AI IN HEALTHCARE<\/p>\n
If you wanted to design an organisation that could benefit enormously from AI, you might end up with something that looks a lot like the NHS.<\/strong><\/p>\n Vast quantities of structured and unstructured data. Chronic resource constraints. Decision-making bottlenecks that cost lives. Repetitive administrative tasks consuming clinician time that should be spent on patients. AI could, genuinely, be transformative here \u2014 and in isolated pockets, it already is.<\/p>\n So why is the overall picture so frustrating?<\/p>\n Radiology is the success story everyone points to, and rightly so. AI-assisted reading of chest X-rays and CT scans has shown consistent evidence of catching pathologies earlier and reducing reporting backlogs. Dermatology screening tools are performing comparably to consultant dermatologists on specific classification tasks. Sepsis prediction algorithms in ICUs are flagging deteriorating patients earlier than traditional observation.<\/p>\n These aren’t pilot projects. They’re deployed at scale, and they’re saving lives. That needs to be said clearly, because the NHS’s relationship with technology is so fraught with failure stories that genuine successes often get overlooked.<\/p>\n “The procurement process for NHS technology was designed to prevent waste. It has become so complex that it now prevents progress.”<\/p><\/blockquote>\n The NHS procurement process for technology is a genuine barrier to progress. It was designed, understandably, to prevent the kind of expensive failures that have characterised NHS IT programmes for decades. But in trying to prevent bad outcomes, it has created a system so slow and complex that by the time a technology has been evaluated, approved, and contracted, the technology itself has often moved on two or three generations.<\/p>\n The solution isn’t to abandon rigour. It’s to build rigorous processes that operate at the speed of the technology being evaluated. Right now, that gap is where good AI goes to die.<\/p>\n Tags: Artificial Intelligence \u2022 Opinion \u2022 Technology & Society \u2022 192.168.1.22\/<\/p>\n","protected":false},"excerpt":{"rendered":" The NHS has more to gain from AI than almost any institution in the UK. So why is adoption so painfully slow?<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3,23],"tags":[],"class_list":["post-9010","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence","category-technology"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"http:\/\/iamglover.com\/index.php?rest_route=\/wp\/v2\/posts\/9010","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/iamglover.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/iamglover.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/iamglover.com\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/iamglover.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=9010"}],"version-history":[{"count":1,"href":"http:\/\/iamglover.com\/index.php?rest_route=\/wp\/v2\/posts\/9010\/revisions"}],"predecessor-version":[{"id":9074,"href":"http:\/\/iamglover.com\/index.php?rest_route=\/wp\/v2\/posts\/9010\/revisions\/9074"}],"wp:attachment":[{"href":"http:\/\/iamglover.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=9010"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/iamglover.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=9010"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/iamglover.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=9010"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Where AI Is Already Working<\/h2>\n
The Procurement Problem<\/h2>\n