Researchers at Georgia Tech 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’s level of sedation and can notify medical staff if there is a change in the level.

“ICU 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,” 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.

During 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 “agitated” or “not agitated.” 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.

“Manual sedation control can be tedious, imprecise, time-consuming and sometimes of poor quality, depending on the skills and judgment of the ICU nurse,” said Wassim Haddad, a professor in the School of Aerospace Engineering. “Ultimately, we envision an automated system in which the ICU nurse evaluates the ICU patient and enters the patient’s 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.”

This 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.

Allen Tannenbaum and Behnood Gholami are working with Haddad and Bailey on this project. Tannenbaum holds a joint appointment as the Julian Hightower Chair in the School of Electrical and Computer Engineering and the Department of Biomedical Engineering, while Gholami is currently a postdoctoral fellow in the  School of Electrical and Computer Engineering.

This research builds on Haddad and Bailey’s 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 IEEE Transactions on Control Systems Technology demonstrate excellent regulation of unconsciousness, allowing for a safe and effective administration of an anesthetic agent.