Emerging Technologies
in Healthcare
Knowledge and Library Services Evidence Update
Part of the Barts Health Education Academy
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Your monthly update on the latest emerging technologies in healthcare developments. Emerging tech can be described as any advanced technologies with the capacity to act as disrupters in their field or sector. Robotics and artificial intelligence are clearly such technologies, as well as machine learning, nanomedicine, deep learning, blockchain and others which are all increasingly impacting medicine and healthcare research and practice.
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News
NHS Digital appoints Simon Bolton as interim CEO.
NHS Digital has announced that Simon Bolton has been appointed as its interim CEO. Simon joins the organisation from Test and Trace, where he has been Chief Information Officer since August 2020.'
https://digital.nhs.uk/news-and-events/latest-news/nhs-digital-appoints-simon-bolton-as-interim-ceo
Trust goes live with EPMA
Grimsby hospital has today gone live with its electronic prescribing and medicines administration (EPMA) system on its Amethyst Ward and its Stroke Unit. The hospital becomes the third and final of Northern Lincolnshire and Goole NHS Foundation Trust’s EPMA programme, following the system going live at Goole hospital in October 2019, and Scunthorpe hospital in February 2020.
https://htn.co.uk/2021/05/18/grimsby-hospital-goes-live-with-epma/
Guy’s and St Thomas’ select new AI speech recognition tech for integration
"Guy’s and St Thomas’ NHS Foundation Trust has chosen Nuance Dragon Medical One’s AI-powered speech recognition technology for integration into its Epic electronic health record (EHR). The technology will form part of the trust’s Apollo Programme – a digital transformation strategy set to reshape the way in which the trust delivers patient care and how patients engage with their own health."
https://htn.co.uk/2021/04/28/guys-and-st-thomas-select-new-ai-speech-recognition-tech-for-integration/
Connecting healthcare with The Electronic Health Record Association
Hans Buitendijk, Chair of the Electronic Health Record Association Executive Committee, explains the benefits of digital healthcare for both patients and healthcare providers. The EHRA works collaboratively with other organisations and stakeholders to expand the benefits of electronic health records (EHRs) and health information technology.'
https://www.healtheuropa.eu/connecting-healthcare-electronic-health-record-association/107900/
Top 5 nightmares hiding in a healthcare organization's unstructured data
Healthcare IT News interview with Apoorv Agarwal the cofounder and CEO of Text IQ, a vendor of technology that uses artificial intelligence and machine learning to work with sensitive unstructured data. Here he describes five nightmares when it comes to what can be found in unstructured data and what healthcare provider organization CIOs and CISOs need to know.
https://www.healthcareitnews.com/news/top-five-nightmares-hiding-healthcare-organizations-unstructured-data
NICE’s Office for Digital Health offically open
The in-house team of advisors has been set up by the health technology assessment (HTA) agency to spearhead its policy on digital health technologies (DHTs) – including apps, programmes and software – which are already starting to transform health and social care delivery.
https://pharmaphorum.com/news/nices-office-for-digital-health-opens-its-doors-in-uk/
NHSX sets up RPA community of practice
NHSX has set up an online community of practice to encourage the adoption of robotic process automation (RPA) in health and social care
https://www.ukauthority.com/articles/nhsx-sets-up-rpa-community-of-practice/
EC regulation proposes laying down harmonised rules on artificial intelligence
The European Commission has published its proposal for a legal framework on AI described as "The combination of the first-ever legal framework on AI and a new Coordinated Plan with Member States will guarantee the safety and fundamental rights of people and businesses, while strengthening AI uptake, investment and innovation across the EU."
https://digital-strategy.ec.europa.eu/en/library/proposal-regulation-laying-down-harmonised-rules-artificial-intelligence
Building our future NHS digital workforce
Health Education England would like to work with digital, human resources (HR) and organisational leads in local or regional NHS organisations to address the capacity and capability challenges facing the NHS digital workforce in the next 10 years. The aim is to develop a set of national workforce plans for different segments of the digital technology workforce. The call for evidence is open for 6 weeks and closes on 13th June 2021, so click this link now to participate and get involved in the conversation.
https://nshcs.hee.nhs.uk/news/building-our-future-nhs-digital-workforce/
Virtual reality used for safeguarding training by NHS trust
An NHS Trust Hospital in Dartford, Darent Valley Hospital, is pioneering the use of virtual reality for their safeguarding training. Overseen by the Safeguarding Children’s Team, Antser VR is being used as a training and development resource for the hospital workforce.
https://www.med-technews.com/news/ai-and-vr-in-healthcare/virtual-reality-used-for-safeguarding-training-by-nhs-trust/
27 trusts to introduce app to support patients coping with Long COVID
The University of Leeds, Leeds Teaching Hospitals and Leeds Community Healthcare NHS Trusts, and digital health company ELAROS, have developed an app to support patients with Long COVID. Developed to enable patients to self-report their symptoms, the app will track the impact their symptoms are having on their daily living and their recovery.
https://htn.co.uk/2021/06/02/27-trusts-to-introduce-app-developed-to-support-patients-coping-with-long-covid/
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Events and Webinars
Full Digital Breakfast events launched by NHS Digital
Throughout 2021 -
The first in a series of digital breakfast events was launched by NHS Digital last week. The Full Digital Breakfast events will run throughout 2021 as an opportunity to discuss the many national digital products that have been developed in response to the COVID-19 pandemic. Events will take place on Microsoft Teams and are open to tech and data innovators - particularly Chief Information Officers (CIOs), Chief Clinical Information Officers (CCIOs) and Chief Technology Officers (CTOs).
https://digital.nhs.uk/news-and-events/latest-news/full-digital-breakfast-events
Supporting people to work in new ways: what have we learnt from the Covid-19 pandemic?
07 - 10 June 2021 - Catch up on demand until Sun 27 Jun, when the event closes
Virtual conference looking at examples of those changes and how people working in health and care have been working remotely, flexibly and in an agile way to meet the demands created by the pandemic and to develop new and improved ways of working for the future.'
https://www.kingsfund.org.uk/events/supporting-people-work-new-ways
Webinar: What should be the digital priorities for integrated care systems?
09 June 2021, 10.30am to 11.15am - Register to watch the webinar live, or for access to the on demand recording that will subsequently be made available
This HSJ webinar, run in association with Cisco, will bring together a small panel of experts to discuss issues concerning delivering of personalised care and what the digital priorities for ICS's should be and how digital infrastructure and solutions should underpin these within the organisational setting.
https://go.wilmingtonplc.com/HSJMarketingSolutions-CiscoMSwebinar-Registration.html
HTN NOW
14 - 17 June 2021 -
The HTN Now health tech tour continues in June, when we bring together the health tech community to share, discuss and collaborate on a variety of topics focused around health technology for the now. The sessions we host typically last up to one hour, providing practical advice, insight and learning from healthcare digital teams across the country. Tune in to hear about their approach, what they have done, what worked well, the challenges they face and what’s coming up next.
https://htn.co.uk/htn-now-june-2021/
Think big. Act now Series 1: Tackling the Patient Backlog
14 - 18 June 2021 Daily at 2pm -
This series aims to explore not just the key questions and themes relating to tackling the backlog, but the practical solutions on offer to help do so. What digital tools exist to support clinicians under pressure and patients waiting for treatment? How can established digital health companies help to restore services, prioritise patients, free-up staff time and reduce some of the unnecessary routine outpatient appointments?
https://hci.digital/news/think-big-act-now/
Health Tech Awards 2021
07 October 2021 -
The awards help to share and celebrate digital teams, programmes, innovations and health tech suppliers that have made a difference through the year. The awards provide a platform to share these innovations and solutions to help shape future services and systems across health and care. Got to https://htn.co.uk/health-tech-awards-2021/ for information on how to nominate and entry deadline dates.
https://htn.co.uk/health-tech-awards-2021/
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Reports
Digital Technology Adoption Depends on EHR Interoperability
"The NEJM Catalyst Insights Council sees great promise in emerging digital technologies for clinical care such as AI tools, but also many barriers, including lack of interoperability and lack of clinician buy-in."
Freely available online
https://catalyst.nejm.org/doi/full/10.1056/CAT.21.0142
2020-21: A year in the life of the NHS AI Lab
Review of the progress of the NHS AI Lab during 2020. The lab surveyed the UK’s AI community, compared the results of this survey with those from 2019 to inform on "the technologies that are being developed, the progress made, and the support needed to accelerate this."
Freely available online
https://www.nhsx.nhs.uk/ai-lab/about-the-nhs-ai-lab/2020-21-a-year-in-the-life-of-the-nhs-ai-lab/
10 practical lessons for implementing digital innovations - learning from the Care City test bed
Digital technology is often implemented as a ‘ready-made’ solution to many of the challenges facing the health and social care system with little consideration of the complexity of implementing digital health innovations. What’s more, guidance on how to best approach the implementation of innovations in health settings is scarce. As a result, many innovations are not embedded into care pathways effectively or adopted successfully. Identifying how to harness the benefits of digital technology will not only increase the chance of successful adoption, but also help to deliver the best care possible for patients, as well as deliver benefits for staff. This summary outlines 10 key lessons for the implementation, adoption, and spread of digital innovations in health and social care services. The lessons are designed to support policy makers, commissioners, innovators and service providers keen to integrate technology into health and social care services to successfully embed innovations into care pathways.'
Freely available online
https://www.nuffieldtrust.org.uk/research/10-practical-lessons-for-implementing-digital-innovations-learning-from-the-care-city-test-bed
Special Report: Electronic Document Management
Special report on the deployment of an Electronic Document Management System (EDMS) to support virtual outpatients at London North-West University Healthcare NHS Trust during the start of the COVID-19 pandemic
Freely available online
https://www.digitalhealth.net/2021/06/special-report-electronic-document-management-8/
An introduction to Research for Parliament 2021
Horizon scanning publication from the Parliamentary Office of Science and Technology (POST) identifying 30 areas of change to help the UK Parliament prepare for the future. One of the technological advances they identify are 'Developments in the diagnosis of disease for medicine and public health' this report looks at the benefits that technological advances in diagnostic tools could bring balanced against issues concerning patient trust, adequate staff training, consideration of the ethical aspects of these new technologies and equity of access.
Freely available online
https://post.parliament.uk/research-for-parliament-2021/
LSE–Lancet Commission on the future of the NHS: re-laying the foundations for an equitable and efficient health and care service after COVID-19
The Lancet and the London School of Economics (LSE) recently published a report on its joint-commission, whichwas established to independently evaluate the NHS. Launched in 2018 the commsision focused on a number of key areas including digital health and IT and digital technology. The digital health paper 'Health information technology and digital innovation for national learning health and care systems' reports the commissions findings.
Freely available online
https://www.thelancet.com/commissions/future-NHS
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Remote Learning
Undertaking a high stakes virtual OSCE (“VOSCE”) during Covid-19
"The Covid pandemic and associated lockdown forced medical schools globally not only to deliver emergency remote teaching, but to consider alternative methods of high stakes assessment. Here we outline our approach to the resit virtual OSCE (“VOSCE”) for final year medical students that we undertook during “lockdown” in the current pandemic."
BMC Med Educ 21, 221 (2021). doi.org/10.1186/s12909-021-02660-5
Machine Learning
Machine learning in clinical decision making
Machine learning is increasingly integrated into clinical practice, with applications ranging from pre-clinical data processing, bedside diagnosis assistance, patient stratification, treatment decision making, and early warning as part of primary and secondary prevention. However, a multitude of technological, medical, and ethical considerations are critical in machine-learning utilization, including the necessity for careful validation of machine-learning-based technologies in real-life contexts, unbiased evaluation of benefits and risks, and avoidance of technological over-dependence and associated loss of clinical, ethical, and social-related decision-making capacities. Other challenges include the need for careful benchmarking and external validations, dissemination of end-user knowledge from computational experts to field users, and responsible code and data sharing, enabling transparent assessment of pipelines. In this review, we highlight key promises and achievements in integration of machine-learning platforms into clinical medicine while highlighting limitations, pitfalls, and challenges toward enhanced integration of learning systems into the medical realm.
Med (2021), doi.org/10.1016/j.medj.2021.04.006
Telehealth
Best Practices for Integrating Medical Students Into Telehealth Visits
Telehealth has become an increasingly important part of health care delivery, with a dramatic rise in telehealth visits during the COVID-19 pandemic. Telehealth visits will continue to be a part of care delivery after the pandemic subsides, and it is important that medical students receive training in telehealth skills to meet emerging telehealth competencies. This paper describes strategies for successfully integrating medical students into telehealth visits in the ambulatory setting based on existing literature and the extensive experience of the authors teaching and learning in the telehealth environment.'
JMIR Med Educ 2021;7(2):e27877 doi:10.2196/27877
Artifical Intelligence
Deconstructing Canada’s efforts to integrate artificial intelligence in medicine and medical education
Artificial intelligence (AI) has gained momentum in the last decade in various professional domains, but its usage remains scarce in the field of medicine. Available AI-enhanced devices are not integrated in a consistent fashion throughout Canadian health facilities, and current medical practitioners and students are not well prepared for AI’s impact on their careers. Undergraduate medical students lack fundamental knowledge of AI in medicine, from its impact on patient care and its potential as an adjunct decision-making tool, to the general fundamentals of how AI-enhanced devices work. Currently, postgraduates don’t have access to AI-enhanced devices; this could potentially limit their understanding of how these devices might affect their future clinical practice. Canadian medical universities can play a critical role in familiarizing students with these new devices. Incorporating new topics into the already heavily charged medical curricula may be challenging, but students could make use of extracurricular activities to learn the concept of AI and strengthen interdisciplinary collaboration. Educational institutions would also need to propose policies for the safe and ethical use of devices in classrooms or internships. However, they might require guidance to draft new policies targeting AI in medical education. Canadian medical associations could take the lead to draft AI policies in healthcare to guide the equal and safe implementation of AI-enhanced devices across the Canadian medical community. Our paper will explore the work that has been done related to AI-specific policies in healthcare, focusing on Canada, and provide key points that could be used to organize future policies.
McGill Journal of Medicine. Montreal, Canada, 19(1). doi: 10.26443/mjm.v19i1.871.
Blockchain
A Scoping Review of Integrated Blockchain-Cloud (BcC) Architecture for Healthcare: Applications, Challenges and Solutions
Blockchain is a disruptive technology for shaping the next era of a healthcare system striving for efficient and effective patient care. This is thanks to its peer-to-peer, secure, and transparent characteristics. On the other hand, cloud computing made its way into the healthcare system thanks to its elasticity and cost-efficiency nature. However, cloud-based systems fail to provide a secured and private patient-centric cohesive view to multiple healthcare stakeholders. In this situation, blockchain provides solutions to address security and privacy concerns of the cloud because of its decentralization feature combined with data security and privacy, while cloud provides solutions to the blockchain scalability and efficiency challenges. Therefore a novel paradigm of blockchain-cloud integration (BcC) emerges for the domain of healthcare. In this paper, we provide an in-depth analysis of the BcC integration for the healthcare system to give the readers the motivations behind the emergence of this new paradigm, introduce a classification of existing architectures and their applications for better healthcare. We then review the development platforms and services and highlight the research challenges for the integrated BcC architecture, possible solutions, and future research directions. The results of this paper will be useful for the healthcare industry to design and develop a data management system for better patient care.
Sensors (Basel). 2021 May 28;21(11):3753. doi.org/10.3390/s21113753
Robotics
Robot-Assisted Autism Therapy (RAAT). Criteria and Types of Experiments Using Anthropomorphic and Zoomorphic Robots. Review of the Research
Supporting the development of a child with autism is a multi-profile therapeutic work on disturbed areas, especially understanding and linguistic expression used in social communication and development of social contacts. Previous studies show that it is possible to perform some therapy using a robot. This article is a synthesis review of the literature on research with the use of robots in the therapy of children with the diagnosis of early childhood autism. The review includes scientific journals from 2005-2021. Using descriptors: ASD (Autism Spectrum Disorders), Social robots, and Robot-based interventions, an analysis of available research in PubMed, Scopus and Web of Science was done. The results showed that a robot seems to be a great tool that encourages contact and involvement in joint activities. The review of the literature indicates the potential value of the use of robots in the therapy of people with autism as a facilitator in social contacts. Robot-Assisted Autism Therapy (RAAT) can encourage child to talk or do exercises. In the second aspect (prompting during a conversation), a robot encourages eye contact and suggests possible answers, e.g., during free conversation with a peer. In the third aspect (teaching, entertainment), the robot could play with autistic children in games supporting the development of joint attention. These types of games stimulate the development of motor skills and orientation in the body schema. In future work, a validation test would be desirable to check whether children with ASD are able to do the same with a real person by learning distrust and cheating the robot.
Sensors (Basel). 2021 May 27;21(11):3720. doi.org/10.3390/s21113720
Robotics
Very Early Robot-Assisted Mobilization of Intensive Care Patients - A Scoping Review
This scoping review gives an overview of current research activities in the field of very early mobilization with robotic devices of intensive care patients. It presents the effect of very early, robot-assisted mobilization on intensive care patients based on their outcomes.
Stud Health Technol Inform. 2021 May 27;281:1073-1074. doi.org/10.3233/shti210350
EHR
Consolidated EHR Workflow for Endoscopy Quality Reporting
Although colonoscopy is the most frequently performed endoscopic procedure, the lack of standardized reporting is impeding clinical and translational research. Inadequacies in data extraction from the raw, unstructured text in electronic health records (EHR) pose an additional challenge to procedure quality metric reporting, as vital details related to the procedure are stored in disparate documents. Currently, there is no EHR workflow that links these documents to the specific colonoscopy procedure, making the process of data extraction error prone. We hypothesize that extracting comprehensive colonoscopy quality metrics from consolidated procedure documents using computational linguistic techniques, and integrating it with discrete EHR data can improve quality of screening and cancer detection rate. As a first step, we developed an algorithm that links colonoscopy, pathology and imaging documents by analyzing the chronology of various orders placed relative to the colonoscopy procedure. The algorithm was installed and validated at the University of Arkansas for Medical Sciences (UAMS). The proposed algorithm in conjunction with Natural Language Processing (NLP) techniques can overcome current limitations of manual data abstraction.
Stud Health Technol Inform. 2021 May 27;281:427-431. doi.org/10.3233/shti210194
Deep Learning
Deep Learning Methods to Predict Mortality in COVID-19 Patients: A Rapid Scoping Review
The ongoing COVID-19 pandemic has become the most impactful pandemic of the past century. The SARS-CoV-2 virus has spread rapidly across the globe affecting and straining global health systems. More than 2 million people have died from COVID-19 (as of 30 January 2021). To lessen the pandemic's impact, advanced methods such as Artificial Intelligence models are proposed to predict mortality, morbidity, disease severity, and other outcomes and sequelae. We performed a rapid scoping literature review to identify the deep learning techniques that have been applied to predict hospital mortality in COVID-19 patients. Our review findings provide insights on the important deep learning models, data types, and features that have been reported in the literature. These summary findings will help scientists build reliable and accurate models for better intervention strategies for predicting mortality in current and future pandemic situations.
Stud Health Technol Inform. 2021 May 27;281:799-803. doi.org/10.3233/shti210285
Artifical Intelligence
Addressing Biodisaster X Threats With Artificial Intelligence and 6G Technologies: Literature Review and Critical Insights
With advances in science and technology, biotechnology is becoming more accessible to people of all demographics. These advances inevitably hold the promise to improve personal and population well-being and welfare substantially. It is paradoxical that while greater access to biotechnology on a population level has many advantages, it may also increase the likelihood and frequency of biodisasters due to accidental or malicious use. Similar to "Disease X" (describing unknown naturally emerging pathogenic diseases with a pandemic potential), we term this unknown risk from biotechnologies "Biodisaster X." To date, no studies have examined the potential role of information technologies in preventing and mitigating Biodisaster X.
J Med Internet Res. 2021 May 25;23(5):e26109. doi.org/10.2196/26109
Robotics
Friends from the Future: A Scoping Review of Research into Robots and Computer Agents to Combat Loneliness in Older People
Loneliness is a common problem in older adults and contributes to poor health. This scoping review aimed to synthesize and report evidence on the effectiveness of interventions using social robots or computer agents to reduce loneliness in older adults and to explore intervention strategies.
Clin Interv Aging. 2021 May 24;16:941-971. doi.org/10.2147/cia.s282709
Artifical Intelligence
Artificial Intelligence for Clinical Decision Support in Sepsis
Sepsis is one of the main causes of death in critically ill patients. Despite the continuous development of medical technology in recent years, its morbidity and mortality are still high. This is mainly related to the delay in starting treatment and non-adherence of clinical guidelines. Artificial intelligence (AI) is an evolving field in medicine, which has been used to develop a variety of innovative Clinical Decision Support Systems. It has shown great potential in predicting the clinical condition of patients and assisting in clinical decision-making. AI-derived algorithms can be applied to multiple stages of sepsis, such as early prediction, prognosis assessment, mortality prediction, and optimal management. This review describes the latest literature on AI for clinical decision support in sepsis, and outlines the application of AI in the prediction, diagnosis, subphenotyping, prognosis assessment, and clinical management of sepsis. In addition, we discussed the challenges of implementing and accepting this non-traditional methodology for clinical purposes.
Front Med (Lausanne). 2021 May 13;8:665464. doi.org/10.3389/fmed.2021.665464
Robotics
Dental Robotics: A Disruptive Technology
Robotics is a disruptive technology that will change diagnostics and treatment protocols in dental medicine. Robots can perform repeated workflows for an indefinite length of time while enhancing the overall quality and quantity of patient care. Early robots required a human operator, but robotic systems have advanced significantly over the past decade, and the latest medical robots can perform patient intervention or remote monitoring autonomously. However, little research data on the therapeutic reliability and precision of autonomous robots are available. The present paper reviews the promise and practice of robots in dentistry by evaluating published work on commercial robot systems in dental implantology, oral and maxillofacial surgery, prosthetic and restorative dentistry, endodontics, orthodontics, oral radiology as well as dental education. In conclusion, this review critically addresses the current limitations of dental robotics and anticipates the potential future impact on oral healthcare and the dental profession.
Sensors (Basel). 2021 May 11;21(10):3308. doi.org/10.3390/s21103308
Virtual Reality
A systematic review of the use of virtual reality or dental smartphone applications as interventions for management of paediatric dental anxiety
Virtual reality (VR) has been used successfully in medicine both as a distraction tool during procedures, and as an acclimatisation tool to prepare for a procedure or experience. It has not yet become widely used in dentistry, but could theoretically have a role in exposure-based acclimatisation for dental experiences.
BMC Oral Health. 2021 May 7;21(1):244. doi.org/10.1186/s12903-021-01602-3
Artifical Intelligence
Reporting guidelines for artificial intelligence in healthcare research
Reporting guidelines are structured tools developed using explicit methodology that specify the minimum information required by researchers when reporting a study. The use of artificial intelligence (AI) reporting guidelines that address potential sources of bias specific to studies involving AI interventions has the potential to improve the quality of AI studies, through improvements in their design and delivery, and the completeness and transparency of their reporting. With a number of guidance documents relating to AI studies emerging from different specialist societies, this Review article provides researchers with some key principles for selecting the most appropriate reporting guidelines for a study involving an AI intervention. As the main determinants of a high-quality study are contained within the methodology of the study design rather than the intervention, researchers are recommended to use reporting guidelines that are specific to the study design, and then supplement them with AI-specific guidance contained within available AI reporting guidelines.
Clin Exp Ophthalmol. 2021 May 6. doi.org/10.1111/ceo.13943
Machine Learning, NLP
Machine Learning and Natural Language Processing in Mental Health: Systematic Review
Machine learning systems are part of the field of artificial intelligence that automatically learn models from data to make better decisions. Natural language processing (NLP), by using corpora and learning approaches, provides good performance in statistical tasks, such as text classification or sentiment mining.
J Med Internet Res. 2021 May 4;23(5):e15708. doi.org/10.2196/15708
Nanomedicine
Nanomedicine Approach to Immunotherapy of Hepatocellular Carcinoma
In recent years, the growing studies focused on the immunotherapy of hepatocellular carcinoma and proved the preclinical and clinical promises of host antitumor immune response. However, there were still various obstacles in meeting satisfactory clinic need, such as low response rate, primary resistance and secondary resistance to immunotherapy. Tackling these barriers required a deeper understanding of immune underpinnings and a broader understanding of advanced technology. This review described immune microenvironment of liver and HCC which naturally decided the complexity of immunotherapy, and summarized recent immunotherapy focusing on different points. The ever-growing clues indicated that the instant killing of tumor cell and the subsequent relive of immunosuppressive microenvironment were both indis- pensables. The nanotechnology applied in immunotherapy and the combination with intervention technology was also discussed.
J Biomed Nanotechnol. 2021 May 1;17(5):771-792. doi.org/10.1166/jbn.2021.3055
NLP
Natural Language Processing in Surgery: A Systematic Review and Meta-analysis
The aim of this study was to systematically assess the application and potential benefits of natural language processing (NLP) in surgical outcomes research.|Summary background data: Widespread implementation of electronic health records (EHRs) has generated a massive patient data source. Traditional methods of data capture, such as billing codes and/or manual review of free-text narratives in EHRs, are highly labor-intensive, costly, subjective, and potentially prone to bias.
Ann Surg. 2021 May 1;273(5):900-908. doi.org/10.1097/sla.0000000000004419
Robotics
Simulation-Based Training in Robotic Surgery: Contemporary and Future Methods
While robotic surgery has grown in popularity and scope over the past decade, there is a persistent need for simulation-based training as surgeons adapt from the working at the bedside to the immersive and multisensory tasks at the console. From dry laboratory to virtual reality (VR) environments, simulation can be used to train surgeons in basic tasks, complex operative steps, and coordination of whole operations with members of the entire operating room (OR) staff. By integrating simulation into mentored training programs, surgeons can reduce the number of cases required to master a complex operation. Future VR based simulation will become essential to the adaptation of the surgical workforce to new technologies and adoption of emerging robotic platforms. Ultimately, robotic simulation will set standards for credentialing of new surgeons.
J Laparoendosc Adv Surg Tech A . 2021 May;31(5):556-560. doi.org/10.1089/lap.2021.0082
Machine Learning
Machine Learning Solutions for Osteoporosis-A Review
Osteoporosis and its clinical consequence, bone fracture, is a multifactorial disease that has been the object of extensive research. Recent advances in machine learning (ML) have enabled the field of artificial intelligence (AI) to make impressive breakthroughs in complex data environments where human capacity to identify high-dimensional relationships is limited. The field of osteoporosis is one such domain, notwithstanding technical and clinical concerns regarding the application of ML methods. This qualitative review is intended to outline some of these concerns and to inform stakeholders interested in applying AI for improved management of osteoporosis. A systemic search in PubMed and Web of Science resulted in 89 studies for inclusion in the review. These covered one or more of four main areas in osteoporosis management: bone properties assessment (n = 13), osteoporosis classification (n = 34), fracture detection (n = 32), and risk prediction (n = 14). Reporting and methodological quality was determined by means of a 12-point checklist. In general, the studies were of moderate quality with a wide range (mode score 6, range 2 to 11). Major limitations were identified in a significant number of studies. Incomplete reporting, especially over model selection, inadequate splitting of data, and the low proportion of studies with external validation were among the most frequent problems. However, the use of images for opportunistic osteoporosis diagnosis or fracture detection emerged as a promising approach and one of the main contributions that ML could bring to the osteoporosis field. Efforts to develop ML-based models for identifying novel fracture risk factors and improving fracture prediction are additional promising lines of research. Some studies also offered insights into the potential for model-based decision-making. Finally, to avoid some of the common pitfalls, the use of standardized checklists in developing and sharing the results of ML models should be encouraged. © 2021 American Society for Bone and Mineral Research (ASBMR).
J Bone Miner Res. 2021 May;36(5):833-851. doi.org/10.1002/jbmr.4292
Nanotechnology
Nanotechnology, and scaffold implantation for the effective repair of injured organs: An overview on hard tissue engineering
The tissue engineering of hard organs and tissues containing cartilage, teeth, and bones is a widely used and rapidly progressing field. One of the main features of hard organs and tissues is the mineralization of their extracellular matrices (ECM) to enable them to withstand pressure and weight. Recently, a variety of printing strategies have been developed to facilitate hard organ and tissue regeneration. Fundamentals in three-dimensional (3D) printing techniques are rapid prototyping, additive manufacturing, and layered built-up and solid-free construction. This strategy promises to replicate the multifaceted architecture of natural tissues. Nowadays, 3D bioprinting techniques have proved their potential applications in tissue engineering to construct transplantable hard organs/tissues including bone and cartilage. Though, 3D bioprinting methods still have some uncertainties to fabricate 3D hard organs/tissues. In the present review, most advanced technical improvements, experiments, and future outlooks of hard tissue engineering are discussed, as well as their relevant additive manufacturing techniques.
J Control Release . 2021 May 10;333:391-417. doi.org/10.1016/j.jconrel.2021.04.003
Virtual Reality
Virtual Reality Exergames for Improving Older Adults' Cognition and Depression: A Systematic Review and Meta-Analysis of Randomized Control Trials
Virtual reality (VR) exergames are an innovative approach to promote older adults' mental health. VR exergames are active video games controlled by bodily movements in a safe surrounding with advantages of physical activity engagement and inter. The purpose of this study was to explore the effectiveness of VR exergames in improving older adults' cognition and ameliorating depressive outcome by a systematic review, meta-analysis, subgroup analysis, and meta-regression.
J Am Med Dir Assoc. 2021 May;22(5):995-1002. doi.org/10.1016/j.jamda.2021.03.009
Virtual Reality, Augmented Reality
Virtual and Augmented Reality Enhancements to Medical and Science Student Physiology and Anatomy Test Performance: A Systematic Review and Meta-Analysis
Virtual and augmented reality have seen increasing employment for teaching within medical and health sciences programs. For disciplines such as physiology and anatomy, these technologies may disrupt the traditional modes of teaching and content delivery. The objective of this systematic review and meta-analysis is to evaluate the impact of virtual reality or augmented reality on knowledge acquisition for students studying preclinical physiology and anatomy. The protocol was submitted to Prospero and literature search undertaken in PubMed, Embase, ERIC, and other databases. Citations were reviewed and articles published in full assessing learning or knowledge acquisition in preclinical physiology and anatomy from virtual or augmented reality were included. Of the 919 records found, 58 eligible articles were reviewed in full-text, with 8 studies meeting full eligibility requirements. There was no significant difference in knowledge scores from combining the eight studies (626 participants), with the pooled difference being a non-significant increase of 2.9 percentage points (95% CI [-2.9; 8.6]). For the four studies comparing virtual reality to traditional teaching, the pooled treatment effect difference was 5.8 percentage points (95% CI [-4.1; 15.7]). For the five studies comparing augmented reality to traditional teaching, the pooled treatment effect difference was 0.07 (95% CI [-7.0; 7.2]). Upon review of the literature, it is apparent that educators could benefit from adopting assessment processes that evaluate three-dimensional spatial understanding as a priority in physiology and anatomy. The overall evidence suggests that although test performance is not significantly enhanced with either mode, both virtual and augmented reality are viable alternatives to traditional methods of education in health sciences and medical courses.
Anat Sci Educ. 2021 May;14(3):368-376. doi.org/10.1002/ase.2049
EHR
Electronic health record usability and workload changes over time for provider and nursing staff following transition to new EHR
The ubiquity of EHRs in healthcare means that small EHR inefficiencies can have a major impact on clinician workload. We conducted a sequential explanatory mixed methods study to: 1) identify EHR-associated workload and usability effects for clinicians following an EHR change over time, 2) determine workload and usability differences for providers (MD and Advance Practice Nurses) versus nurses (RNs and MAs), 3) determine if usability predicts workload, 4) identify potential sources of EHR design flaws. Workload (NASA-Task Load Index) and usability (System Usability Scale) measures were administered pre, 6-8 month and 30-32 months post-implementation. We found significant increase in perceived workload post-implementation that persisted for 2.5 years (p < .001). The workload increase was associated with usability ratings, which in turn may relate to EHR interface design violations identified by a heuristic evaluation. Our findings suggest further innovation and attention to interface design flaws are needed to improve EHR usability and reduce clinician workload.
Appl Ergon. 2021 May;93:103359. doi.org/10.1016/j.apergo.2021.103359
Nanomedicine
Toward nanobioelectronic medicine: Unlocking new applications using nanotechnology
Bioelectronic medicine aims to interface electronic technology with biological components and design more effective therapeutic and diagnostic tools. Advances in nanotechnology have moved the field forward improving the seamless interaction between biological and electronic components. In the lab many of these nanobioelectronic devices have the potential to improve current treatment approaches, including those for cancer, cardiovascular disorders, and disease underpinned by malfunctions in neuronal electrical communication. While promising, many of these devices and technologies require further development before they can be successfully applied in a clinical setting. Here, we highlight recent work which is close to achieving this goal, including discussion of nanoparticles, carbon nanotubes, and nanowires for medical applications. We also look forward toward the next decade to determine how current developments in nanotechnology could shape the growing field of bioelectronic medicine.
Wiley Interdiscip Rev Nanomed Nanobiotechnol. 2021 May;13(3):e1693. doi.org/10.1002/wnan.1693
Nanomedicine
Targeted nanomedicines for the treatment of bone disease and regeneration
Targeted delivery by either passive or active targeting of therapeutics to the bone is an attractive treatment for various bone related diseases such as osteoporosis, osteosarcoma, multiple myeloma, and metastatic bone tumors. Engineering novel drug delivery carriers can increase therapeutic efficacy and minimize the risk of side effects. Developmnet of nanocarrier delivery systems is an interesting field of ongoing studies with opportunities to provide more effective therapies. In addition, preclinical nanomedicine research can open new opportunities for preclinical bone-targeted drug delivery; nevertheless, further research is needed to progress these therapies towards clinical applications. In the present review, the latest advancements in targeting moieties and nanocarrier drug delivery systems for the treatment of bone diseases are summarized. We also review the regeneration capability and effective delivery of nanomedicines for orthopedic applications.
Med Res Rev. 2021 May;41(3):1221-1254. doi.org/10.1002/med.21759
Robotics
Progress and Roadmap for Intelligent Self-Healing Materials in Autonomous Robotics
Robots are increasingly assisting humans in performing various tasks. Like special agents with elite skills, they can venture to distant locations and adverse environments, such as the deep sea and outer space. Micro/nanobots can also act as intrabody agents for healthcare applications. Self-healing materials that can autonomously perform repair functions are useful to address the unpredictability of the environment and the increasing drive toward the autonomous operation. Having self-healable robotic materials can potentially reduce costs, electronic wastes, and improve a robot endowed with such materials longevity. This review aims to serve as a roadmap driven by past advances and inspire future cross-disciplinary research in robotic materials and electronics. By first charting the history of self-healing materials, new avenues are provided to classify the various self-healing materials proposed over several decades. The materials and strategies for self-healing in robotics and stretchable electronics are also reviewed and discussed. It is believed that this article encourages further innovation in this exciting and emerging branch in robotics interfacing with material science and electronics.
Adv Mater. 2021 May;33(19):e2002800. doi.org/10.1002/adma.202002800
Robotics
Recent Progress in Artificial Muscles for Interactive Soft Robotics
Artificial muscles are the core components of the smart and interactive soft robotic systems, providing the capabilities in shape morphing, manipulation, and mobility. Intense research efforts in the development of artificial muscles are based on the dielectric elastomer actuators, pneumatic actuators, electrochemical actuators, soft magnetic actuators, and stimulus responsive polymers. Recent progress has presented artificial muscles with impressive specific power output exceeding that of the natural muscles, dexterous shape morphing behavior that can be programmed and reconfigured, and exceptional high maneuverability to traverse surfaces with obstacles and different textures. Here, a succinct and critical summary is provided on the materials and strategies that have contributed to the important advancement of the artificial muscles in recent research. On that basis, the exciting opportunities are discussed in the integration of soft electronic devices with artificial muscles to enable smart and interactive soft robotic systems.
Adv Mater. 2021 May;33(19):e2003088. doi.org/10.1002/adma.202003088
Robotics
Nonobstetrical Robotic-Assisted Laparoscopic Surgery in Pregnancy: A Systematic Literature Review
Urologic and gynecologic surgeons are the top utilizers of robotic surgery; however, nonobstetrical robotic-assisted laparoscopic surgery (RALS) in pregnant patients is infrequent. A systematic literature review was performed to ascertain the frequency, indication and complications of RALS in pregnancy. Results showed 38 pregnancies from eleven publications between 2008 and 2020. Five cases were for urologic indication and 33 for gynecologic indication. Minimal surgical alterations were required. Although no adverse maternal-fetal outcomes were reported, there are not enough cases published to determine safety. This review demonstrates the feasibility of RALS for the pregnant population in the hands of competent robotic surgeons.
Urology. 2021 May;151:58-66. doi.org/10.1016/j.urology.2020.05.017
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