{"id":39948,"date":"2024-11-20T13:15:00","date_gmt":"2024-11-20T21:15:00","guid":{"rendered":"https:\/\/efaxunifiedstg.wpengine.com\/?p=39948"},"modified":"2025-08-12T13:24:54","modified_gmt":"2025-08-12T20:24:54","slug":"hlth-2024","status":"publish","type":"post","link":"https:\/\/www.efax.com\/blog\/hlth-2024","title":{"rendered":"Getting Down to Business with AI: Key Observations from HLTH"},"content":{"rendered":"\n<p>AI took center stage at HLTH 2024, where an estimated 12,000 healthcare stakeholders came to Las Vegas to explore what\u2019s new, what\u2019s next and what\u2019s needed in the industry.&nbsp;<\/p>\n\n\n\n<p>But unlike discussions at past HLTH events, there was a noticeable shift away from what AI <em>could<\/em> do for healthcare, in theory, toward use cases for AI that are<em> working right now<\/em>.&nbsp;<\/p>\n\n\n\n<p>This year\u2019s attendees\u2014from health system and health plan leaders to heads of startups and innovators\u2014found an environment marked by:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li class=\"font-sans-serif\"><strong>Vendors that have \u201cpicked their swim lane\u201d for AI<\/strong>. Industry pressures for proven AI use cases have forced vendors to demonstrate expertise in a particular area and market themselves based on this single capability, from ambient listening to prior authorization to clinical decision support, now called Decision Support Interventions (DSI).<\/li>\n\n\n\n<li class=\"font-sans-serif\"><strong>A look under the hood at AI solutions<\/strong>. Today\u2019s leaders want to know how AI solutions were built, how they were trained and what they can deliver now. They\u2019re also curious about where the best use cases are happening and the lessons learned from early adopters around implementation, engagement and sustainable success.<\/li>\n\n\n\n<li class=\"font-sans-serif\"><strong>Intense interest around ways to measure AI success<\/strong>. There\u2019s an emphasis on <em>validation<\/em>, making sure the AI tool delivers on its promises for a healthcare setting. This has led to more mature conversations around which key performance indicators should be used to evaluate performance, the timeframe in which leaders can expect results and the gains similar organizations have made, from improved health outcomes and operational efficiency to reduced burnout, administrative burden and cost.<\/li>\n<\/ul>\n\n\n\n<p class=\"mb-3 pt-4\">Among health system leaders, there\u2019s also a palpable sense of caution in evaluating new AI solutions. That\u2019s not surprising, given the number of organizations that have struggled to find solutions that deliver tangible value. A <a href=\"https:\/\/blackbookmarketresearch.newswire.com\/news\/black-book-it-leader-survey-reveals-8-technologies-draining-value-from-22427966\" target=\"_blank\" rel=\"noreferrer noopener\">Black Book survey<\/a> released just three weeks before HLTH found 96% of healthcare leaders face challenges with demonstrating ROI from AI solutions. Nine out of 10 say their solutions aren\u2019t accurate or actionable enough in clinical settings. Meanwhile, 85% saw \u201clittle to no ROI\u201d from solutions that automate diagnostics or treatment planning because these tools \u201cfailed to grasp the complexities of real-world clinical environments.\u201d<\/p>\n\n\n\n<p>For these leaders, questions such as, \u201cWhat problem do we want to solve with AI? And, is it worth the investment?\u201d are just the start of the AI evaluation process. There\u2019s also a desire to go beyond minimal impact toward tackling big problems with AI investments. The prevailing thinking is, \u201cIf we can\u2019t address our most pressing challenges with this tool, it\u2019s probably not worth the time, energy and resources to make the investment.\u201d<\/p>\n\n\n\n<h2 class=\"wp-block-heading mb-3 pt-4\"><strong>Our Take: AI Doesn\u2019t Have to Be Expensive to Be Transformative<\/strong><\/h2>\n\n\n\n<p>We continue to believe AI\u2019s biggest potential for right-now value comes from intelligent data extraction: applying machine learning and natural language processing to unstructured documents to transform the data into actionable insights. The value in this approach extends beyond small organizations.&nbsp;<\/p>\n\n\n\n<p>Think of healthcare disruptors (like Best Buy), which had a supersized presence at HLTH with a tech-enabled approach to at-home care. What happens when state Medicaid programs fax their patient information to team members to act upon? Someone has to enter the data from the fax. Or when a pharmacy \u2013 (also in attendance, like Kroger or Walgreens) \u2013 receives a faxed prescription, intelligent data extraction is a powerful tool for transforming this unstructured data and applying it to structured data fields that can be mapped to any receiving workflow.&nbsp;<\/p>\n\n\n\n<p>It\u2019s a technique that can be applied to images, PDFs, scans and even handwritten text. Included in the value of intelligent data extraction is a technology most organizations already possess\u2014digital cloud fax. Many Consensus customers using <a href=\"https:\/\/www.efax.com\/products\/corporate\">eFax Corporate<\/a>\u00ae, our industry-leading digital cloud fax platform, are increasingly adopting advanced tools like <a href=\"https:\/\/www.efax.com\/products\/corporate\" target=\"_blank\" rel=\"noreferrer noopener\">Clarity<\/a>, our AI solution, to revolutionize workflows, freeing administrative staff from tedious, time-consuming, and error-prone data entry.\u00a0<\/p>\n\n\n\n<p>Because it\u2019s a pragmatic approach to addressing healthcare\u2019s unstructured data problem, it\u2019s a tool that empowers healthcare\u2019s \u201cdigital have nots\u201d\u2014small organizations that didn\u2019t receive federal funds to implement an EHR\u2014to seamlessly exchange structured information with their large-system counterparts. Once the data is structured it can be shared using FHIR, HL7, X12 and Direct Secure Message to share information. That means better care and more reliable access to referrals.<\/p>\n\n\n\n<p>Find out more about our take on where AI could provide transformative value for healthcare in <a href=\"https:\/\/www.linkedin.com\/posts\/healthcareittoday_hlthusa-datatransformation-activity-7257825844847366146-3QE8?utm_source=share&amp;utm_medium=member_desktop\" target=\"_blank\" rel=\"noreferrer noopener\">my interview with Healthcare IT Today<\/a>, recorded during HLTH.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI took center stage at HLTH 2024, where an estimated 12,000 healthcare stakeholders came to Las Vegas to explore what\u2019s new, what\u2019s next and what\u2019s needed in the industry.&nbsp; But unlike discussions at past HLTH events, there was a noticeable shift away from what AI could do for healthcare, in theory, toward use cases for&#8230;<\/p>\n","protected":false},"author":35,"featured_media":39951,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[404],"tags":[],"class_list":["post-39948","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-thought-leadership"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>HLTH 2024 Recap: Practical AI Insights Transforming Healthcare<\/title>\n<meta name=\"description\" content=\"Discover how AI is moving from theory to real\u2011world impact at HLTH 2024 \u2013 actionable use cases, vendor strategies, and performance metrics.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.efax.com\/blog\/hlth-2024\" \/>\n<meta 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