{"id":215282,"date":"2017-03-11T15:43:40","date_gmt":"2017-03-11T20:43:40","guid":{"rendered":"http:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/uncategorized\/can-artificial-intelligence-save-the-nhs-itproportal.php"},"modified":"2017-03-11T15:43:40","modified_gmt":"2017-03-11T20:43:40","slug":"can-artificial-intelligence-save-the-nhs-itproportal","status":"publish","type":"post","link":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/artificial-intelligence\/can-artificial-intelligence-save-the-nhs-itproportal.php","title":{"rendered":"Can artificial intelligence save the NHS? &#8211; ITProPortal"},"content":{"rendered":"<p><p>    According to the Office for Budget Responsibility, the NHS    budget will need to increase by 88billion over the next 50    years if it is to keep pace with the rising demand for    healthcare in the UK. But with the 2017 Budget showcasing a    massive leaning towards building up its Brexit reserves and    allocating a mere 100 million for 100 onsite GP treatment    centres in A&Es across England, the NHS is justifiably    bracing itself for a painful future.  <\/p>\n<p>    With 20billion worth of cuts scheduled by 2020, combined with    fierce warnings that the UKs health services are on the edge    of an unprecedented crisis, the urgent call for solutions to be    brought to the healthcare table has incontrovertibly    intensified.  <\/p>\n<p>    With deep cuts looming, its time to properly consider how    Artificial Intelligence can answer this call and shed light on    how its technologies could provide the healthcare industry with    some much-needed respite and real solutions to meet the ever    spiralling rise in demand for healthcare.  <\/p>\n<p>    The issue of voluminous data that draws relentlessly on    healthcare professionals resources is something that could    benefit significantly from the implementation of an AI-based    system.  <\/p>\n<p>    It has been estimated that it would take at least 160 hours of    reading a week just to keep up with new medical knowledge as    it's published, let alone consider its relevance. It soon    becomes apparent then, that it would be physically impossible    for a doctor to be able to process all of the patient    information as well as digest insight from new materials and    medical journals, and still be able to treat patients.  <\/p>\n<p>    Imagine a scenario wherein supercomputers could process the    information  and far more efficiently, too  making sense of    the sheer quantity of data, flagging any relevant information    to the doctors and nurses that might be pertinent to a    patients case, and providing them with access to    up-to-the-minute and highly applicable insight in the field.  <\/p>\n<p>    Such an AI system would effectively unshackle medical    professionals from these time-consuming processes, freeing them    up to focus on work that requires human skills. Contrary to    popular belief that AI will result in mass job losses, the    implementation of AI systems in this instance would actually    augment the roles and skills of the human workers  performing    the tasks they dont have the time or capacity to do. Moreover,    this rapid analysis and provision of data would enhance the    overall efficiency of the human decision-making processes. And    so, rather than replace jobs, the AI systems would empower    human services.  <\/p>\n<p>    This is exactly what IBM Watson has been working on in    collaboration with Memorial Sloan-Kettering Cancer Center.    World-renowned oncologists have been training Watson to compare    a patients medical information against a vast array of    treatment guidelines and research to provide recommendations to    physicians on a patient-by-patient basis.  <\/p>\n<p>    Supporting evidence is provided for each recommendation in    order to provide transparency and to aid in the doctors    decision-making process, and Watson will update its suggestions    as new data is added. Watson is being used to facilitate access    to the best of oncologys collective knowledge, therefore    demonstrating how this can be applied across the entire medical    profession.  <\/p>\n<p>    Having recognised the potential that AI tech can bring to the    wider industry, community healthcare service Fluid Motion has    rolled out pilot trials in a bid to overcome the challenges    they face in relation to cost, staffing, efficient    decision-making processes and data crunching.  <\/p>\n<p>    Born from the frustration of facing barriers presented by the    current healthcare system, Fluid Motions group aquatic therapy    programme is a tailored rehabilitation concept that has been    designed to be both fun and beneficial for people with a range    of musculoskeletal conditions, with an overall aim to treat,    manage and prevent such conditions.  <\/p>\n<p>    With one in five GP appointments being related to    musculoskeletal disorders  translating into a cost to the UK    economy of 24.8 billion per year due to sick leave  the need    for fast and effective healthcare solutions is clear. But the    challenge, as indicated Ben Wilkins of Fluid Motion, is that    while these programmes are successful, there simply arent    enough professionals to sustain the growing levels of demand    for the service. Additionally the very nature of the programmes    means that they depend heavily on vast amounts of data input    and analysis to determine the right solution.   <\/p>\n<p>    Fluid Motion recognised that, if they could generate these    rehabilitation plans automatically, it would allow them to    lower their staff costs and increasing their reach. Fitness    Instructors could quickly generate a high-quality tailored plan    based on a model of the Physiotherapist and Osteopaths    expertise, modelled in AI-powered cognitive reasoning platform,    Rainbird.  <\/p>\n<p>    Rainbird modelled the knowledge of Fluid Motions qualified    physiotherapists and osteopaths, including the suitability of    numerous exercises to individual patient symptoms, and added it    to an interface that could be accessed by Fluid Motions    network of fitness instructors. The tool allowed them to create    a tailored, illustrated rehabilitation plan for patients, based    on the results of an initial interaction with a virtual    physiotherapist or osteopath.  <\/p>\n<p>    The next step will be to provide access to patients directly so    that they can create their own rehabilitation plans. Patients    will have the facility to give feedback so that Rainbird can    learn and, where necessary, adapt their plan or make    alternative recommendations if specific exercises are    uncomfortable.  <\/p>\n<p>    Fluid Motion has since been able to track and reflect on    participants progress in real-time, meaning the data can be    utilised to improve clinical decision-making in rehabilitative    healthcare. The application of AI helps patients get    better sooner, and prevents pain and disability for longer.  <\/p>\n<p>    The time and cost saving possibilities resulting from the    implementation of such a programme are indubitable. According    to Wilkins, the cumulative cost for a healthcare professional    per session is 75 (50 for hiring an Osteo\/Physio for the    whole session and 25 to pay them to review feedback data to    make recommendation). When Fluid Motion sessions now only cost    the company 35 (for a Fluid Motion fitness instructor) and 25    (for pool hire), theres a full 150 per cent saving. With this    model, it means that Fluid Motion can charge participants less    than the average price of a swim to attend sessions.  <\/p>\n<p>    Up to this point, Fluid Motion had been subsidising cost with    grant payments, but now the company breaks even each session.    Moreover, this is a model which is scalable. As a result of    this initiative, Fluid Motion is now working to become an    organisation that provides support and treatment for    musculoskeletal health conditions alongside the NHS.  <\/p>\n<p>    Indeed, the Fluid Motion case study clearly illustrates how    challenges in healthcare can be overcome through the    implementation of AI systems, and also highlights the potential    time and cost saving benefits that the NHS could reap, if such    an approach were adopted.  <\/p>\n<p>    By mapping knowledge of some of the medical roles that are in    high demand, there are many ways that the technology can help    to streamline some of the more rudimentary elements of those    roles. This would free up time to devote to face-to-face    consultancy that would have the most impact for patients,    reduce waiting times and even enable medical professionals to    engage in a more personalised service.  <\/p>\n<p>    This application of AI has the potential to address the rise in    demand for NHS services, whilst ensuring that doctors and    nurses spend more time doing the work that they are trained to    do; treating patients to the best of their ability. Indeed,    with the assistance of AI-powered technologies, the NHS may not    only survive the crisis but, like the Phoenix, rise from the    ashes to achieve its original goal of bringing good healthcare    to all.  <\/p>\n<p>    Katie Gibbs, Head of Accelerated Consulting, Aigen    Image Credit: John Williams RUS \/ Shutterstock  <\/p>\n<p><!-- Auto Generated --><\/p>\n<p>More here: <\/p>\n<p><a target=\"_blank\" href=\"http:\/\/www.itproportal.com\/features\/can-artificial-intelligence-save-the-nhs\/\" title=\"Can artificial intelligence save the NHS? - ITProPortal\">Can artificial intelligence save the NHS? - ITProPortal<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p> According to the Office for Budget Responsibility, the NHS budget will need to increase by 88billion over the next 50 years if it is to keep pace with the rising demand for healthcare in the UK. But with the 2017 Budget showcasing a massive leaning towards building up its Brexit reserves and allocating a mere 100 million for 100 onsite GP treatment centres in A&#038;Es across England, the NHS is justifiably bracing itself for a painful future <a href=\"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/artificial-intelligence\/can-artificial-intelligence-save-the-nhs-itproportal.php\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"limit_modified_date":"","last_modified_date":"","_lmt_disableupdate":"","_lmt_disable":"","footnotes":""},"categories":[13],"tags":[],"class_list":["post-215282","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence"],"modified_by":null,"_links":{"self":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/215282"}],"collection":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/comments?post=215282"}],"version-history":[{"count":0,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/215282\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/media?parent=215282"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/categories?post=215282"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/tags?post=215282"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}