Browse through all publications from the Institute of Global Health Innovation, which our Patient Safety Research Collaboration is part of. This feed includes reports and research papers from our Centre. 

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  • Conference paper
    Zhao M, Oude Vrielink J, Kogkas A, Mylonas G, Elson Det al., 2019,

    Prototype Designs of a Cable-driven Parallel Robot for Transoral Laser Surgery

    , Hamlyn Symposium on Medical Robotics
  • Conference paper
    Leiloglou M, Chalau V, Kedrzycki M, Qi J, Martin-Gonzalez P, Hanna G, Darzi A, Leff D, Elson Det al., 2019,

    Fluorescence Intensity Image Guided Breast Conserving Surgery (BCS).

    , European Molecular Imaging Meeting
  • Conference paper
    Achanccaray D, Mylonas G, Andreu-Perez J, 2019,

    An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapy

    , IEEE International Conference on Systems, Man and Cybernetics (SMC), Publisher: IEEE, Pages: 2829-2832, ISSN: 1062-922X
  • Book chapter
    Kogkas A, Ezzat A, Thakkar R, Darzi A, Mylonas Get al., 2019,

    Free-View, 3D Gaze-Guided Robotic Scrub Nurse

    , Editors: Shen, Liu, Peters, Staib, Essert, Zhou, Yap, Khan, Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 164-172, ISBN: 978-3-030-32253-3
  • Journal article
    Clarke JM, Warren LR, Arora S, Barahona M, Darzi AWet al., 2018,

    Guiding interoperable electronic health records through patient-sharing networks.

    , NPJ digital medicine, Vol: 1, Pages: 65-65, ISSN: 2398-6352

    Effective sharing of clinical information between care providers is a critical component of a safe, efficient health system. National data-sharing systems may be costly, politically contentious and do not reflect local patterns of care delivery. This study examines hospital attendances in England from 2013 to 2015 to identify instances of patient sharing between hospitals. Of 19.6 million patients receiving care from 155 hospital care providers, 130 million presentations were identified. On 14.7 million occasions (12%), patients attended a different hospital to the one they attended on their previous interaction. A network of hospitals was constructed based on the frequency of patient sharing between hospitals which was partitioned using the Louvain algorithm into ten distinct data-sharing communities, improving the continuity of data sharing in such instances from 0 to 65-95%. Locally implemented data-sharing communities of hospitals may achieve effective accessibility of clinical information without a large-scale national interoperable information system.

  • Journal article
    Ahmed Z, Jani Y, Franklin BD, 2018,

    Qualitative study exploring the phenomenon of multiple electronic prescribing systems within single hospital organisations

    , BMC HEALTH SERVICES RESEARCH, Vol: 18, ISSN: 1472-6963
  • Journal article
    Alsaidan J, Portlock J, Aljadhey HS, Shebl NA, Franklin BDet al., 2018,

    Systematic review of the safety of medication use in inpatient, outpatient and primary care settings in the Gulf Cooperation Council countries

    , SAUDI PHARMACEUTICAL JOURNAL, Vol: 26, Pages: 977-1011, ISSN: 1319-0164
  • Journal article
    Flott K, Nelson D, Moorcroft T, Mayer EK, Gage W, Redhead J, Darzi AWet al., 2018,

    Enhancing safety culture through improved incident reporting: A case study in translational research

    , Health Affairs, Vol: 37, Pages: 1797-1804, ISSN: 0278-2715

    The Imperial College Healthcare National Health Service Trust, a large health care provider in London, together with an academic research unit, used a learning health systems cycle of interventions. The goals were to improve patient safety incident reporting and learning and shape a more just organizational safety culture. Following a phase of feedback gathering from front-line staff, seven evidence-based interventions were implemented and evaluated from October 2016 to August 2018. Indicators of safety culture, incident reporting rates, and reported rates of harm to patients and "never events" (events that should not happen in medical practice) were continuously monitored. In this article we report on this initiative, including its early results. We observed improvement on some measures of safety culture and incident reporting rates. Staff members' perceptions of six of the seven interventions were positive. The intervention exercise demonstrated the importance of health care policies in supporting local ownership of safety culture and encouraging the application of rigorous research standards.

  • Journal article
    Lyons I, Furniss D, Blandford A, Chumbley G, Iacovides I, Wei L, Cox A, Mayer A, Vos J, Galal-Edeen GH, Schnock KO, Dykes PC, Bates DW, Franklin BDet al., 2018,

    Errors and discrepancies in the administration of intravenous infusions: a mixed methods multihospital observational study

    , BMJ QUALITY & SAFETY, Vol: 27, Pages: 892-901, ISSN: 2044-5415
  • Journal article
    Rao AM, Bottle A, Bicknell C, Darzi A, Aylin Pet al., 2018,

    Trajectory modelling to assess trends in long-term readmission rate among abdominal aortic aneurysm patients

    , Surgery Research and Practice, Vol: 2018, ISSN: 2356-7759

    Introduction. The aim of the study was to use trajectory analysis to categorise high-impact users based on their long-term readmission rate and identify their predictors following AAA (abdominal aortic aneurysm) repair. Methods. In this retrospective cohort study, group-based trajectory modelling (GBTM) was performed on the patient cohort (2006-2009) identified through national administrative data from all NHS English hospitals. Proc Traj software was used in SAS program to conduct GBTM, which classified patient population into groups based on their annual readmission rates during a 5-year period following primary AAA repair. Based on the trends of readmission rates, patients were classified into low- and high-impact users. The high-impact group had a higher annual readmission rate throughout 5-year follow-up. Short-term high-impact users had initial high readmission rate followed by rapid decline, whereas chronic high-impact users continued to have high readmission rate. Results. Based on the trends in readmission rates, GBTM classified elective AAA repair () patients into 2 groups: low impact (82.0%) and high impact (18.0%). High-impact users were significantly associated with female sex () undergoing other vascular procedures (), poor socioeconomic status index (), older age (), and higher comorbidity score (). The AUC for c-statistics was 0.84. Patients with ruptured AAA repair () had 3 groups: low impact (82.7%), short-term high impact (7.2%), and chronic high impact (10.1%). Chronic high impact users were significantly associated with renal failure (), heart failure (P = 0.01), peripheral vascular disease (), female sex (P = 0.02), open repair (), and undergoing other related procedures (). The AUC for c-statistics was 0.71. Conclusion. Patients with persistent high readmission rates exist among AAA population; however, their readmissions and mortality are not related to AAA repair. They may benefit from optimization of their medical management of comorbiditie

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