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
    Dewa L, Crandell C, Choong E, Jaques J, Bottle R, Kilkenny C, Lawrence-Jones A, Di Simplicio M, Nicholls D, Aylin Pet al., 2020,

    CCopeY: a mixed-methods co-produced study on the mental health status and coping strategies of young people during COVID-19 UK lockdown

    , Journal of Adolescent Health, ISSN: 1054-139X

    PurposeExploring the impact of COVID-19 pandemic on young people’s mental health is an increasing priority. Studies to date are largely surveys and lack meaningful involvement from service users in their design, planning and delivery. The study aimed to examine the mental health status and coping strategies of young people during the first UK COVID-19 lockdown using co-production methodology.MethodsThe mental health status of young people (aged 16-24) in April 2020 was established utilising a sequential explanatory co-produced mixed methods design. Factors associated with poor mental health status including coping strategies were also examined using an online survey and semi-structured interviews.Results30.3% had poor mental health and 10.8% had self-harmed since lockdown. Young people identifying as Black/Black-British ethnicity had the highest increased odds of experiencing poor mental health (odds ratio [OR] 3.688, 95% CI 0.54-25.40). Behavioural disengagement (OR 1.462, 95% CI 1.22-1.76), self-blame (OR 1.307 95% CI 1.10-1.55), and substance use (OR 1.211 95% CI 1.02-1.44) coping strategies, negative affect (OR 1.109, 95% CI 1.07-1.15), sleep problems (OR 0.915 95% CI 0.88-0.95) and conscientiousness personality trait (OR 0.819 95% CI 0.69-0.98) were significantly associated with poor mental health. Three qualitative themes were identified: (1) pre-existing/developed helpful coping strategies employed, (2) mental health difficulties worsened and (3) mental health and non-mental health support needed during and after lockdown.ConclusionPoor mental health is associated with dysfunctional coping strategies. Innovative coping strategies can help other young people cope during and after lockdowns, with digital and school promotion and application.

  • Journal article
    Iqbal F, Lam K, Joshi M, Khan S, Ashrafian H, Darzi Aet al., 2021,

    Clinical outcomes of digital sensor alerting systems in remote monitoring: a systematic review and meta-analysis

    , npj Digital Medicine, Vol: 4, Pages: 1-12, ISSN: 2398-6352

    Advances in digital technologies have allowed remote monitoring and digital alerting systems to gain popularity. Despite this, limited evidence exists to substantiate claims that digital alerting can improve clinical outcomes. The aim of this study was to appraise the evidence on the clinical outcomes of digital alerting systems in remote monitoring through a systematic review and meta-analysis. A systematic literature search, with no language restrictions, was performed to identify studies evaluating healthcare outcomes of digital sensor alerting systems used in remote monitoring across all (medical and surgical) cohorts. The primary outcome was hospitalisation; secondary outcomes included hospital length of stay (LOS), mortality, emergency department and outpatient visits. Standard, pooled hazard ratio and proportion of means meta-analyses were performed. A total of 33 studies met the eligibility criteria; of which, 23 allowed for a meta-analysis. A 9.6% mean decrease in hospitalisation favouring digital alerting systems from a pooled random effects analysis was noted. However, pooled weighted mean differences and hazard ratios did not reproduce this finding. Digital alerting reduced hospital LOS by a mean difference of 1.043 days. A 3% mean decrease in all-cause mortality from digital alerting systems was noted. There was no benefit of digital alerting with respect to emergency department or outpatient visits. Digital alerts can considerably reduce hospitalisation and length of stay for certain cohorts in remote monitoring. Further research is required to confirm these findings and trial different alerting protocols to understand optimal alerting to guide future widespread implementation.

  • Journal article
    Jones MD, McGrogan A, Raynor DK, Watson MC, Franklin BDet al., 2021,

    User-testing guidelines to improve the safety of intravenous medicines administration: a randomised in situ simulation study

    , BMJ QUALITY & SAFETY, Vol: 30, Pages: 17-26, ISSN: 2044-5415
  • Journal article
    O'Brien N, Grass E, Martin G, Durkin M, Darzi A, Ghafur Set al., 2021,

    Developing a globally applicable cybersecurity framework for healthcare: a Delphi consensus study

    , BMJ INNOVATIONS, Vol: 7, Pages: 199-207, ISSN: 2055-8074
  • Journal article
    Smalley K, Aufegger L, Flott K, Mayer E, Darzi Aet al., 2021,

    Can self-management programmes change healthcare utilisation in COPD?: A systematic review and framework analysis

    , Patient Education and Counseling, Vol: 104, Pages: 50-63, ISSN: 0738-3991

    ObjectiveThe study aims to evaluate the ability of self-management programmes to change the healthcare-seeking behaviours of people with Chronic Obstructive Pulmonary Disease (COPD), and any associations between programme design and outcomes.MethodsA systematic search of the literature returned randomised controlled trials of SMPs for COPD. Change in healthcare utilisation was the primary outcome measure. Programme design was analysed using the Theoretical Domains Framework (TDF).ResultsA total of 26 papers described 19 SMPs. The most common utilisation outcome was hospitalisation (n = 22). Of these, 5 showed a significant decrease. Two theoretical domains were evidenced in all programmes: skills and behavioural regulation. All programmes evidenced at least 5 domains. However, there was no clear association between TDF domains and utilisation. Overall, study quality was moderate to poor.ConclusionThis review highlights the need for more alignment in the goals, design, and evaluation of SMPs. Specifically, the TDF could be used to guide programme design and evaluation in future.Practice implicationsPractices have a reasonable expectation that interventions they adopt will provide patient benefit and value for money. Better design and reporting of SMP trials would address their ability to do so.

  • Journal article
    Sounderajah V, Patel V, Varatharajan L, Harling L, Normahani P, Symons J, Barlow J, Darzi A, Ashrafian Het al., 2020,

    Are disruptive innovations recognised in the healthcare literature? A systematic review

    , BMJ Innovations, Vol: 7, Pages: 208-216, ISSN: 2055-8074

    The study aims to conduct a systematic review to characterise the spread and use of the concept of ‘disruptive innovation’ within the healthcare sector. We aim to categorise references to the concept over time, across geographical regions and across prespecified healthcare domains. From this, we further aim to critique and challenge the sector-specific use of the concept. PubMed, Medline, Embase, Global Health, PsycINFO, Maternity and Infant Care, and Health Management Information Consortium were searched from inception to August 2019 for references pertaining to disruptive innovations within the healthcare industry. The heterogeneity of the articles precluded a meta-analysis, and neither quality scoring of articles nor risk of bias analyses were required. 245 articles that detailed perceived disruptive innovations within the health sector were identified. The disruptive innovations were categorised into seven domains: basic science (19.2%), device (12.2%), diagnostics (4.9%), digital health (21.6%), education (5.3%), processes (17.6%) and technique (19.2%). The term has been used with increasing frequency annually and is predominantly cited in North American (78.4%) and European (15.2%) articles. The five most cited disruptive innovations in healthcare are ‘omics’ technologies, mobile health applications, telemedicine, health informatics and retail clinics. The concept ‘disruptive innovation’ has diffused into the healthcare industry. However, its use remains inconsistent and the recognition of disruption is obscured by other types of innovation. The current definition does not accommodate for prospective scouting of disruptive innovations, a likely hindrance to policy makers. Redefining disruptive innovation within the healthcare sector is therefore crucial for prospectively identifying cost-effective innovations.

  • Report
    Riley S, Walters C, Wang H, Eales O, Ainslie K, Atchison C, Fronterre C, Diggle PJ, Ashby D, Donnelly C, Cooke G, Barclay W, Ward H, Darzi A, Elliott Pet al., 2020,

    REACT-1 round 7 updated report: regional heterogeneity in changes in prevalence of SARS-CoV-2 infection during the second national COVID-19 lockdown in England

    , REACT-1 round 7 updated report: regional heterogeneity in changes in prevalence of SARS-CoV-2 infection during the second national COVID-19 lockdown in England, London, Publisher: Imperial College London

    BackgroundEngland exited a four-week second national lockdown on 2nd December 2020 initiated in response to the COVID-19 pandemic. Prior results showed that prevalence dropped during the first half of lockdown, with greater reductions in higher-prevalence northern regions.MethodsREACT-1 is a series of community surveys of SARS-CoV-2 RT-PCR swab-positivity in England, designed to monitor the spread of the epidemic and thus increase situational awareness. Round 7 of REACT-1 commenced swab-collection on 13th November 2020. A prior interim report included data from 13th to 24th November 2020 for 105,122 participants. Here, we report data for the entire round with swab results obtained up to 3rd December 2020.ResultsBetween 13th November and 3rd December (round 7) there were 1,299 positive swabs out of 168,181 giving a weighted prevalence of 0.94% (95% CI 0.87%, 1.01%) or 94 per 10,000 people infected in the community in England. This compares with a prevalence of 1.30% (1.21%, 1.39%) from 16th October to 2nd November 2020 (round 6), a decline of 28%. Prevalence during the latter half of round 7 was 0.91% (95% CI, 0.81%, 1.03%) compared with 0.96% (0.87%, 1.05%) in the first half. The national R number in round 7 was estimated at 0.96 (0.88, 1.03) with a decline in prevalence observed during the first half of this period no longer apparent during the second half at the end of lockdown. During round 7 there was a marked fall in prevalence in West Midlands, a levelling off in some regions and a rise in London. R numbers at regional level ranged from 0.60 (0.41, 0.80) in West Midlands up to 1.27 (1.04, 1.54) in London, where prevalence was highest in the east and south-east of the city. Nationally, between 13th November and 3rd December, the highest prevalence was in school-aged children especially at ages 13-17 years at 2.04% (1.69%, 2.46%), or approximately 1 in 50.ConclusionBetween the previous round and round 7 (during lockdown), there was a fall in prevalence of SARS-C

  • Journal article
    Orlovic M, Callender T, Riley J, Darzi A, Droney Jet al., 2020,

    Impact of advance care planning on dying in hospital: Evidence from urgent care records

    , PLoS One, Vol: 15, Pages: 1-12, ISSN: 1932-6203

    Place of death is an important outcome of end-of-life care. Many people do not have the opportunity to express their wishes and die in their preferred place of death. Advance care planning (ACP) involves discussion, decisions and documentation about how an individual contemplates their future death. Recording end-of-life preferences gives patients a sense of control over their future. Coordinate My Care (CMC) is London’s largest electronic palliative care register designed to provide effective ACP, with information being shared with urgent care providers. The aim of this study is to explore determinants of dying in hospital. Understanding advance plans and their outcomes can help in understanding the potential effects that implementation of electronic palliative care registers can have on the end-of-life care provided. Retrospective observational cohort analysis included 21,231 individuals aged 18 or older with a Coordinate My Care plan who had died between March 2011 and July 2019 with recorded place of death. Logistic regression was used to explore demographic and end-of-life preference factors associated with hospital deaths. 22% of individuals died in hospital and 73% have achieved preferred place of death. Demographic characteristics and end-of-life preferences have impact on dying in hospital, with the latter having the strongest influence. The likelihood of in-hospital death is substantially higher in patients without documented preferred place of death (OR = 1.43, 95% CI 1.26–1.62, p<0.001), in those who prefer to die in hospital (OR = 2.30, 95% CI 1.60–3.30, p<0.001) and who prefer to be cared in hospital (OR = 2.77, 95% CI 1.94–3.96, p<0.001). “Not for resuscitation” individuals (OR = 0.43, 95% CI 0.37–0.50, p<0.001) and who preferred symptomatic treatment (OR = 0.36, 95% CI 0.33–0.40, p<0.001) had a lower likelihood of in-hospital death. Effective advance care planning is necessary for improve

  • Journal article
    Joshi M, Ashrafian H, Khan S, Darzi Aet al., 2020,


    , The Lancet, Vol: 396, Pages: 1805-1805, ISSN: 0140-6736
  • Journal article
    Saracino A, Oude-Vrielink TJC, Menciassi A, Sinibaldi E, Mylonas GPet al., 2020,

    Haptic Intracorporeal Palpation Using a Cable-Driven Parallel Robot: A User Study

    , IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 67, Pages: 3452-3463, ISSN: 0018-9294

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=7&respub-action=search.html Current Millis: 1679421112858 Current Time: Tue Mar 21 17:51:52 GMT 2023