in the intensive care unit? Systematic review and meta-analysis.
Studies have shown that a small percentage of ICU patients have prolonged length of stay (LoS) and account for a large proportion of resource use. Therefore, the identification of prolonged stay patients can improve unit efficiency. In this study, we performed a systematic review and meta-analysis to understand the risk factors of ICU LoS. ⋯ This work suggested a list of risk factors that should be considered in prediction models for ICU LoS, as follows: severity scores, mechanical ventilation, hypomagnesemia, delirium, malnutrition, infection, trauma, red blood cells, and PaO2:FiO2. Our findings can be used by prediction models to improve their predictive capacity of prolonged stay patients, assisting in resource allocation, quality improvement actions, and benchmarking analysis.
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Journal of critical care · Dec 2020
Review Meta AnalysisWhat factors predict length of stay in the intensive care unit? Systematic review and meta-analysis.
Studies have shown that a small percentage of ICU patients have prolonged length of stay (LoS) and account for a large proportion of resource use. Therefore, the identification of prolonged stay patients can improve unit efficiency. In this study, we performed a systematic review and meta-analysis to understand the risk factors of ICU LoS. ⋯ This work suggested a list of risk factors that should be considered in prediction models for ICU LoS, as follows: severity scores, mechanical ventilation, hypomagnesemia, delirium, malnutrition, infection, trauma, red blood cells, and PaO2:FiO2. Our findings can be used by prediction models to improve their predictive capacity of prolonged stay patients, assisting in resource allocation, quality improvement actions, and benchmarking analysis.
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Journal of critical care · Dec 2020
ReviewNovel approaches to facilitate the implementation of guidelines in the ICU.
The effective implementation of evidence-based recommendations in routine intensive care unit (ICU) practice is challenging. Barriers related to the proposed recommendations, local contexts and processes can make the adoption of evidence-based practices difficult, contributing to healthcare inefficiency and worse patient and family outcomes. This review discusses the common barriers to guideline implementation in critical care settings, explores how implementation science provides an important framework for guiding implementation interventions, and discusses some specific and proven implementation strategies to improve adherence to evidence-based practices in the ICU.
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Journal of critical care · Dec 2020
ReviewPrediction on critically ill patients: The role of "big data".
Accurate outcome prediction in Intensive Care Units (ICUs) would allow for better treatment planning, risk adjustment of study populations, and overall improvements in patient care. In the past, prognostic models have focused on mortality using simple ordinal severity of illness scores which could be tabulated manually by a human. With the improvements in computing power and proliferation of electronic medical records, entirely new approaches have become possible. Here we review the latest advances in outcome prediction, paying close attention to methods which are widely applicable and provide a high-level overview of the challenges the field currently faces.