Your city has 48 hours to vaccinate every man, woman and child to prevent a dangerous pandemic. Where do you put the clinics, how many health care workers will you need and how do you get 2 million people to a finite number of emergency clinics?
The logistics of handling all those panicked people, health care workers, vaccinations, clinics and forms are dizzying. And while health departments have plans in place, it’s very difficult to know how well those plans will perform when time is critical and the minutes needed to move patients to a large clinic or for a frightened patient to fill out a form could mean life or death for thousands or millions of people.
Now researchers at Georgia Tech have developed a computer program, based on a clinical model created by the Centers for Disease Control and Prevention (CDC), to help U.S. state, city and county health care departments create and test more efficient plans for treating infectious illness, whether it’s a natural or man-made outbreak.
The program, called RealOpt and created by Dr. Eva Lee, an associate professor of industrial and systems engineering at the Georgia Institute of Technology, will be installed over the next few months at health departments across the state of Georgia and health departments in 35 other states have plans to test the program. While the program is still in the testing phase, it will soon be available free to any government health department that requests it from Georgia Tech.
RealOpt has been tested by the DeKalb County Health Department in Georgia, and the county ran a very successful anthrax drill last year. Lee used RealOpt to help DeKalb test and improve its existing bioterror preparedness plan.
RealOpt takes the numerous variables associated with a health care department’s treatment of a very large group of people, and through large-scale simulation and optimization (even considering variables such as panic and language barriers), pinpoints the most efficient way to move patients to and through a facility. Using the program, a health care department can determine the best location for emergency clinics based on population density and road accessibility, the most efficient facility layout, the number of health care professionals needed in certain areas, the number of vaccinations needed and the time it will take to treat patients.
RealOpt can be used to prepare for a possible outbreak, as well as for emergency re-assignment of health care workers within the clinic and between clinics during an actual outbreak. By being able to assess preparedness, health departments will have more a precise estimate of the resources and funds needed to treat communities before an actual outbreak.
In addition to its role in planning, one of RealOpt’s significant advantages is its ability to process data in real time as the emergency treatment occurs. As patient flows fluctuate, the program can determine how to reallocate the facility’s resources in a fraction of a second, sending more doctors or nurses to one station or more attendants to the paperwork processing area.
“Rapid analysis of scenarios not only allows for large-scale planning and preparedness, but also allows on-the-spot optimization to maintain the best resource allocation over time,” Lee said. “As patients enter and progress through the clinic we can observe the flow and dynamically adjust the configuration as needed. This is also critical for response to catastrophic events, for example, if one treatment site collapses.”
RealOpt also includes an automated facility-layout drawing tool that allows health care workers to design and analyze their own clinic layout in response to various emergency situations, such as anthrax, smallpox, flu pandemic or natural disaster.
Lee continues to add to RealOpt’s capabilities, and is currently adding a disease propagation component to the system. The addition would help to analyze the disease’s spread within treatment sites and possible ways to halt or minimize the spread. It will also determine how to redirect patients should one center need to be quarantined or closed to prevent further spread of a disease.
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