[{"data":1,"prerenderedAt":384},["ShallowReactive",2],{"slug-analysis-of-over-10000-healthcare-ai-patents-highlights-future-trends-our-new-study":3},{"post":4,"relatedPosts":157,"relatedBooks":286},{"id":5,"date":6,"date_gmt":7,"guid":8,"modified":10,"modified_gmt":11,"slug":12,"status":13,"type":14,"link":15,"title":16,"content":18,"excerpt":21,"author":23,"featured_media":24,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":29,"categories":30,"tags":32,"project_category":44,"contact_email_category":46,"yst_prominent_words":47,"class_list":48,"better_featured_image":68,"acf":91,"yoast_meta":101,"_links":104},51273,"2023-06-15T10:00:00","2023-06-15T08:00:00",{"rendered":9},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=51273&_wpnonce=54cde71949&status=auto-draft&type=post","2023-06-16T14:00:31","2023-06-16T12:00:31","analysis-of-over-10000-healthcare-ai-patents-highlights-future-trends-our-new-study","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002Fanalysis-of-over-10000-healthcare-ai-patents-highlights-future-trends-our-new-study",{"rendered":17},"Analysis Of Over 10,000 Healthcare AI Patents Highlights Future Trends: Our New Study",{"rendered":19,"protected":20},"\n\u003Cp>We are thrilled to announce the recent publication of our new study, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fai.jmir.org\u002F2023\u002F1\u002Fe47283\" target=\"_blank\">Forecasting Artificial Intelligence Trends in Health Care: Systematic International Patent Analysis\u003C\u002Fa> in the Journal of Medical Internet Research AI (JMIR AI). Our study takes an interesting deep dive into healthcare AI patents from the last decade, analysing over 10,000 of them from 2012 to 2022. Through this exploration, we shed light on the growth trends, the direction AI innovation is heading in different medical specialties, and the potential future implications of AI and Machine Learning (ML) in healthcare.\u003C\u002Fp>\n\n\n\n\u003Cp>Our journey into the world of healthcare AI innovation and regulation started in 2019-2020 with a fair amount of research resulting in \u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41746-020-00324-0\" target=\"_blank\" rel=\"noreferrer noopener\">this study published in Nature digital medicine\u003C\u002Fa>. A fascinating starting point for that venture was that although the FDA had been approving AI-based devices for years, they hadn’t initially distinguished them as a unique category. We decided to sift through these approvals and identify those that were AI-based. This resulted in the creation of an open-access database, which we shared with the FDA. Imagine our delight when, a year later, the \u003Ca href=\"https:\u002F\u002Fwww.fda.gov\u002Fmedical-devices\u002Fsoftware-medical-device-samd\u002Fartificial-intelligence-and-machine-learning-aiml-enabled-medical-devices\">FDA published their own database\u003C\u002Fa> and cited us as a source!\u003C\u002Fp>\n\n\n\n\u003Cp>To illustrate this work, we also created an infographic, “The Current State of FDA-Approved, AI-Based Medical Devices,” which, to our immense pleasure, has been downloaded millions of times and has been updated regularly since then. Here is its latest iteration:\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1436\" height=\"1080\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-5.png\" alt=\"\" class=\"wp-image-51277\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-5.png 1436w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-5-768x578.png 768w\" sizes=\"auto, (max-width: 1436px) 100vw, 1436px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">The \u003Ca href=\"http:\u002F\u002Fwww.medicalfuturist.com\u002Fpatents)\" target=\"_blank\" rel=\"noreferrer noopener\">new database\u003C\u002Fa> \u003C\u002Fh2>\n\n\n\n\u003Cp>But our curiosity didn’t stop there! \u003Ca href=\"https:\u002F\u002Fai.jmir.org\u002F2023\u002F1\u002Fe47283\" target=\"_blank\" rel=\"noreferrer noopener\">Our latest study\u003C\u002Fa> ventured even further, focusing primarily on AI-based healthcare patents. As sadly there is no unified global patent database, we worked with data from the 5 most active patent offices. We identified more than 10,000 such patents over the past 10 years.\u003C\u002Fp>\n\n\n\n\u003Cp>This undertaking was not just academic but also strategic, providing regulators with a clearer picture of the landscape they need to manage and the upcoming technologies they will need to regulate.\u003C\u002Fp>\n\n\n\n\u003Cp>Our research was using the Espacenet database, which includes patents from the China National Intellectual Property Administration, European Patent Office, Japan Patent Office, Korean Intellectual Property Office, and the United States Patent and Trademark Office.\u003C\u002Fp>\n\n\n\n\u003Cp>Our findings were intriguing. We identified a total of 10,967 patents, \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>with an overwhelming 66.9% (7,332 patents) originating from the China National Intellectual Property Administration\u003C\u002Fli>\n\n\n\n\u003Cli>the United States Patent and Trademark Office contributed 25.2% (2,768 patents),\u003C\u002Fli>\n\n\n\n\u003Cli>the Korean Intellectual Property Office 4.7% (513 patents), \u003C\u002Fli>\n\n\n\n\u003Cli>the European Patent Office 1.7% (191 patents), \u003C\u002Fli>\n\n\n\n\u003Cli>and the Japan Patent Office 1.5% (163 patents)\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cfigure class=\"wp-block-image size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1200\" height=\"656\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-4.png\" alt=\"\" class=\"wp-image-51275\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-4.png 1200w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-4-768x420.png 768w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>From 2015 until 2021, the number of published patents experienced an impressive doubling year on year. Five international companies played a substantial role in this surge: \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Ping An Medical and Healthcare Management Co Ltd led the pack with 568 (5.2%) patents, \u003C\u002Fli>\n\n\n\n\u003Cli>followed by Siemens Healthineers with 273 (2.5%) patents, \u003C\u002Fli>\n\n\n\n\u003Cli>IBM Corp with 226 (2.1%) patents, \u003C\u002Fli>\n\n\n\n\u003Cli>Philips Healthcare with 150 (1.4%) patents, and \u003C\u002Fli>\n\n\n\n\u003Cli>Shanghai United Imaging Healthcare Co Ltd with 144 (1.3%) patents.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">It is possible to predict which areas will need regulatory focus\u003C\u002Fh2>\n\n\n\n\u003Cp>We can draw several conclusions from this data. First,\u003Cstrong> it is possible to predict which areas will need regulatory focus\u003C\u002Fstrong>, as patents are followed by market-ready products\u002Fdevices with a predictable delay. Radiology, coupled with Oncology and Ophthalmology, stood out with a significant number of patents, so these areas will see the largest number of new technologies in clinical practice in a few years.\u003C\u002Fp>\n\n\n\n\u003Cp>Second, it is obvious that\u003Cstrong> China is at the forefront of innovation\u003C\u002Fstrong>, it is worth keeping an eye on them. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1200\" height=\"714\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-6.png\" alt=\"AI patents in healthcare\" class=\"wp-image-51279\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-6.png 1200w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-6-768x457.png 768w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>In our ongoing commitment to making information accessible, we’ve developed an \u003Ca href=\"http:\u002F\u002Fwww.medicalfuturist.com\u002Fpatents\" target=\"_blank\" rel=\"noreferrer noopener\">open-access database of these patents\u003C\u002Fa>. This database allows anyone to freely search and delve into the wealth of information about AI patents in healthcare. \u003C\u002Fp>\n\n\n\n\u003Cp>Hopefully, this database will empower policy makers worldwide to better predict healthcare trends in AI and to see which medical specialties will need more detailed regulations around this breakthrough technology.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Join the discussion\u003C\u002Fh2>\n\n\n\n\u003Ciframe loading=\"lazy\" src=\"https:\u002F\u002Fwww.linkedin.com\u002Fembed\u002Ffeed\u002Fupdate\u002Furn:li:share:7075073197464764416\" height=\"898\" width=\"404\" frameborder=\"0\" allowfullscreen=\"\" title=\"Embedded post\">\u003C\u002Fiframe>\n",false,{"rendered":22,"protected":20},"\u003Cp>By analysing more than 10,000 AI patents, it is possible to predict which specialties will see the largest number of new technologies and will need new regulations.\u003C\u002Fp>\n",6,51343,"closed",true,"","standard",{"_acf_changed":20,"footnotes":27},[31],504,[33,34,35,36,37,38,39,40,41,42,43],246,271,289,671,7671,7673,134,7829,144,7831,207,[45],952,[],[],[49,14,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67],"post-51273","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","tag-future","tag-health","tag-innovation","tag-machine-learning","tag-ai-in-healthcare","tag-ai-in-medicine","tag-ai","tag-ai-patents","tag-artificial-intelligence","tag-patent-analysis","tag-digital-health","project_category-policy-makers",{"id":24,"alt_text":27,"caption":27,"description":27,"media_type":69,"media_details":70,"post":5,"source_url":90},"image",{"width":71,"height":72,"file":73,"filesize":74,"sizes":75,"image_meta":88},720,405,"2023\u002F06\u002Ftmf_article_370_720.png",90990,{"medium":76,"thumbnail":83},{"file":77,"width":78,"height":79,"mime-type":80,"filesize":81,"source_url":82},"tmf_article_370_720-370x208.png","370","208","image\u002Fpng","91280","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_370_720-370x208.png",{"file":84,"width":85,"height":85,"mime-type":80,"filesize":86,"source_url":87},"tmf_article_370_720-150x150.png","150","28313","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_370_720-150x150.png",{"aperture":89,"credit":27,"camera":27,"caption":27,"created_timestamp":89,"copyright":27,"focal_length":89,"iso":89,"shutter_speed":89,"title":27,"orientation":89},"0","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_370_720.png",{"cta_type":92,"cta_color":27,"related_books":93,"related_posts_footer":97,"related_posts":20,"subtitle":27,"key_takeaways":20},"subscribe",[94,95,96],47427,34151,30419,[98,99,100],51165,51051,51061,{"yoast_wpseo_title":102,"yoast_wpseo_metadesc":103,"yoast_wpseo_canonical":15},"Analysis Of 10,000+ Healthcare AI Patents Highlights Future Trends, Study","By analysing AI patents, it is possible to predict which healthcare areas will see the largest number of new technologies and will need new regulations.",{"self":105,"collection":111,"about":114,"author":117,"replies":120,"version-history":123,"predecessor-version":127,"wp:featuredmedia":131,"wp:attachment":134,"wp:term":137,"curies":153},[106],{"href":107,"targetHints":108},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F51273",{"allow":109},[110],"GET",[112],{"href":113},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts",[115],{"href":116},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fpost",[118],{"embeddable":26,"href":119},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F6",[121],{"embeddable":26,"href":122},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=51273",[124],{"count":125,"href":126},9,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F51273\u002Frevisions",[128],{"id":129,"href":130},51391,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F51273\u002Frevisions\u002F51391",[132],{"embeddable":26,"href":133},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F51343",[135],{"href":136},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=51273",[138,141,144,147,150],{"taxonomy":139,"embeddable":26,"href":140},"category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=51273",{"taxonomy":142,"embeddable":26,"href":143},"post_tag","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=51273",{"taxonomy":145,"embeddable":26,"href":146},"project_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=51273",{"taxonomy":148,"embeddable":26,"href":149},"contact_email_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=51273",{"taxonomy":151,"embeddable":26,"href":152},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=51273",[154],{"name":155,"href":156,"templated":26},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",[158],{"id":100,"date":159,"date_gmt":160,"guid":161,"modified":163,"modified_gmt":164,"slug":165,"status":13,"type":14,"link":166,"title":167,"content":169,"excerpt":171,"author":173,"featured_media":174,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":175,"categories":176,"tags":178,"project_category":183,"contact_email_category":185,"yst_prominent_words":186,"class_list":189,"better_featured_image":197,"acf":234,"yoast_meta":241,"_links":243},"2023-06-01T13:20:43","2023-06-01T11:20:43",{"rendered":162},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=51061&_wpnonce=432a312f81&status=auto-draft&type=post","2023-06-01T13:20:45","2023-06-01T11:20:45","what-is-medical-coding-automation-and-its-potentials-in-healthcare","https:\u002F\u002Fmedicalfuturist.com\u002Fwhat-is-medical-coding-automation-and-its-potentials-in-healthcare",{"rendered":168},"What Is Medical Coding Automation And Its Potentials In Healthcare?",{"rendered":170,"protected":20},"\n\u003Cp>When it comes to the term ‘coding’, what comes to mind is probably programmers writing software. While this applies to the medical setting in the digital health age, traditionally, medical coding has referred to a specific process. It involves \u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41746-022-00705-7#Sec1\" target=\"_blank\" rel=\"noreferrer noopener\">the conversion of medical records\u003C\u002Fa>, generally from clinician’s texts, into structured codes based on a classification system for the appropriate patient diagnosis and relevant procedure.\u003C\u002Fp>\n\n\n\n\u003Cp>The result is clinical information that is consistent and comparable over time and across healthcare departments. Such data can subsequently be used to inform relevant research, policies and, in the case of the US, \u003Ca href=\"https:\u002F\u002Fwww.aapc.com\u002Fmedical-coding\u002Fmedical-coding.aspx\" target=\"_blank\" rel=\"noreferrer noopener\">for billing purposes\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cp>While important, the manual task of clinical coding is time-consuming. In the case of NHS Scotland for example, a single clinical coder can code \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41746-022-00705-7#Sec2\" target=\"_blank\">around 60 cases daily\u003C\u002Fa>, and a whole coding department can cover over 20,000 cases monthly. However, there remains a backlog which can take several months to cover. In addition, manual coding can lead to errors due to a number of reasons ranging from incomplete data to lack of coding experience.\u003C\u002Fp>\n\n\n\n\u003Cp>For these reasons, the medical coding process \u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41746-022-00705-7\" target=\"_blank\" rel=\"noreferrer noopener\">has attracted interest\u003C\u002Fa> in automating the process; more specifically with artificial intelligence (AI) technologies such as machine learning and natural language processing (NLP). In this article, we’ll consider the impact and potentials of such an approach.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Automating medical coding: an AI opportunity\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Computer-assisted medical coding \u003Ca href=\"https:\u002F\u002Fjournals.sagepub.com\u002Fdoi\u002F10.1177\u002F1833358319851305\" target=\"_blank\" rel=\"noreferrer noopener\">has been found to\u003C\u002Fa> enhance the accuracy, quality, and efficiency of manual coding. Researchers and medtech companies alike are now interested in supplementing such aids with AI technologies.\u003C\u002Fp>\n\n\n\n\u003Cp>“Anything image or text-centric is a great opportunity for AI,” \u003Ca href=\"https:\u002F\u002Frevcycleintelligence.com\u002Ffeatures\u002Fmedical-coding-is-the-next-stop-for-artificial-intelligence-in-healthcare\" target=\"_blank\" rel=\"noreferrer noopener\">explains Dr Eric Wilke\u003C\u002Fa>, chief operations officer at ER physician staffing company TECHealth. “So, yes, pathology, radiology, and dermatology are all areas of opportunity, but so is analysing charts for billing and coding.” \u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F065_compassionate_care_v2-768x432.png\" alt=\"A.I. in medicine\" class=\"wp-image-23751\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F065_compassionate_care_v2-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F065_compassionate_care_v2-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F065_compassionate_care_v2-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F065_compassionate_care_v2-2048x1152.png 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F065_compassionate_care_v2-512x288.png 512w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>With an AI-powered coding approach, the aim is to \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedcitynews.com\u002F2022\u002F10\u002Fwhat-will-the-next-generation-of-medical-coding-look-like\u002F\" target=\"_blank\">fully automate\u003C\u002Fa> the medical coding process. Through AI technologies such as NLP, clinical notes are interpreted and translated into codes appropriate for the healthcare organisation’s classification system. Let’s now consider the impact of such automation on the medical coding process.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>The impact of medical coding automation\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Considering the non-trivial aspect of medical coding, it’s no wonder that it entails a whole profession, but it’s experiencing a shortage. In the US alone, the nation is facing a 30% shortage of medical coders. AI-powered automation can address those gaps by supplementing those processes. Such potentials do not only lie in the realm of academic discussions. Companies like  \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fnym.health\u002F\" target=\"_blank\">Nym\u003C\u002Fa>, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.fathomhealth.com\u002F\" target=\"_blank\">Fathom\u003C\u002Fa> and \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fc212.net\u002Fc\u002Flink\u002F?t=0&l=en&o=3793383-1&h=2728337200&u=https%3A%2F%2Fwww.codametrix.com%2F&a=https%3A%2F%2Fwww.codametrix.com\" target=\"_blank\">CodaMetrix\u003C\u002Fa> are proposing such solutions.\u003C\u002Fp>\n\n\n\n\u003Cp>“[It’s] assigning the medical codes accurately within seconds and absolutely zero human intervention,” \u003Ca href=\"https:\u002F\u002Fmedcitynews.com\u002F2022\u002F10\u002Fwhat-will-the-next-generation-of-medical-coding-look-like\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">said Julien Dubuis\u003C\u002Fa>, chief commercial officer at Nym, when describing their company’s AI autonomous coding solution. “When I say accurately, I mean that we can achieve 96% accuracy code-over-code for outpatient specialties, which is at par with some of the best human coders.”\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-768x432.png\" alt=\"TMF, medical student, AI, doctor, data, computer\" class=\"wp-image-50547\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-2048x1152.png 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>CodaMetrix \u003Ca href=\"https:\u002F\u002Ffinance.yahoo.com\u002Fnews\u002Fcodametrix-closes-55m-series-autonomously-192000925.html\" target=\"_blank\" rel=\"noreferrer noopener\">is in partnership\u003C\u002Fa> with 10 health systems and universities to deploy its autonomous solution. The AI’s reported outcomes include 70% reduction in manual labour and a significant increase in cost savings.\u003C\u002Fp>\n\n\n\n\u003Cp>Fathom’s automated AI tool \u003Ca href=\"https:\u002F\u002Frevcycleintelligence.com\u002Ffeatures\u002Fmedical-coding-is-the-next-stop-for-artificial-intelligence-in-healthcare\" target=\"_blank\" rel=\"noreferrer noopener\">was leveraged by\u003C\u002Fa> ER physician staffing company TECHealth for medical billing and coding. With AI’s assistance, the company was able to process up to 80% of claims with little to no human interaction.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Supplementing, not replacing the medical coder\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Such potentials of automated medical coding might raise \u003Ca href=\"https:\u002F\u002Fhbr.org\u002F2021\u002F03\u002Fai-should-augment-human-intelligence-not-replace-it\" target=\"_blank\" rel=\"noreferrer noopener\">increasingly prevalent concerns\u003C\u002Fa> about AI replacing humans, even in the healthcare sector. However, this AI-fuelled evolution of medical coding will still factor in humans as the relationship will be more akin to a human-technology collaboration rather than a technological replacement of humans.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002F5-levels-of-automation-768x432.png\" alt=\"AI automation doctor radiology diagnositcs tmf\" class=\"wp-image-50501\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002F5-levels-of-automation-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002F5-levels-of-automation-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002F5-levels-of-automation-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002F5-levels-of-automation-2048x1152.png 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002F5-levels-of-automation.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>“There are so many things that [a] coder has to remember today… And so having technology helps ease some of that so that we won’t lose revenue,” \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedcitynews.com\u002F2022\u002F10\u002Fwhat-will-the-next-generation-of-medical-coding-look-like\u002F\" target=\"_blank\">explained Sherine Koshy\u003C\u002Fa>, senior director of health information management at Penn Medicine. “We’re here going to make sure that you are becoming more of an auditor in this job, more than just a coder.”\u003C\u002Fp>\n\n\n\n\u003Cp>TECHealth’s case, where the company employed Fathom’s AI automation solution, can help visualise such collaboration. In their example, the technology assisted in processing tens of thousands of medical charts to ensure proper coding in just a few days. This would have taken considerably longer without the aid of AI.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Preparing for the next step in medical automation\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>AI’s potential to positively enhance the medical coding process is undeniable; and AI automation can be considered as the next step in the process. However, its effective implementation will require surmounting some hurdles. Since the efficiency of the AI tool is highly dependent on the data it is trained on, it needs to be supplied with quality data. However, this is not a given from historical medical data.\u003C\u002Fp>\n\n\n\n\u003Cp>“If you don’t give the [AI] the most accurate information upfront, then you don’t always get the most correct information on the backside,” TECHealth’s \u003Ca href=\"https:\u002F\u002Frevcycleintelligence.com\u002Ffeatures\u002Fmedical-coding-is-the-next-stop-for-artificial-intelligence-in-healthcare\" target=\"_blank\" rel=\"noreferrer noopener\">Dr Wilke highlights\u003C\u002Fa>. “If I could go back and redo [implementation], one of the things I would’ve redone is analyzing our coding team to make sure they were using appropriate codes because anyone using an AI engine has to use historical data so they can build the AI’s prediction model.”\u003C\u002Fp>\n\n\n\n\u003Cp>Thus, to prepare for the adoption of automation in medical coding, healthcare organisations will need to ensure their medical data is accurate and of quality. This can then be used to train AI tools more efficiently. Medical coders in turn need to be trained to familiarise themselves with AI automation tools. With AI supplementing human coders’ tasks, existing hurdles in the medical coding process can thus be overcome.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cem>Written by Dr. Bertalan Meskó & Dr. Pranavsingh Dhunnoo\u003C\u002Fem>\u003C\u002Fp>\n",{"rendered":172,"protected":20},"\u003Cp>AI can help out humans in medical coding, where healthcare systems struggle with heavy backlogs. Algorithms work tirelessly and accurately.\u003C\u002Fp>\n",16,51069,{"_acf_changed":20,"footnotes":27},[177,31],7079,[179,180,39,181,41,182,43],7819,7821,7823,7825,[184,45],950,[],[187,188],1723,1833,[190,14,50,51,52,53,54,191,55,192,193,62,194,64,195,66,196,67],"post-51061","category-tmf","tag-medical-coding","tag-clinical-coding","tag-ai-in-medical-coding","tag-ai-in-hospitals","project_category-medical-professionals",{"id":174,"alt_text":198,"caption":27,"description":27,"media_type":69,"media_details":199,"post":100,"source_url":233},"AI medical coding doctor, hospital, clinic, man, laptop, computer",{"width":200,"height":201,"file":202,"filesize":203,"sizes":204,"image_meta":232},1920,1080,"2023\u002F06\u002Ftmf_article_365.png",95473,{"medium":205,"large":209,"thumbnail":215,"medium_large":219,"1536x1536":220,"2048x2048":226},{"file":206,"width":78,"height":79,"mime-type":80,"filesize":207,"source_url":208},"tmf_article_365-370x208.png","33431","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_365-370x208.png",{"file":210,"width":211,"height":212,"mime-type":80,"filesize":213,"source_url":214},"tmf_article_365-768x432.png","768","432","93344","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_365-768x432.png",{"file":216,"width":85,"height":85,"mime-type":80,"filesize":217,"source_url":218},"tmf_article_365-150x150.png","10783","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_365-150x150.png",{"file":210,"width":211,"height":212,"mime-type":80,"filesize":213,"source_url":214},{"file":221,"width":222,"height":223,"mime-type":80,"filesize":224,"source_url":225},"tmf_article_365-1536x864.png","1536","864","236001","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_365-1536x864.png",{"file":227,"width":228,"height":229,"mime-type":80,"filesize":230,"source_url":231},"tmf_article_365-2048x1152.png","2048","1152","350490","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_365-2048x1152.png",{"aperture":89,"credit":27,"camera":27,"caption":27,"created_timestamp":89,"copyright":27,"focal_length":89,"iso":89,"shutter_speed":89,"title":27,"orientation":89},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_365.png",{"cta_type":92,"cta_color":27,"subtitle":27,"related_books":235,"related_posts_footer":237,"related_posts":20},[94,96,236],24761,[238,239,240],50987,50545,50671,{"yoast_wpseo_title":168,"yoast_wpseo_metadesc":242,"yoast_wpseo_canonical":166},"AI can help out humans in medical coding, where healthcare systems struggle with heavy backlogs. Algorithms work tirelessly and accurately.",{"self":244,"collection":249,"about":251,"author":253,"replies":256,"version-history":259,"predecessor-version":263,"wp:featuredmedia":267,"wp:attachment":270,"wp:term":273,"curies":284},[245],{"href":246,"targetHints":247},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F51061",{"allow":248},[110],[250],{"href":113},[252],{"href":116},[254],{"embeddable":26,"href":255},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F16",[257],{"embeddable":26,"href":258},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=51061",[260],{"count":261,"href":262},8,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F51061\u002Frevisions",[264],{"id":265,"href":266},51123,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F51061\u002Frevisions\u002F51123",[268],{"embeddable":26,"href":269},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F51069",[271],{"href":272},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=51061",[274,276,278,280,282],{"taxonomy":139,"embeddable":26,"href":275},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=51061",{"taxonomy":142,"embeddable":26,"href":277},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=51061",{"taxonomy":145,"embeddable":26,"href":279},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=51061",{"taxonomy":148,"embeddable":26,"href":281},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=51061",{"taxonomy":151,"embeddable":26,"href":283},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=51061",[285],{"name":155,"href":156,"templated":26},[287],{"id":96,"date":288,"date_gmt":289,"guid":290,"modified":292,"modified_gmt":293,"slug":294,"status":13,"type":295,"link":296,"title":297,"content":299,"excerpt":301,"author":23,"featured_media":303,"comment_status":25,"ping_status":25,"template":27,"yst_prominent_words":304,"class_list":308,"better_featured_image":311,"acf":331,"yoast_meta":353,"_links":356},"2020-10-01T10:54:54","2020-10-01T08:54:54",{"rendered":291},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=book&p=30419","2023-03-12T18:16:29","2023-03-12T17:16:29","privacy-in-digital-health","book","https:\u002F\u002Fapi.medicalfuturist.com\u002Fbooks\u002Fprivacy-in-digital-health\u002F",{"rendered":298},"Hackers, Breaches and the Value of Health Data",{"rendered":300,"protected":20},"\n\u003Cp>Today, everyone needs to understand that there is no digital health without sacrificing a part of our privacy. The advanced technologies fueling the transformation cannot improve without our data; and without it, they can’t be implemented as part of regular medical care. And COVID-19 has only made things worse.\u003C\u002Fp>\n\n\n\n\u003Cp>In this e-Book, we defined the three cornerstones of privacy of every privacy discussion going forward: the traditional, the new and the future spheres that deal with your health data, and put forward recommendations on how you can start protecting yourself.\u003C\u002Fp>\n",{"rendered":302,"protected":20},"\u003Cp>Today, everyone needs to understand that there is no digital health without sacrificing a part of our privacy. The advanced technologies fueling the transformation cannot […]\u003C\u002Fp>\n",49967,[305,306,307],1693,1571,3633,[309,295,310,51,53,54],"post-30419","type-book",{"id":303,"alt_text":27,"caption":27,"description":27,"media_type":69,"media_details":312,"post":96,"source_url":330},{"width":313,"height":314,"file":315,"filesize":316,"sizes":317,"image_meta":328},320,414,"2020\u002F10\u002Fhack-breaches-health-data.png",89249,{"medium":318,"thumbnail":323},{"file":319,"width":313,"height":320,"mime-type":80,"filesize":321,"source_url":322},"hack-breaches-health-data-320x208.png",208,53801,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002Fhack-breaches-health-data-320x208.png",{"file":324,"width":325,"height":325,"mime-type":80,"filesize":326,"source_url":327},"hack-breaches-health-data-150x150.png",150,20987,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002Fhack-breaches-health-data-150x150.png",{"aperture":89,"credit":27,"camera":27,"caption":27,"created_timestamp":89,"copyright":27,"focal_length":89,"iso":89,"shutter_speed":89,"title":27,"orientation":89,"keywords":329},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002Fhack-breaches-health-data.png",{"buy_button_text":332,"leanpub_url":333,"preview":334},"Get it on Leanpub","https:\u002F\u002Fleanpub.com\u002Fprivacy-in-digital-health\u002F",[335,337,339,341,343,345,347,349,351],{"image":336},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-01.png",{"image":338},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-03.png",{"image":340},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-04.png",{"image":342},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-05.png",{"image":344},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-06.png",{"image":346},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-07.png",{"image":348},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-08.png",{"image":350},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-09.png",{"image":352},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-10.png",{"yoast_wpseo_title":354,"yoast_wpseo_metadesc":355,"yoast_wpseo_canonical":296},"Hackers, Breaches and the Value of Health Data: What You Need To Know - The Medical Futurist","Privacy in Digital Health: Privacy and security issues pertaining to the digital health era are complex and multifactorial. Learn more from our book",{"self":357,"collection":362,"about":365,"author":368,"replies":370,"wp:featuredmedia":373,"wp:attachment":376,"wp:term":379,"curies":382},[358],{"href":359,"targetHints":360},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fbook\u002F30419",{"allow":361},[110],[363],{"href":364},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fbook",[366],{"href":367},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fbook",[369],{"embeddable":26,"href":119},[371],{"embeddable":26,"href":372},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=30419",[374],{"embeddable":26,"href":375},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F49967",[377],{"href":378},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=30419",[380],{"taxonomy":151,"embeddable":26,"href":381},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=30419",[383],{"name":155,"href":156,"templated":26},1789720090991]