10 research outputs found

    A systematic review of de-escalation strategies for redeployed staff and repurposed facilities in COVID-19 intensive care units (ICUs) during the pandemic

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    Background: Intensive care units (ICUs) experienced a surge in patient cases during the COVID-19 pandemic. Demand was managed by redeploying healthcare workers (HCWs) and restructuring facilities. The rate of ICU admissions has subsided in many regions, with the redeployed workforce and facilities returning to usual functions. Previous literature has focused on the escalation of ICUs, limited research exists on de-escalation. This study aimed to identify the supportive and operational strategies used for the flexible de-escalation of ICUs in the context of COVID-19. Methods: The systematic review was developed by searching eight databases in April and November 2021. Papers discussing the return of redeployed staff and facilities and the training, wellbeing, and operational strategies were included. Excluded papers were non-English and unrelated to ICU de-escalation. Quality was assessed using the mixed methods appraisal tool (MMAT) and authority, accuracy, coverage, objectivity, date, and significance (AACODS) checklist, findings were developed using narrative synthesis and thematic analysis. Findings: Fifteen papers were included from six countries covering wellbeing and training themes encompassing; time off, psychological follow-up, gratitude, identification of training needs, missed training catch-up, and continuation of ICU and disaster management training. Operational themes included management of rotas, retainment of staff, division of ICU facilities, leadership changes, traffic light systems, and preparation for re-expansion. Interpretation: The review provided an overview of the landscape of de-escalation strategies that have taken place in six countries. Limited empirical evidence was available that evaluated the effectiveness of such strategies. Empirical and evaluative research from a larger array of countries is needed to be able to make global recommendations on ICU de-escalation practices

    Engaging domestic abuse practitioners and survivors in a review of outcome tools – reflections on differing priorities

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    Researchers often develop and decide upon the measurement tools for assessing outcomes related to domestic abuse interventions. However, it is known that clients, service providers and researchers have different ideas about the outcomes that should be measured as markers of success. Evidence from non-domestic abuse sectors indicates that engagement of service providers, clients and researchers contributes to more robust research, policy and practice. We reflect on what we have learnt from the engagement of practitioners and domestic abuse survivors in a review of domestic abuse measurement tools where there were clear differences in priorities between survivors, practitioners and researchers about the ideal measurement tools. The purpose of this reflective article is to support the improvement of future outcome measurement from domestic abuse interventions, while ensuring that domestic abuse survivors do not relive trauma because of measurement

    Patients’ Experiences of a Sarcoma Diagnosis: A Process Mapping Exercise of Diagnostic Pathways

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    Patients with sarcoma often report prolonged time to diagnosis, which is attributed to the rarity of sarcoma and the low awareness of pre-diagnostic signs and symptoms. Aims: To describe patients’ experiences of pre-diagnostic signs/symptoms and pathways to diagnosis, including where help was sought, and the processes involved. Methods: Mixed methods involving quantitative, qualitative and inductive thematic analyses using novel process mapping of patient journey data, as reported by the patients. We examined the time from symptom onset to first professional presentation (patient interval, PI), first consultation to diagnostic biopsy, first consultation to diagnosis (diagnostic interval) and first presentation to diagnosis (total interval). Results: A total of 87 interviews were conducted over 5 months in 2017. Of these, 78 (40 males/38 females) were included. The sarcoma subtypes were bone (n = 21), soft tissue (n = 41), head and neck (n = 9) and gastro-intestinal (GIST; n = 7). Age at diagnosis was 13–24 (n = 7), 25–39 (n = 23), 40–64 (n = 34) and 65+ (n = 14) years. The median PI was 13 days (1–4971) and similar between sarcoma subtypes, with the exception of GIST (mPI = 2 days, (1–60). The longest mPI (31 days, range 4–762) was for those aged 13–24 years. The median diagnostic interval was 87.5 (range 0–5474 days). A total of 21 patients were misdiagnosed prior to diagnosis and symptoms were commonly attributed to lifestyle factors. Conclusions: Prolonged times to diagnosis were experienced by the majority of patients in our sample. Further research into the evolution of pre-diagnostic sarcoma symptoms is required to inform awareness interventions

    Standards for Rapid Evaluation and Appraisal Methods

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    The Rapid Research Evaluation and Appraisal Lab (RREAL) are working to improve the transparency and completeness of reporting and to increase the quality of rapid studies by developing Standards for Rapid Evaluation and Appraisal Methods (STREAM). This is an 18-month MRC-UKRI funded research project, the ultimate aim is for STREAM to become internationally used as a guideline for the design and implementation of rapid evaluations and appraisal methods, as a reporting template, and as a quality assessment tool. This project has been registered with the EQUATOR network: https://www.equator-network.org/library/reporting-guidelines-under-development/reporting-guidelines-under-development-for-other-study-designs/#STREA

    STREAM Stakeholder workshops

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    This is the third phase of the STREAM project. Updates will be available following the completion of phase 2 (e-Delphi study)

    Training and redeployment of healthcare workers to intensive care units (ICUs) during the COVID-19 pandemic: a systematic review.

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    OBJECTIVES The rapid influx of patients with COVID-19 to intensive care at a rate that exceeds pre-existing staff capacity has required the rapid development of innovative redeployment and training strategies, which considered patient care and infection control. The aim of this study was to provide a detailed understanding of redeployment and training during the first year of the COVID-19 pandemic by capturing and considering the merit of the strategies enlisted and the experiences and needs of redeployed healthcare workers (HCWs). DESIGN The review involved a systematic search of key terms related to intensive care AND training AND redeployment AND healthcare workers within nine databases (Medline, CINAHL, PsychINFO, MedRxiv, Web of Science, The Health Management Consortium database, Social Science Research Network, OpenGrey and TRIP), which took place on 16 July 2021. Analysis consisted of a synthesis of quantitative study outputs and framework-based thematic analysis of qualitative study outputs and grey literature. These results were then combined applying an interpretative synthesis. We followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses, and the review protocol was available online. RESULTS Forty papers were analysed. These took place primarily in the UK (n=15, 37.5%) and USA (n=17, 42.5%). Themes presented in the results are . Based on this, key principles for successful redeployment and training were proposed. CONCLUSIONS The COVID-19 pandemic presents unique challenges to develop flexible redeployment strategies and deliver training promptly while following infection control recommendations. This review synthesises original approaches to tackle these challenges, which are relevant to inform the development of targeted and adaptative training and redeployment plans considering the needs of HCWs

    LISTEN - Collaborative and Digital Analysis of Big Qualitative Data in Time Sensitive Contexts

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    Our project will develop, implement, evaluate and disseminate the Collaborative and Digital Analysis of Big Qual Data in Time Sensitive Contexts (LISTEN) method
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