RealOpt© – Helping Health Care Officials Make Important Decisions Quickly
Decision support capabilities for modeling and optimizing the public health infrastructure for all hazard emergency response: Exciting news on RealOpt© from AAAS – American Association for the Advancement of Science – Annual Meeting
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.
In a 2012 article from HP INPUT/OUT: “Technology is being used more frequently to save lives, whether in surgery, to safeguard the elderly, or now, in the event of a disease outbreak during a catastrophe. Faced with the potential for mass casualties, emergency managers have to make critical decisions rapidly to assess the affected populations, determine the location and size of treatment distribution facilities, appropriately staff those facilities with adequately trained personnel, and provide them with needed medicines and supplies. Technology is being used more frequently to save lives, whether in surgery, to safeguard the elderly, or now, in the event of a disease outbreak during a catastrophe. Faced with the potential for mass casualties, emergency managers have to make critical decisions rapidly to assess the affected populations, determine the location and size of treatment distribution facilities, appropriately staff those facilities with adequately trained personnel, and provide them with needed medicines and supplies.
The U.S. Centers for Disease Control and Prevention (CDC) has partnered with a research team at Georgia Institute of Technology to produce a modeling tool to help health personnel with the challenge of mass dispensing of medical supplies in an emergency. The software, known as RealOpt©, has decision support capabilities for modeling and optimizing the public health infrastructure for hazardous emergency response. It is designed for use in biological and radiological preparedness, for disease outbreaks planning and response, and for natural disasters planning. RealOpt helps officials plan for dispensing facilities locations, to ensure optimal facility staffing and allocation of resources, including routing of the population and dispensing modalities, according to Eva Lee, a professor at the School of Industrial and Systems Engineering at Georgia Tech, and director of the Center for Operations Research in Medicine and Health Care at the school.”
Fast forward to the recent American Association for the Advancement of Science Annual Meeting, and Dr. Eva Lee’s presentation of the novel software program that sifts through massive amounts of data to better optimize decision-making during the event of an emergency scenario – especially in the case of a deadly outbreak.
Envisioned and launched in 2004, RealOpt© now consists of various decision support capabilities for modeling and optimizing the public health infrastructure for all hazard emergency response, and has been used in the areas of biological or radiological terrorism preparedness, infectious disease outbreaks planning, and natural disasters response. The enterprise system consists of stand-alone software and decision support systems, including RealOpt-POD©, RealOpt-Regional©, RealOpt-CRC©, RealOpt-RSS©, and RealOpt-evacuate©. An agent-based biosurveillance and disease mitigation module is integrated within the RealOpt-POD© and RealOpt-Regional© systems.
The real-time capability of RealOpt© means that users can enter different parameters into the system and obtain results very quickly. This rapid computational time of RealOpt© facilitates analysis of “what-if” scenarios, thus it serves as an invaluable tool for planning and reconfigurations.
As detailed in an article on Fox News:
“To develop her system, Lee and her team utilized a number of data sets, including population demographics, socioeconomic information, hospital data and scientific literature regarding a range of infectious diseases – such as the flu, smallpox, anthrax, and more. With these numbers, she programmed software that can produce detailed instructions with very little input from the user.”
In the event that an infectious pathogen emerges, health officials can input into RealOpt information regarding what disease is spreading, the geographical area in need of service, and the resources at their disposal – and within seconds, the system will provide users with instructions on how to proceed.
“It could be the central command in the region, so for example, [the CDC in] Atlanta,” Lee said. “…They can say, ‘Okay, this is the affected area with 5.2 million people,’ and the system will tell them…where to put up all the medical dispensing sites where citizens can come in and get instruments to protect themselves.”
As eloquently written by Dr. Lee: “A catastrophic man-made or natural disaster can destabilize critical infrastructure, impede sanitation services, and cripple healthcare delivery systems. While it is not possible to prevent all casualties in catastrophic events, strategic and operational improvements in our federal, state and local planning can prepare our nation to deliver appropriate care to the largest possible number of people, lessen the impact on limited health care resources, and support the continuity of society and government. This would include collaborative responses in all levels of business and government to pandemic disease, catastrophic natural disasters and other large-scale public health emergencies.”
Firestorm applauds the great strides in public health response made by Dr. Lee and her team.
About Dr. Eva K Lee: Dr. Lee is a professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology, and Director of the Center for Operations Research in Medicine and HealthCare. She is also a Senior Research Professor at the Atlanta VA Medical Center. Dr. Lee earned a Ph.D. at Rice University in the Department of Computational and Applied Mathematics, and received her undergraduate degree in Mathematics from Hong Kong Baptist University, where she graduated with Highest Distinction. Dr. Lee was awarded a NSF/NATO postdoctoral fellowship on Scientific Computing, and a postdoctoral fellowship from Konrad-Zuse-Zentrum Informationstechnik Berlin in 1995 for Parallel Computation.