{"64241":{"#nid":"64241","#data":{"type":"news","title":"Researchers Work Toward Automating Sedation in Intensive Care Units","body":[{"value":"\u003Cp\u003EResearchers at the Georgia Institute of Technology and the Northeast Georgia Medical Center are one step closer to their goal of automating the management of sedation in hospital intensive care units (ICUs). They have developed control algorithms that use clinical data to accurately determine a patient\u0027s level of sedation and can notify medical staff if there is a change in the level.\u003C\/p\u003E\n\u003Cp\u003E\u0022ICU nurses have one of the most task-laden jobs in medicine and typically take care of multiple patients at the same time, so if we can use control system technology to automate the task of sedation, patient safety will be enhanced and drug delivery will improve in the ICU,\u0022 said James Bailey, the chief medical informatics officer at the Northeast Georgia Medical Center in Gainesville, Ga. Bailey is also a certified anesthesiologist and intensive care specialist. \n\u003C\/p\u003E\n\u003Cp\u003EDuring a presentation at the IEEE Conference on Decision and Control, the researchers reported on their analysis of more than 15,000 clinical measurements from 366 ICU patients they classified as \u0022agitated\u0022 or \u0022not agitated.\u0022 Agitation is a measure of the level of patient sedation. The algorithm returned the same results as the assessment by hospital staff 92 percent of the time.\n\u003C\/p\u003E\n\u003Cp\u003E\u0022Manual sedation control can be tedious, imprecise, time-consuming and sometimes of poor quality, depending on the skills and judgment of the ICU nurse,\u0022 said Wassim Haddad, a professor in the Georgia Tech School of Aerospace Engineering. \u0022Ultimately, we envision an automated system in which the ICU nurse evaluates the ICU patient, enters the patient\u0027s sedation level into a controller, which then adjusts the sedative dosing regimen to maintain sedation at the desired level by continuously collecting and analyzing quantitative clinical data on the patient.\u0022\n\u003C\/p\u003E\n\u003Cp\u003EThis project is supported in part by the U.S. Army. On the battlefield, military physicians sometimes face demanding critical care situations and the use of advanced control technologies is essential for extending the capabilities of the health care system to handle large numbers of injured soldiers.\n\u003C\/p\u003E\n\u003Cp\u003EWorking with Haddad and Bailey on this project are Allen Tannenbaum and Behnood Gholami.  Tannenbaum holds a joint appointment as the Julian Hightower Chair in the Georgia Tech School of Electrical and Computer Engineering and the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University, while Gholami is currently a postdoctoral fellow in the Georgia Tech School of Electrical and Computer Engineering.\n\u003C\/p\u003E\n\u003Cp\u003EThis research builds on Haddad and Bailey\u0027s previous work automating anesthesia in hospital operating rooms. The adaptive control algorithms developed by Haddad and Bailey control the infusion of an anesthetic drug agent in order to maintain a desired constant level of depth of anesthesia during surgery in the operating room. Clinical trial results that will be published in the March issue of the journal \u003Cem\u003EIEEE Transactions on Control Systems Technology \u003C\/em\u003Edemonstrate excellent regulation of unconsciousness allowing for a safe and effective administration of an anesthetic agent. \n\u003C\/p\u003E\n\u003Cp\u003ECritically ill patients in the ICU frequently require invasive monitoring and other support that can lead to anxiety, agitation and pain. Sedation is essential for the comfort and safety of these patients.\u003C\/p\u003E\n\u003Cp\u003E\u0022The challenge in developing closed-loop control systems for sedating critically ill patients is finding the appropriate performance variable or variables that measure the level of sedation of a patient, in turn allowing an automated controller to provide adequate sedation without oversedation,\u0022 said Gholami.\n\u003C\/p\u003E\n\u003Cp\u003EIn the ICU, the researchers used information detailing each patient\u0027s facial expression, gross motor movement, response to a potentially noxious stimulus, heart rate and blood pressure stability, noncardiac sympathetic stability, and nonverbal pain scale to determine a level of sedation. \n\u003C\/p\u003E\n\u003Cp\u003EThe researchers classified the clinical data for each variable into categories. For example, a patient\u0027s facial expression was categorized as \u0022relaxed,\u0022 \u0022grimacing and moaning,\u0022 or \u0022grimacing and crying.\u0022 A patient\u0027s noncardiac sympathetic stability was classified as \u0022warm and dry skin,\u0022 \u0022flushed and sweaty,\u0022 or \u0022pale and sweaty.\u0022 \n\u003C\/p\u003E\n\u003Cp\u003EThey also recorded each patient\u0027s score on the motor activity and assessment scale (MAAS), which is used by clinicians to evaluate level of sedation on a scale of zero to six. In the MAAS system, a score of zero represents an \u0022unresponsive patient,\u0022 three represents a \u0022calm and cooperative patient,\u0022 and six represents a \u0022dangerously agitated patient.\u0022 The MAAS score is subjective and can result in inconsistencies and variability in sedation administration.\n\u003C\/p\u003E\n\u003Cp\u003EUsing a Bayesian network, the researchers used the clinical data to compute the probability that a patient was agitated. Twelve-thousand measurements collected from patients admitted to the ICU at the Northeast Georgia Medical Center between during a one-year period were used to train the Bayesian network and the remaining 3,000 were used to test it. \n\u003C\/p\u003E\n\u003Cp\u003EIn 18 percent of the test cases, the computer classified a patient as \u0022agitated\u0022 but the MAAS score described the same patient as \u0022not agitated.\u0022 In five percent of the test cases, the computer classified a patient as \u0022not agitated,\u0022 whereas the MAAS score indicated \u0022agitated.\u0022 These probabilities signify an 18 percent false-positive rate and a five percent false-negative rate.\n\u003C\/p\u003E\n\u003Cp\u003E\u0022This level of performance would allow a significant reduction in the workload of the intensive care unit nurse, but it would in no way replace the nurse as the ultimate judge of the adequacy of sedation,\u0022 said Bailey. \u0022However, by relieving the nurse of some of the work associated with titration of sedation, it would allow the nurse to better focus on other aspects of his or her demanding job.\u0022\n\u003C\/p\u003E\n\u003Cp\u003EThe researchers\u0027 next step toward closed-loop control of sedation in the ICU will be to continuously collect clinical data from ICU patients in real time. Future work will involve the development of objective techniques for assessing ICU sedation using movement, facial expression and responsiveness to stimuli.\n\u003C\/p\u003E\n\u003Cp\u003EDigital imaging will be used to assess a patient\u0027s facial expression and also gross motor movement. In a study published in the June 2010 issue of the journal \u003Cem\u003EIEEE Transactions on Biomedical Engineering\u003C\/em\u003E, the researchers showed that machine learning methods could be used to assess the level of pain in patients using facial expressions.\n\u003C\/p\u003E\n\u003Cp\u003E\u0022We will explore the relationship between the data we can extract from these multiple sensors and the subjective clinical MAAS score,\u0022 said Haddad. \u0022We will then use the knowledge we have gained in developing feedback control algorithms for anesthesia dosage levels in the operating room to develop an expert system to automate drug dosage in the ICU.\u0022\n\u003C\/p\u003E\n\u003Cp\u003E\u003Cem\u003EThis project is supported in part by the U.S. Army Medical Research and Material Command (Grant No. 08108002). The content is solely the responsibility of the principal investigator (Wassim Haddad) and does not necessarily represent the official views of the U.S. Army.\u003C\/em\u003E\n\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EResearch News \u0026amp; Publications Office\u003Cbr \/\u003E\nGeorgia Institute of Technology\u003Cbr \/\u003E\n75 Fifth Street, N.W., Suite 314\u003Cbr \/\u003E\nAtlanta, Georgia  30308  USA\u003C\/strong\u003E\n\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EMedia Relations Contacts:\u003C\/strong\u003E Abby Robinson (abby@innovate.gatech.edu; 404-385-3364) or John Toon (jtoon@gatech.edu; 404-894-6986)\n\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EWriter:\u003C\/strong\u003E Abby Robinson\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":[{"value":"Computer System for Evaluating Sedation Level Shows Strong Agreement with Clinical Assessment"}],"field_summary":[{"value":"Researchers are a step closer to automating sedation in hospital intensive care units. They have developed control algorithms that use clinical data to accurately determine a patient\u0027s level of sedation and can notify medical staff if the level changes.","format":"limited_html"}],"field_summary_sentence":[{"value":"Researchers step closer to automating sedation in hospital ICUs"}],"uid":"27206","created_gmt":"2011-02-12 01:00:00","changed_gmt":"2016-10-08 03:08:10","author":"Abby Vogel Robinson","boilerplate_text":"","field_publication":"","field_article_url":"","dateline":{"date":"2011-02-14T00:00:00-05:00","iso_date":"2011-02-14T00:00:00-05:00","tz":"America\/New_York"},"extras":[],"hg_media":{"64242":{"id":"64242","type":"image","title":"Haddad\/Tannenbaum\/Gholami","body":null,"created":"1449176735","gmt_created":"2015-12-03 21:05:35","changed":"1475894564","gmt_changed":"2016-10-08 02:42:44","alt":"Haddad\/Tannenbaum\/Gholami","file":{"fid":"191973","name":"tbh63890.jpg","image_path":"\/sites\/default\/files\/images\/tbh63890_0.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/tbh63890_0.jpg","mime":"image\/jpeg","size":963223,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/tbh63890_0.jpg?itok=CUjwfUw8"}},"64243":{"id":"64243","type":"image","title":"Haddad\/Tannenbaum\/Gholami","body":null,"created":"1449176735","gmt_created":"2015-12-03 21:05:35","changed":"1475894564","gmt_changed":"2016-10-08 02:42:44","alt":"Haddad\/Tannenbaum\/Gholami","file":{"fid":"191974","name":"tfd63890.jpg","image_path":"\/sites\/default\/files\/images\/tfd63890_0.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/tfd63890_0.jpg","mime":"image\/jpeg","size":1179892,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/tfd63890_0.jpg?itok=VYJuHp5s"}}},"media_ids":["64242","64243"],"related_links":[{"url":"http:\/\/www.ae.gatech.edu\/community\/staff\/bio\/haddad-w","title":"Wassim Haddad"},{"url":"http:\/\/www.ece.gatech.edu\/faculty-staff\/fac_profiles\/bio.php?id=101","title":"Allen Tannenbaum"},{"url":"http:\/\/dx.doi.org\/10.1109\/TCST.2010.2042810","title":"IEEE Transactions on Control Systems Technology paper"},{"url":"http:\/\/dx.doi.org\/10.1109\/TBME.2009.2039214","title":"IEEE Transactions on Biomedical Engineering paper"}],"groups":[{"id":"1188","name":"Research Horizons"}],"categories":[{"id":"136","name":"Aerospace"},{"id":"153","name":"Computer Science\/Information Technology and Security"},{"id":"145","name":"Engineering"},{"id":"147","name":"Military Technology"},{"id":"135","name":"Research"}],"keywords":[{"id":"2082","name":"aerospace engineering"},{"id":"11910","name":"Agitation"},{"id":"11901","name":"Allen Tannenbaum"},{"id":"7780","name":"anesthesia"},{"id":"11905","name":"automated anesthesia"},{"id":"11907","name":"automated sedation"},{"id":"249","name":"Biomedical Engineering"},{"id":"11911","name":"closed-loop control system"},{"id":"594","name":"college of engineering"},{"id":"11903","name":"control algorithm"},{"id":"11904","name":"Intensive Care Unit"},{"id":"11913","name":"Maas"},{"id":"11912","name":"motor activity and assessment scale"},{"id":"11908","name":"Nurse"},{"id":"11909","name":"Nurse Anesthesia"},{"id":"171061","name":"Sedation"},{"id":"11902","name":"Wassim Haddad"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cstrong\u003EAbby Robinson\u003C\/strong\u003E\u003Cbr \/\u003EResearch News and Publications\u003Cbr \/\u003E\u003Ca href=\u0022http:\/\/www.gatech.edu\/contact\/index.html?id=avogel6\u0022\u003EContact Abby Robinson\u003C\/a\u003E\u003Cbr \/\u003E\u003Cstrong\u003E404-385-3364\u003C\/strong\u003E","format":"limited_html"}],"email":["abby@innovate.gatech.edu"],"slides":[],"orientation":[],"userdata":""}}}