On September 28, 2014, Thomas Eric Duncan became the first patient in the US diagnosed with Ebola. He died on October 8, 2014. On October 12, one of his caregivers tested positive for Ebola. The tragic reality is that both Mr. Duncan’s death, and the transmission of his disease, might have been prevented through the use of readily available clinical surveillance software.
Three days prior to his diagnosis, Mr. Duncan had gone to the emergency room at Texas Health Presbyterian Hospital with a fever, after recently traveling to Liberia, implying significant risk for Ebola. However, the healthcare professionals at Texas Health failed to recognize the risk, and failed to take the necessary actions, including admitting and isolating Mr. Duncan. In fact, they discharged Mr. Duncan – a terribly dangerous diagnostic error.
Diagnostic errors contribute up to 80,000 deaths per year in the US. Unfortunately, this particular error may turn out to be extremely dangerous. In hindsight, these types of errors are preventable through the application of clinical surveillance using business rules management software.
In this case, as in so many others, we trust the healthcare community to make the right diagnosis. But, in the rush to treat patients, it’s very easy to make mistakes. That is why we must leverage the power of software to aid healthcare professionals to prevent these mistakes. Long ago, the airlines added pre-flight safety checks and auto-error detection software to help pilots diagnose and prevent errors. It’s time that the healthcare community adopted the same.
Of course, the business rules governing healthcare are far more complex than those governing the airline industry. Fortunately, software is available that can handle even the most complex business rules. This software, known as “Business Rules Management Systems” or “rules engines” can be used to monitor patient data (called clinical surveillance), and provide alerts to healthcare workers when risks are identified.
For example, rules engine software can alert ER triage nurses to ask all patients with fever about their travel history or contact with recent travelers. And, if a risk is identified, the rules engine can immediately trigger the appropriate clinical recommendations within the electronic medical records systems.
I know a little about this topic. I’m a former ER physician who left medicine in 2000 to build a rules engine and deliver on the vision of clinical surveillance. The first applications of Corticon Business Rules Management System were in clinical surveillance. But, due to a variety of reasons, product adoption grew much faster in other industries, including banking, insurance and government. Corticon is now used by organizations such as eBay, Unum and DBS to help with their data surveillance and decision making.
Another interesting use case that comes to mind is Progress customer Carego, which used our Rollbase rapid application development software to create an app that provides clinic staff with complete and immediate access to patient health information, without the need for bulky and unreliable paper filing – which means faster, safer and more personalized care in even the most remote areas of the world. Something like Rollbase, combined with Corticon, could really change the the game for early diagnosis of diseases like Ebola.
And, though we are seeing growing adoption by the healthcare industry of these types of technologies, it’s at a slower rate than I’d hope. Especially when lives are on the line.
Dr. Mark Allen is a Progress General Manager, dedicated to advancing business automation and passionate about applying technology to improve the world. In 2000, he founded Corticon, later acquired by Progress in 2011. Under his leadership, Corticon became a leading independent business rules platform with hundreds of customers in diverse industries such as financial services, government, healthcare and insurance. Prior to founding Corticon, Dr. Allen developed rules-based systems to help physicians make better patient care decisions. Dr. Allen has a B.S. in Applied Physics from Columbia University, and an M.D. from the University of California Los Angeles.
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