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      Clinical practice, decision-making, and use of clinical decision support systems in invasive mechanical ventilation: a narrative review

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          Summary

          Invasive mechanical ventilation is a key supportive therapy for patients on intensive care. There is increasing emphasis on personalised ventilation strategies. Clinical decision support systems (CDSS) have been developed to support this. We conducted a narrative review to assess evidence that could inform device implementation.

          A search was conducted in MEDLINE (Ovid) and EMBASE. Twenty-nine studies met the inclusion criteria. Role allocation is well described, with interprofessional collaboration dependent on culture, nurse:patient ratio, the use of protocols, and perception of responsibility. There were no descriptions of process measures, quality metrics, or clinical workflow. Nurse-led weaning is well-described, with factors grouped by patient, nurse, and system. Physician-led weaning is heterogenous, guided by subjective and objective information, and ‘gestalt’. No studies explored decision-making with CDSS. Several explored facilitators and barriers to implementation, grouped by clinician (facilitators: confidence using CDSS, retaining decision-making ownership; barriers: undermining clinician's role, ambiguity moving off protocol), intervention (facilitators: user-friendly interface, ease of workflow integration, minimal training requirement; barriers: increased documentation time), and organisation (facilitators: system-level mandate; barriers: poor communication, inconsistent training, lack of technical support). One study described factors that support CDSS implementation.

          There are gaps in our understanding of ventilation practice. A coordinated approach grounded in implementation science is required to support CDSS implementation. Future research should describe factors that guide clinical decision-making throughout mechanical ventilation, with and without CDSS, map clinical workflow, and devise implementation toolkits. Novel research design analogous to a learning organisation, that considers the commercial aspects of device design, is required.

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          Most cited references64

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          Making sense of implementation theories, models and frameworks

          Background Implementation science has progressed towards increased use of theoretical approaches to provide better understanding and explanation of how and why implementation succeeds or fails. The aim of this article is to propose a taxonomy that distinguishes between different categories of theories, models and frameworks in implementation science, to facilitate appropriate selection and application of relevant approaches in implementation research and practice and to foster cross-disciplinary dialogue among implementation researchers. Discussion Theoretical approaches used in implementation science have three overarching aims: describing and/or guiding the process of translating research into practice (process models); understanding and/or explaining what influences implementation outcomes (determinant frameworks, classic theories, implementation theories); and evaluating implementation (evaluation frameworks). Summary This article proposes five categories of theoretical approaches to achieve three overarching aims. These categories are not always recognized as separate types of approaches in the literature. While there is overlap between some of the theories, models and frameworks, awareness of the differences is important to facilitate the selection of relevant approaches. Most determinant frameworks provide limited “how-to” support for carrying out implementation endeavours since the determinants usually are too generic to provide sufficient detail for guiding an implementation process. And while the relevance of addressing barriers and enablers to translating research into practice is mentioned in many process models, these models do not identify or systematically structure specific determinants associated with implementation success. Furthermore, process models recognize a temporal sequence of implementation endeavours, whereas determinant frameworks do not explicitly take a process perspective of implementation.
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            Technology Acceptance Model 3 and a Research Agenda on Interventions

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              Acute Respiratory Distress Syndrome

              Acute respiratory distress syndrome (ARDS) is a life-threatening form of respiratory failure that affects approximately 200 000 patients each year in the United States, resulting in nearly 75 000 deaths annually. Globally, ARDS accounts for 10% of intensive care unit admissions, representing more than 3 million patients with ARDS annually.
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                Author and article information

                Contributors
                Journal
                Br J Anaesth
                Br J Anaesth
                BJA: British Journal of Anaesthesia
                Elsevier
                0007-0912
                1471-6771
                17 April 2024
                July 2024
                17 April 2024
                : 133
                : 1
                : 164-177
                Affiliations
                [1 ]Division of Anaesthetics, Pain Medicine & Intensive Care, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London, UK
                [2 ]NIHR London In Vitro Diagnostics Cooperative, London, UK
                [3 ]Respiratory and Critical Care Group, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
                [4 ]Imperial Centre for Paediatrics and Child Health, London, UK
                [5 ]Department of Anaesthesia & Critical Care, Royal Brompton Hospital, London, UK
                Author notes
                [* ]Corresponding author. m.murali@ 123456imperial.ac.uk
                Article
                S0007-0912(24)00142-9
                10.1016/j.bja.2024.03.011
                11213991
                38637268
                c0f0aa28-10e3-486e-b1f0-c2869db79294
                © 2024 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 24 November 2023
                : 7 March 2024
                Categories
                Respiration and the Airway

                Anesthesiology & Pain management
                clinical decision support system,clinical practice,decision-making,implementation,invasive mechanical ventilation,personalised ventilation

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