{"id":4692,"date":"2020-12-09T13:59:20","date_gmt":"2020-12-09T13:59:20","guid":{"rendered":"http:\/\/orionhealth-blog.local\/?p=4692"},"modified":"2023-02-01T00:32:36","modified_gmt":"2023-02-01T00:32:36","slug":"managing-machine-learning","status":"publish","type":"post","link":"https:\/\/orionhealth.com\/nz\/blog\/managing-machine-learning\/","title":{"rendered":"Managing machine learning"},"content":{"rendered":"\n<p>There is still something slightly futuristic about machine learning. After all,&nbsp;it\u2019s&nbsp;less&nbsp;than a decade since Hollywood&nbsp;thought it was worth boosting the sci-fi credentials of a movie by calling it&nbsp;A.I. Artificial Intelligence.&nbsp;&nbsp;<\/p>\n\n\n\n<p>However, the use&nbsp;of AI or machine learning products is becoming more and more common in healthcare, not least&nbsp;as a result of&nbsp;the Covid-19 pandemic. Governments and planners have turned to computer models to project the progress of the disease, calculate risk scores for patient cohorts and individuals, and support clinicians in triage and treatment decisions.&nbsp;&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>NHS context&nbsp;<\/strong>&nbsp;<\/h2>\n\n\n\n<p>Bruce Horne, product specialist at Orion Health, told the last&nbsp;of its 2020 series of autumn webinars that these trends would continue. \u201cThe NHS Long Term Plan talks about the importance of technology, and especially AI, to improving outcomes and efficiency,\u201d he said.&nbsp;&nbsp;<\/p>\n\n\n\n<p>\u201cNational bodies have been making awards in this area, and NHSX has created an NHS AI Lab.\u00a0We are also seeing customers who are interested in AI. For example, one of our customers <a href=\"https:\/\/blog.orionhealth.com\/connecting-care-expands-and-evolves-in-response-to-covid-19\/\" target=\"_blank\" rel=\"noreferrer noopener\">Connecting Care<\/a> in Bristol used AI to score Covid-19 risk and made the tool available through its portal\u201d<\/p>\n\n\n\n<p>Orion Health has\u00a0a range of products\u00a0and services to support these developments. The webinar focused on <a href=\"https:\/\/orionhealth.com\/\/nz\/knowledge-hub\/reports\/machine-learning-in-healthcare\/\">Machine Learning Manager<\/a>\u00a0and <a href=\"https:\/\/orionhealth.com\/\/global\/knowledge-hub\/press-releases\/orion-health-supports-covid-19-decision-making-with-a-national-algorithm-management-solution\/\">Algorithm Library;<\/a> although Orion Health also offers data de-identification tools and document tagging that makes it much easier to turn free text into searchable, machine readable data that can be mined for further insights.\u00a0\u00a0<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Orion Health Machine Manager and Algorithm Library&nbsp;<\/strong>&nbsp;<\/h2>\n\n\n\n<p>Machine Learning Manager is important because, as Horne went on to point out: \u201cAn algorithm has no value without effective deployment.\u201d&nbsp;&nbsp;<\/p>\n\n\n\n<p>As things stand, organisations that want to roll-out machine learning products need to come up with their own model for working out how to get them into the right hands, find out what is happening to them, and keep them up to date.&nbsp;But&nbsp;MLM can do the job for them.&nbsp;&nbsp;<\/p>\n\n\n\n<p>MLM can handle the algorithms and calculators in the Algorithm Library or those&nbsp;developed by&nbsp;third parties. In all cases, it will look after their administration and deployment, whether that is through a dashboard, or a portal, or as a data extract.&nbsp;&nbsp;<\/p>\n\n\n\n<p>The Algorithm Library, meanwhile, gives users access to a long list of locally configurable algorithms and calculators that provide \u2018out of the box\u2019 predictive insights into areas such as risk of readmission and surgical outcomes. But it can also be used to store and manage third-party tools.&nbsp;&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Think first, and&nbsp;<\/strong><strong>don\u2019t<\/strong><strong>&nbsp;forget change management&nbsp;<\/strong>&nbsp;<\/h2>\n\n\n\n<p>Even with this kind of support, machine learning and AI is a complex business. \u201cAll of the above looks great, but there are some logistical considerations,\u201d Horne said, in a section headed \u2018important considerations\u2019.&nbsp;&nbsp;<\/p>\n\n\n\n<p>\u201cThe first thing is to have a strategy, driven by local needs,\u201d he said, \u201cbecause then&nbsp;you can consider how AI can help you to meet challenges instead of&nbsp;[coming at things] the other way around.&nbsp;The second thing is to start simple: deploy something well and understand it fully before you move onto something more complex.&nbsp;&nbsp;<\/p>\n\n\n\n<p>\u201cAnd the third thing is to understand that there is a change management task: you need end-users to understand these tools and how they will impact their workload and working practices.\u201d As in so many areas of health tech: \u201cClinical engagement is critical.\u201d&nbsp;&nbsp;<\/p>\n\n\n\n<p>Finally, users need good local governance practices for the storage and control of data, they need good infrastructure, and they need good data. \u201cData is key,\u201d Horne emphasised. \u201cYou need to understand your data, and when it is good enough, and how you can continuously improve it.\u201d&nbsp;&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>The New Zealand Algorithm Hub&nbsp;<\/strong>&nbsp;<\/h2>\n\n\n\n<p>To help customers that want to move into the world of machine learning and AI, Orion Health has an Intelligence Services team. Pieta Brown, senior data science consultant, explained that it can provide data science consultancy and support on strategy as well as specific development skills.&nbsp;&nbsp;<\/p>\n\n\n\n<p>Her colleague, Genevieve&nbsp;Dawick, then explained how&nbsp;<a href=\"https:\/\/www.hinz.org.nz\/news\/508052\/Orion-to-deliver-national-algorithm-hub.htm\" target=\"_blank\" rel=\"noreferrer noopener\">it had helped the New Zealand government<\/a>&nbsp;to develop a cloud-based, MLM-based,&nbsp;<a href=\"https:\/\/orionhealth.com\/\/nz\/solutions\/new-zealand-algorithm-hub\/#:~:text=Orion%20Health%27s%20NZ%20Algorithm%20Hub,and%20practice%20for%20operational%20use.\" target=\"_blank\" rel=\"noreferrer noopener\">Algorithm Hub to support the fight against Covid-19<\/a>.&nbsp;&nbsp;<\/p>\n\n\n\n<p>\u201cIn New Zealand, we have had a fairly successful Covid-19 elimination strategy,\u201d she said [the country implemented an early travel ban, lockdown and test and trace strategy, and&nbsp;at the time of the webinar had seen just&nbsp;2,078 cases of the disease and 25 deaths].&nbsp;&nbsp;<\/p>\n\n\n\n<p>\u201cBecause of our unique situation, our&nbsp;<a href=\"https:\/\/algorithmhub.co.nz\/\" target=\"_blank\" rel=\"noreferrer noopener\">focus has been on three areas<\/a>:&nbsp;Covid&nbsp;disease spread, models to help clear [elective care] backlogs, and preparedness if outbreaks were to occur.&nbsp;We also created some simple calculators&nbsp;in case they were required.\u201d&nbsp;&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Learning lessons, tracking concept drift&nbsp;<\/strong>&nbsp;<\/h2>\n\n\n\n<p>One of the challenges that the development team has faced is that New Zealand has had too few cases of the disease to fully validate the tools.&nbsp;&nbsp;<\/p>\n\n\n\n<p>However, the&nbsp;team has&nbsp;focused on making sure that&nbsp;they should work in a&nbsp;New Zealand context and not adversely impact on any of its population groups,&nbsp;including the Maori population that has traditionally experienced worse health outcomes.&nbsp;&nbsp;<\/p>\n\n\n\n<p>Dawick&nbsp;said it has&nbsp;been working with a governance group that&nbsp;\u201creally helps&nbsp;keeps us&nbsp;on our toes about what is deployed and how it should be used.\u201d&nbsp;The hub is now being updated so it can be used on a \u2018business as usual\u2019 basis. New context is being added to the tools that are in it and additional calculators are being added.&nbsp;<\/p>\n\n\n\n<p>Experience tracking is also being added, so the team can assess the performance of the different modules and keep on top of \u2018concept drift\u2019. \u201cThis is important,\u201d&nbsp;Dawick&nbsp;said as the&nbsp;webinar drew to its close. \u201cYou need to track the performance of the model because it can change over time.&nbsp;&nbsp;<\/p>\n\n\n\n<p>\u201cChanges in lockdown regimes is a good example. They change, so you need to refine the model to make sure you are keeping up with these different factors over time.\u201d&nbsp;&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Improving patient care, saving lives&nbsp;<\/strong>&nbsp;<\/h2>\n\n\n\n<p>Because the Orion Health Machine Learning Manager makes this kind of administration achievable, it supports the very non-sci-fi aim of using AI and machine learning&nbsp;in healthcare to improve clinical decision making and, with it,&nbsp;efficiency&nbsp;and quality. Or, as Horne summarised, to&nbsp;\u201cimprove patient care and save even more lives.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"<p>There is still something slightly futuristic about machine learning. After all,&nbsp;it\u2019s&nbsp;less&nbsp;than a decade since Hollywood&nbsp;thought it was worth boosting the sci-fi credentials of a movie by calling it&nbsp;A.I. Artificial Intelligence.&nbsp;&nbsp; However, the use&nbsp;of AI or machine learning products is becoming more and more common in healthcare, not least&nbsp;as a result of&nbsp;the Covid-19 pandemic. Governments and [&hellip;]<\/p>\n","protected":false},"author":6,"featured_media":4693,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[1],"tags":[],"region":[24,27],"class_list":["post-4692","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","region-nz","region-uk"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Managing machine learning - Orion Health<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/orionhealth.com\/nz\/blog\/managing-machine-learning\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Managing machine learning - Orion Health\" \/>\n<meta property=\"og:description\" content=\"There is still something slightly futuristic about machine learning. After all,&nbsp;it\u2019s&nbsp;less&nbsp;than a decade since Hollywood&nbsp;thought it was worth boosting the sci-fi credentials of a movie by calling it&nbsp;A.I. Artificial Intelligence.&nbsp;&nbsp; However, the use&nbsp;of AI or machine learning products is becoming more and more common in healthcare, not least&nbsp;as a result of&nbsp;the Covid-19 pandemic. 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