Use the links below to access our reports, or scroll down to use the search function to explore all of our publications including peer-reviewed papers and briefing papers.

Browse all publications

Search or filter publications

Filter by type:

Filter by publication type

Filter by year:



  • Showing results for:
  • Reset all filters

Search results

  • Journal article
    Neves AL, van Dael J, O'Brien N, Flott K, Ghafur S, Darzi A, Mayer Eet al., 2024,

    Use and impact of virtual primary care on quality and safety: The public's perspectives during the COVID-19 pandemic

    , Journal of Telemedicine and Telecare, Vol: 30, Pages: 393-401, ISSN: 1357-633X

    IntroductionWith the onset of Coronavirus disease (COVID-19), primary care has swiftly transitioned from face-to-face to virtual care, yet it remains largely unknown how this has impacted the quality and safety of care. We aim to evaluate patient use of virtual primary care models during COVID-19, including change in uptake, perceived impact on the quality and safety of care and willingness of future use.MethodologyAn online cross-sectional survey was administered to the public across the United Kingdom, Sweden, Italy and Germany. McNemar tests were conducted to test pre- and post-pandemic differences in uptake for each technology. One-way analysis of variance was conducted to examine patient experience ratings and perceived impacts on healthcare quality and safety across demographic characteristics.ResultsRespondents (n = 6326) reported an increased use of telephone consultations ( + 6.3%, p < .001), patient-initiated services ( + 1.5%, n = 98, p < 0.001), video consultations ( + 1.4%, p < .001), remote triage ( + 1.3, p < 0.001) and secure messaging systems ( + 0.9%, p = .019). Experience rates using virtual care technologies were higher for men (2.4  ±  1.0 vs. 2.3  ±  0.9, p < .001), those with higher literacy (2.8  ±  1.0 vs. 2.3  ±  0.9, p < .001), and participants from Germany (2.5  ±  0.9, p < .001). Healthcare timeliness and efficiency were the dimensions most often reported as being positively impacted by virtual technologies (60.2%, n = 2793 and 55.7%, n = 2,401, respectively), followed by effectiveness (46.5%, n = 

  • Journal article
    Alford J, Massazza A, Jennings NR, Lawrance Eet al., 2023,

    Developing global recommendations for action on climate change and mental health across sectors: a Delphi-style study

    , The Journal of Climate Change and Health, Vol: 12, Pages: 1-11, ISSN: 2667-2782

    Climate change is causing far-reaching yet underappreciated worsening of outcomes across the mental health and wellbeing spectrum. Despite increasing attention to the mental health impacts of climate change, an absence of a clear, cross-sectoral agenda for action has held back progress against the dual and interconnected challenges of supporting human and planetary health. This study aims to serve as an essential first step to address this gap. Harnessing the expertise of a diverse panel of 61 participants, representing 24 nationalities, this study developed and prioritized recommendations for action on climate change and mental health across the relevant sectors of research, policy, healthcare and the third sector, and used a Delphi-style methodology to examine their feasibility and importance. Broadly, the prioritized recommendations highlighted the need to expand the evidence base, work collaboratively across sectors, and raise awareness. While broadly there was consensus on recommendation importance, there was greater variation in the reported feasibility of the recommendations, which differed across settings. Other common themes included the need for cultural and resource contextualization, raising awareness of and addressing mental health co-benefits via climate action, and working with communities with lived experience to develop and implement the findings. As there may be some interdependencies between the recommendations, further work needs to identify how best to implement them. The recommendations serve as a robust and evidence-based framework that can be used as a foundation to devise locally appropriate, concrete implementation strategies matching levels of need and resource. These also serve as a clear call to action for investment from leaders across sectors to ensure they are realized.

  • Journal article
    Bai W, Cursi F, Guo X, Huang B, Lo B, Yang G-Z, Yeatman EMet al., 2022,

    Task-Based LSTM Kinematic Modeling for a Tendon-Driven Flexible Surgical Robot

  • Journal article
    Lam K, Chen J, Wang Z, Iqbal F, Darzi A, Lo B, Purkayastha S, Kinross Jet al., 2022,

    Machine learning for technical skill assessment in surgery: a systematic review

    , npj Digital Medicine, Vol: 5, ISSN: 2398-6352

    Accurate and objective performance assessment is essential for both trainees and certified surgeons. However, existing methods can be time consuming, labor intensive and subject to bias. Machine learning (ML) has the potential to provide rapid, automated and reproducible feedback without the need for expert reviewers. We aimed to systematically review the literature and determine the ML techniques used for technical surgical skill assessment and identify challenges and barriers in the field. A systematic literature search, in accordance with the PRISMA statement, was performed to identify studies detailing the use of ML for technical skill assessment in surgery. Of the 1896 studies that were retrieved, 66 studies were included. The most common ML methods used were Hidden Markov Models (HMM, 14/66), Support Vector Machines (SVM, 17/66) and Artificial Neural Networks (ANN, 17/66). 40/66 studies used kinematic data, 19/66 used video or image data, and 7/66 used both. Studies assessed performance of benchtop tasks (48/66), simulator tasks (10/66), and real-life surgery (8/66). Accuracy rates of over 80% were achieved, although tasks and participants varied between studies. Barriers to progress in the field included a focus on basic tasks, lack of standardization between studies, and lack of datasets. ML has the potential to produce accurate and objective surgical skill assessment through the use of methods including HMM, SVM, and ANN. Future ML-based assessment tools should move beyond the assessment ofbasic tasks and towards real-life surgery and provide interpretable feedback with clinical value for the surgeon.

  • Journal article
    Danielli S, Donnelly P, Coffey T, Horn S, Ashrafian H, Darzi Aet al., 2022,

    Measuring more than just economic growth to improve well-being

    , Journal of Public Health, Vol: 44, Pages: e76-e78, ISSN: 1741-3842

    It's official: The UK is in a recession. The economy has suffered its biggest slump on record with a drop in gross domestic product (GDP) of 20.4%. 1 This is going to have a significant impact on our health and well-being. It risks creating a spiralling decay as we know good health is not only a consequence, but also a condition for sustained and sustainable economic development. 2 In this way, the health of a nation creates a virtuous circle of improved health and improved economic prosperity. How we measure prosperity is therefore important and needs to be considered.

  • Journal article
    O'Brien N, Shaw A, Flott K, Leatherman S, Durkin Met al., 2022,

    Safety in fragile, conflict-affected, and vulnerable settings: An evidence scanning approach for identifying patient safety interventions

    , Journal of Global Health, Vol: 12, Pages: 1-10, ISSN: 2047-2978

    BackgroundThe number of people living in fragile, conflict-affected, and vulnerable (FCV) settings is growing rapidly and attention to achieving universal health coverage must be accompanied by sufficient focus on the safety of care for universal access to be meaningful. Healthcare workers in these settings are working under extreme conditions, often with insufficient contextualized evidence to support decision-making. Recognising the relative paucity of, and methodological issues in gathering evidence from these settings, the evidence scanning described in this paper considered which patient safety interventions might offer the ‘better bet’, e.g., the most effective and appropriate intervention in FCV settings.MethodsAn evidence scanning approach was used to examine the literature. The search was limited to FCV settings and low-income settings as defined by the World Bank, but if a systematic review included a mix of evidence from FCV/low income settings, as well as low-middle income settings, it was included. The search was conducted in English and limited to studies published from 2003 onwards, utilising Google Scholar as a publicly accessible database and further review of the grey literature, with specific attention to the outputs of non-governmental organisations. The search and subsequent analysis were completed between April and June 2020.FindingsThe majority of studies identified related to strengthening infection prevention and control which was also found to be the ‘better bet’ intervention that could generalise to other settings, be most feasible to implement, and most effective for improving patient care and associated outcomes. Other prioritized interventions include risk management, with contributing elements such as reporting, audits, and death review processes.ConclusionsInfection prevention and control interventions dominate in the literature for multiple reasons including strength of evidence, acceptability, feasibility, an

  • Journal article
    O'Brien N, Flott K, Bray O, Shaw A, Durkin Met al., 2022,

    Implementation of initiatives designed to improve healthcare worker health and wellbeing during the COVID-19 pandemic: comparative case studies from 13 healthcare provider organisations globally

    , Globalization and Health, Vol: 18, ISSN: 1744-8603

    Background: Healthcare workers are at a disproportionate risk of contracting COVID-19. The physical and mental repercussions of such risk have an impact on the wellbeing of healthcare workers around the world. Healthcare workers are the foundation of all well-functioning health systems capable of responding to the ongoing pandemic; initiatives to address and reduce such risk are critical. Since the onset of the pandemic healthcare organizations have embarked on the implementation of a range of initiatives designed to improve healthcare worker health and wellbeing. Methods: Through a qualitative collective case study approach where participants responded to a longform survey, the facilitators, and barriers to implementing such initiatives were explored, offering global insights into the challenges faced at the organizational level. 13 healthcare organizations were surveyed across 13 countries. Of these 13 participants, 5 subsequently provided missing information through longform interviews or written clarifications.Results: 13 case studies were received from healthcare provider organizations. Mental health initiatives were the most commonly described health and wellbeing initiatives among respondents. Physical health and health and safety focused initiatives, such as the adaption of workspaces, were also described. Strong institutional level direction, including engaged leadership, and the input, feedback, and engagement of frontline staff were the two main facilitators in implementing initiatives. The most common barrier to implementation, noted largely by organizations who discussed infection prevention and control initiatives, was inadequate personal protective equipment and supply chain disruption. Conclusions: Common themes emerge globally in exploring the enablers and barriers to implementing initiatives to improve healthcare workers health and wellbeing through the COVID-19 pandemic. Consideration of the themes outlined in the paper by healthcare organizations

  • Journal article
    Elliott P, Bodinier B, Eales O, Wang H, Haw D, Elliott J, Whitaker M, Jonnerby J, Tang D, Walters CE, Atchison C, Diggle PJ, Page AJ, Trotter AJ, Ashby D, Barclay W, Taylor G, Ward H, Darzi A, Cooke GS, Chadeau-Hyam M, Donnelly CAet al., 2022,

    Rapid increase in Omicron infections in England during December 2021: REACT-1 study.

    , Science, Vol: 375, Pages: eabn8347-eabn8347, ISSN: 0036-8075

    The unprecedented rise in SARS-CoV-2 infections during December 2021 was concurrent with rapid spread of the Omicron variant in England and globally. We analyzed prevalence of SARS-CoV-2 and its dynamics in England from end November to mid-December 2021 among almost 100,000 participants from the REACT-1 study. Prevalence was high with rapid growth nationally and particularly in London during December 2021, and an increasing proportion of infections due to Omicron. We observed large falls in swab positivity among mostly vaccinated older children (12-17 years) compared with unvaccinated younger children (5-11 years), and in adults who received a third (booster) vaccine dose vs. two doses. Our results reinforce the importance of vaccination and booster campaigns, although additional measures have been needed to control the rapid growth of the Omicron variant.

  • Journal article
    Khanbhai M, Symons J, Flott K, Harrison-White S, Spofforth J, Klaber R, Manton D, Darzi A, Mayer Eet al., 2022,

    Enriching the value of patient experience feedback: interactive dashboard development using co-design and heuristic evaluation

    , JMIR Human Factors, Vol: 9, Pages: 1-14, ISSN: 2292-9495

    Background:There is an abundance of patient experience data held within healthcare organisations but stakeholders and staff are often unable to use the output in a meaningful and timely way to improve care delivery. Dashboards, which use visualised data to summarise key patient experience feedback, have the potential to address these issues.Objective:The aim of this study was to develop a patient experience dashboard with an emphasis on FFT reporting as per the national policy drive. An iterative process involving co-design involving key stakeholders was used to develop the dashboard, followed by heuristic usability testing.Methods:A two staged approach was employed; participatory co-design involving 20 co-designers to develop a dashboard prototype followed by iterative dashboard testing. Language analysis was performed on free-text patient experience data from the Friends and Family Test (FFT) and the themes and sentiment generated was used to populate the dashboard with associated FFT metrics. Heuristic evaluation and usability testing were conducted to refine the dashboard and assess user satisfaction using the system usability score (SUS).Results:Qualitative analysis from the co-design process informed development of the dashboard prototype with key dashboard requirements and a significant preference for bubble chart display. Heuristic evaluation revelated the majority of cumulative scores had no usability problem (n=18), cosmetic problem only (n=7), or minor usability problem (n= 5). Mean SUS was 89.7 (SD 7.9) suggesting an excellent rating.Conclusions:The growing capacity to collect and process patient experience data suggests that data visualisation will be increasingly important in turning the feedback into improvements to care. Through heuristic usability we demonstrated that very large FFT data can be presented into a thematically driven, simple visual display without loss of the nuances and still allow for exploration of the original free-text comments. T

  • Journal article
    Sounderajah V, 2022,

    Quality assessment standards in artificial intelligence diagnostic accuracy systematic reviews: a meta-research study

    , npj Digital Medicine, Vol: 5, Pages: 1-13, ISSN: 2398-6352

    Artificial intelligence (AI) centred diagnostic systems are increasingly recognized as robust solutions in healthcare delivery pathways. In turn, there has been a concurrent rise in secondary research studies regarding these technologies in order to influence key clinical and policymaking decisions. It is therefore essential that these studies accurately appraise methodological quality and risk of bias within shortlisted trials and reports. In order to assess whether this critical step is performed, we undertook a meta-research study evaluating adherence to the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool within AI diagnostic accuracy systematic reviews. A literature search was conducted on all studies published from 2000 to December 2020. Of 50 included reviews, 36 performed quality assessment, of which 27 utilised the QUADAS-2 tool. Bias was reported across all four domains of QUADAS-2. 243 of 423 studies (57.5%) across all systematic reviews utilising QUADAS-2 reported a high or unclear risk of bias in the patient selection domain, 110 (26%) reported a high or unclear risk of bias in the index test domain, 121 (28.6%) in the reference standard domain and 157 (37.1%) in the flow and timing domain. This study demonstrates incomplete uptake of quality assessment tools in reviews of AI-based diagnostic accuracy studies and highlights inconsistent reporting across all domains of quality assessment. Poor standards of reporting act as barriers to clinical implementation. The creation of an AI specific extension for quality assessment tools of diagnostic accuracy AI studies may facilitate the safe translation of AI tools into clinical practice.

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

Request URL: Request URI: /respub/WEB-INF/jsp/search-t4-html.jsp Query String: id=281&limit=10&page=1&respub-action=search.html Current Millis: 1713147198658 Current Time: Mon Apr 15 03:13:18 BST 2024