{"id":19530,"date":"2025-03-06T20:50:35","date_gmt":"2025-03-06T20:50:35","guid":{"rendered":"https:\/\/www.tun.com\/home\/?p=19530"},"modified":"2025-03-06T20:51:00","modified_gmt":"2025-03-06T20:51:00","slug":"ai-model-to-improve-icu-bed-management","status":"publish","type":"post","link":"https:\/\/www.tun.com\/home\/ai-model-to-improve-icu-bed-management\/","title":{"rendered":"AI Model to Improve ICU Bed Management"},"content":{"rendered":"\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<div class=\"wp-block-uagb-blockquote uagb-block-e7eb3fc3 uagb-blockquote__skin-border uagb-blockquote__stack-img-none\"><blockquote class=\"uagb-blockquote\"><div class=\"uagb-blockquote__content\">New research led by Texas McCombs offers an AI model that predicts ICU length of stay with explainable results, potentially transforming how hospitals manage critical care resources.<\/div><footer><div class=\"uagb-blockquote__author-wrap uagb-blockquote__author-at-left\"><\/div><\/footer><\/blockquote><\/div>\n\n\n\n<div class=\"wp-block-group is-content-justification-space-between is-nowrap is-layout-flex wp-container-core-group-is-layout-0dfbf163 wp-block-group-is-layout-flex\"><div style=\"font-size:16px;\" class=\"has-text-align-left wp-block-post-author\"><div class=\"wp-block-post-author__content\"><p class=\"wp-block-post-author__name\">The University Network<\/p><\/div><\/div>\n\n\n<div class=\"wp-block-uagb-social-share uagb-social-share__outer-wrap uagb-social-share__layout-horizontal uagb-block-ee584a31\">\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-ec619ce7\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.facebook.com\/sharer.php?u=\" tabindex=\"0\" role=\"button\" aria-label=\"facebook\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M504 256C504 119 393 8 256 8S8 119 8 256c0 123.8 90.69 226.4 209.3 245V327.7h-63V256h63v-54.64c0-62.15 37-96.48 93.67-96.48 27.14 0 55.52 4.84 55.52 4.84v61h-31.28c-30.8 0-40.41 19.12-40.41 38.73V256h68.78l-11 71.69h-57.78V501C413.3 482.4 504 379.8 504 256z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-32d99934\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/twitter.com\/share?url=\" tabindex=\"0\" role=\"button\" aria-label=\"twitter\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M389.2 48h70.6L305.6 224.2 487 464H345L233.7 318.6 106.5 464H35.8L200.7 275.5 26.8 48H172.4L272.9 180.9 389.2 48zM364.4 421.8h39.1L151.1 88h-42L364.4 421.8z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-1d136f14\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.linkedin.com\/shareArticle?url=\" tabindex=\"0\" role=\"button\" aria-label=\"linkedin\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 448 512\"><path d=\"M416 32H31.9C14.3 32 0 46.5 0 64.3v383.4C0 465.5 14.3 480 31.9 480H416c17.6 0 32-14.5 32-32.3V64.3c0-17.8-14.4-32.3-32-32.3zM135.4 416H69V202.2h66.5V416zm-33.2-243c-21.3 0-38.5-17.3-38.5-38.5S80.9 96 102.2 96c21.2 0 38.5 17.3 38.5 38.5 0 21.3-17.2 38.5-38.5 38.5zm282.1 243h-66.4V312c0-24.8-.5-56.7-34.5-56.7-34.6 0-39.9 27-39.9 54.9V416h-66.4V202.2h63.7v29.2h.9c8.9-16.8 30.6-34.5 62.9-34.5 67.2 0 79.7 44.3 79.7 101.9V416z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n<p><\/p>\n\n\n\n<p>At the height of the COVID-19 pandemic, hospitals across the United States struggled to keep up with the demand for intensive care unit (ICU) beds as patient numbers surged. But even before the pandemic, ICUs faced persistent challenges in maintaining available beds for gravely ill patients.<\/p>\n\n\n\n<p>Artificial intelligence (AI) holds promise in addressing these challenges by predicting the lengths of ICU stays, enabling hospitals to better manage their bed capacity and reduce costs.<\/p>\n\n\n\n<p>Indranil Bardhan, professor of information, risk and operations management and the Charles and Elizabeth Prothro Regents Chair in Health Care Management at Texas McCombs School of Business, is at the forefront of this innovation. <\/p>\n\n\n\n<p>Bardhan and his team have developed an AI model designed to predict ICU stay durations with improved clarity for health care providers \u2014 a concept known as explainable artificial intelligence (XAI).<\/p>\n\n\n\n<p>&#8220;People were mostly focused on the accuracy of prediction, and that\u2019s an important thing,&#8221; Bardhan said in a news release. &#8220;The prediction is good, but can you explain your prediction?&#8221;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Explaining AI Predictions<\/h2>\n\n\n\n<p>Bardhan\u2019s research, conducted alongside doctoral student Tianjian Guo, Ying Ding of UT\u2019s School of Information and Shichang Zhang of Harvard University, aims to make AI more interpretable and useful to ICU doctors. <\/p>\n\n\n\n<p>The team trained their model on a dataset of 22,243 medical records spanning from 2001 to 2012, incorporating 47 different patient attributes, such as age, gender, vital signs, medications and diagnoses.<\/p>\n\n\n\n<p>The model can produce graphs indicating a patient\u2019s probability of being discharged within seven days and detailing which attributes most influence this outcome. For example, the model might show an 8.5% likelihood of discharge within seven days and highlight a respiratory system diagnosis as a primary factor, with age and medications as significant secondary factors.<\/p>\n\n\n\n<p>The study, <a href=\"https:\/\/pubsonline.informs.org\/doi\/abs\/10.1287\/isre.2023.0029\" target=\"_blank\" rel=\"noopener\" title=\"\">published<\/a> in the journal Information Systems Research, found that the model\u2019s predictions were as accurate as other leading AI models, but its explanatory power was superior.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Beyond the ICU<\/h2>\n\n\n\n<p>To test the practical application of their model, the researchers surveyed six physicians working in ICUs in the Austin area. Four of the six doctors indicated that the model&#8217;s explanations could help them improve staffing and resource management, aiding in more effective patient scheduling.<\/p>\n\n\n\n<p>Despite its promise, the model has a notable limitation: it uses outdated data from prior to 2014, when the health care industry transitioned from the ICD-9-CM to the ICD-10-CM coding system, which offers more detailed and specific diagnostic information.<\/p>\n\n\n\n<p>&#8220;If we were able to get access to more recent data, we would have loved to extend our models using that data,&#8221; Bardhan added.<\/p>\n\n\n\n<p>However, this model has the potential to be adapted beyond adult ICUs. Bardhan suggests it could also be applicable in pediatric and neonatal ICUs, emergency rooms and even regular hospital units for predicting patient stay durations and optimizing bed management.<\/p>\n\n\n\n<div style=\"height:7px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Source: <a href=\"https:\/\/news.mccombs.utexas.edu\/research\/ai-can-open-up-beds-in-the-icu\/\" target=\"_blank\" rel=\"noopener\" title=\"\">UT Austin McCombs School of Business<\/a><\/p>\n\n\n\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>At the height of the COVID-19 pandemic, hospitals across the United States struggled to keep up with the demand for intensive care unit (ICU) beds as patient numbers surged. But even before the pandemic, ICUs faced persistent challenges in maintaining available beds for gravely ill patients. Artificial intelligence (AI) holds promise in addressing these challenges [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-no-separators","format":"standard","meta":{"_acf_changed":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[8],"tags":[78,41],"class_list":["post-19530","post","type-post","status-publish","format-standard","hentry","category-ai","tag-harvard-university","tag-ut-austin"],"acf":[],"aioseo_notices":[],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false},"uagb_author_info":{"display_name":"The University Network","author_link":"https:\/\/www.tun.com\/home\/author\/funky_junkie\/"},"uagb_comment_info":0,"uagb_excerpt":"At the height of the COVID-19 pandemic, hospitals across the United States struggled to keep up with the demand for intensive care unit (ICU) beds as patient numbers surged. But even before the pandemic, ICUs faced persistent challenges in maintaining available beds for gravely ill patients. Artificial intelligence (AI) holds promise in addressing these challenges&hellip;","_links":{"self":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/19530","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/comments?post=19530"}],"version-history":[{"count":9,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/19530\/revisions"}],"predecessor-version":[{"id":19584,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/19530\/revisions\/19584"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/media?parent=19530"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/categories?post=19530"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/tags?post=19530"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}