{"id":353,"date":"2013-10-12T11:29:58","date_gmt":"2013-10-12T15:29:58","guid":{"rendered":"http:\/\/jhumag.dev.173.166.187.154.xip.io\/?p=353"},"modified":"2014-06-02T15:20:55","modified_gmt":"2014-06-02T19:20:55","slug":"engineering-smarter-icu","status":"publish","type":"post","link":"https:\/\/engineering.jhu.edu\/magazine-archive\/2013\/10\/engineering-smarter-icu\/","title":{"rendered":"Engineering a Smarter ICU"},"content":{"rendered":"
\"Suchi
Suchi Saria wields innovative tools to make ICUs safer and more intelligent.<\/figcaption><\/figure>\n

A<\/span>merica\u2019s intensive care units\u00a0(ICUs) are supposed to\u00a0<\/span>showcase the lifesaving potential\u00a0of modern medicine. They are\u00a0<\/span>equipped with the latest technology,<\/span>staffed with the most skilled staff, and centered in the best hospitals. Yet statistics show that ICUs are failing miserably: One out of every\u00a0five people treated in ICUs is harmed in some way (medical errors, mostly), costing the U.S. health care system an estimated\u00a0<\/span>$20 billion, and exacting a notable human toll.<\/p>\n

Johns Hopkins researchers want to reverse this troubling trend. Under a $1.5 million grant from the Gordon and Betty Moore Foundation as well as a $300,000 grant from Florida\u2019s All Children\u2019s Hospital Foundation,
\nWhiting School computer scientist<\/span>\u00a0Suchi Saria has launched a research program aimed at making hospitals safer.\u00a0<\/span><\/p>\n

Using ICUs as her proving ground, Saria is wielding innovative machine learning tools aimed at making the health care delivery environment more\u00a0\u201cintelligent.\u201d Her project is one of<\/span>\u00a0the first funded at Johns Hopkins
\nunder a nationwide Moore Foundation initiative to improve patient safety with $500 million in grants over the next decade.<\/p>\n

An assistant professor at the Whiting School and the Bloomberg School of Public Health, Saria imagines an ICU where computers equipped with sophisticated algorithms help doctors make more efficient and accurate medical decisions, and where unobtrusive sensors alert hospital staff to potentially harmful errors.<\/p>\n

\u201cWe have an enormous opportunity here to make a significant difference in terms of the quality of care that patients get, and to enhance their safety while they are being cared for, especially in parts of the inpatientenvironment where fast assimilation<\/span>\u00a0of a large amount of information is necessary to respond in a timely manner,\u201d she says.<\/p>\n

The approach of Saria\u2019s team is twofold. In the first, it will put to work the reams of data that normally are collected at patients\u2019 bedsides\u2014from symptoms and medications to test results and tracings from bedside sensors like the EKG\u2014to tease out patterns that will indicate which patients need more aggressive care.<\/p>\n

\u201cWe are developing computational models that crunch enormous amounts of data that are collected on the patient, and [putting] that to work to help physicians track changes in health status over time,\u201d Saria explains.<\/p>\n

\u201cThese data are being\u00a0routinely collected in the Electronic<\/span>\u00a0Medical Record already. By developing computational approaches that can continuously scan this data, we\u2019re providing\u00a0caregivers with an extra set of \u2018eyes\u2019<\/span>\u00a0that detect salient information<\/span>\u00a0that\u00a0the caregivers can then use to help<\/span>make their treatment decisions.\u201d<\/p>\n

Saria points out that there is growing evidence that predictive algorithms are useful in the early detection of which patients are at risk, as well as in reducing the time it takes to intervene in those cases. This work has its roots in research that Saria started at Stanford University. There, she\u00a0and her team successfully predicted<\/span>health risks in premature infants using the abundance of data collected in bedside monitors\u00a0in neonatal intensive care units.<\/p>\n

The other prong in Saria\u2019s current project involves the development of noninvasive 3D sensors that will unobtrusively monitor care activities in the patient\u2019s room to identify when an error might have occurred or when an important care activity was missed.<\/p>\n

\u201cThese sensors will track a number of important activities, from safety steps\u2014 such as hand washing\u2014that medical staff perform to care-related practices that help improve patient outcomes,\u201d she says. \u201cBy giving this information to them in near real-time, quality improvement experts can institute processes for rapid cycle improvement. Doctors think this type of high-fidelity, data-driven, more timely feedback would be a huge leap forward for the field of quality improvement.\u201d<\/p>\n

Saria\u2019s work is being done in collaboration with clinical researchers at Johns Hopkins Medicine\u2019s Armstrong Institute for Patient Safety and Quality, an organization that has pioneered the field of quality improvement with tools such as the patient checklist.<\/p>\n

\u201cThe potential of applying this novel sensing technology for quality improvement purposes is simply breathtaking,\u201d says Peter Pronovost, director of the Armstrong Institute and Johns Hopkins Medicine\u2019s vice president for patient safety and quality.<\/p>\n

\u201cBy integrating sensor data with existing information from the electronic medical record and patient monitors and analyzing these data, this research can show new approaches for creating a learning health care system.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

America\u2019s intensive care units\u00a0(ICUs) are supposed to\u00a0showcase the lifesaving potential\u00a0of modern medicine. They are\u00a0equipped with the latest technology,staffed with the most skilled staff, and centered in the best hospitals. Yet statistics show that ICUs are failing miserably: One out of every\u00a0five people treated in ICUs is harmed in some way (medical errors, mostly), costing the…<\/p>\n","protected":false},"author":4,"featured_media":571,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[31],"tags":[],"class_list":["post-353","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-big-ideas","issue-winter-2014"],"acf":[],"yoast_head":"\nEngineering a Smarter ICU - JHU Engineering Magazine<\/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:\/\/engineering.jhu.edu\/magazine-archive\/2013\/10\/engineering-smarter-icu\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Engineering a Smarter ICU - JHU Engineering Magazine\" \/>\n<meta property=\"og:description\" content=\"America\u2019s intensive care units\u00a0(ICUs) are supposed to\u00a0showcase the lifesaving potential\u00a0of modern medicine. 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