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RHEA: modeling healthcare policy and its regional effects

To some, hospitals can seem like manmade incubators for bacteria and viruses, and for good reason. The US Centers for Disease Control and Prevention (CDC) reported in September that one in every 20 hospitalized patients contracts a hospital-acquired infection.While it’s true hospitals can be a source of risk, many facilities take routine measures to prevent the spread of infection. Even so, when patients regularly enter and exit hospital systems, they run an increased risk of acquiring and spreading infection.

Bruce Y. Lee, associate professor in international health. Image courtesy Johns Hopkins Bloomberg School of Public Health.

In healthcare facilities, VRE (vancomycin resistant enterococci) is one of the most common bacteria to cause infection. There are an estimated 20,000 to 85,000 cases of VRE infection in US hospitals each year. Staph (staphylococcus) is another common infection. For most individuals, neither is particularly harmful. In fact, VRE is common in the urinary track and intestines, and Staph is common on the skin or in the nose of even healthy people. However, given their high resistance to antibiotics, these bacteria can be lethal to those with a compromised immune system.

US researchers from the Johns Hopkins Bloomberg School of Public Health in Maryland, Pittsburgh Supercomputing Center (PSC), the University of Pittsburgh, and the University of California, Irvine, US, have created the Regional Healthcare Ecosystem Analyst (RHEA) – a mathematical and computational modeling tool designed a mathematical and computational modeling tool designed to track the movement of patients carrying pathogens like VRE among healthcare facilities. The team used RHEA to develop a simulation of the patients, facilities, and community in Orange County, California.

“VRE can readily spread from one facility to another by sharing patients, even when those facilities are many, many miles apart,” says Bruce Lee, MD, MBA, an associate professor in international health at Johns Hopkins Bloomberg School of Public Health and lead author of the study published in the August 2013 issue of the American Journal of Infection Control.

As a matter of policy, many hospitals take precautionary measures – like contact isolation or decolonization using special soaps and topical applications – to eliminate infection occurrence and spread. “We can model those procedures and how following them rigorously in one hospital may affect surrounding hospitals in the network,” explains Shawn Brown, director of public health applications at PSC. “Conversely we can look at hospitals that are not rigorously adhering to preventative policies, and see how it affects the hospitals that do.”

Pathogens such as methicillin-resistant Staphylococcus aureus (above) develop vulnerabilities as they evolve resistance to antibiotics. Choosing antibiotics that exploit these weaknesses can thwart resistant bacteria. Image courtesy

Nursing homes in the county add another dimension to the hospital network. Patients regularly leave nursing homes and enter various regional hospitals, only to eventually return to the nursing home and often begin the cycle all over again at the same or another hospital.

What makes the RHEA model so powerful is its detailed representation of the interconnected system of health care facilities. You can observe, as patients are transferred from one hospital to another, their chances of having an infection and how that affects the hospital they are being transferred to, and finally how it impacts the regional hospital system. “VRE control is every hospital’s concern. As long as one hospital in your region is struggling with VRE control, your hospital is at risk,” Lee says.

Lee’s analysis drew upon real patient data from 29 hospitals. His results show that a mere 10 percent increase in VRE at a single hospital can produce a nearly 3 percent increase in every hospital countywide. “Active and close communication among health care facilities is important since an outbreak could quickly go from one hospital’s problem to a whole county’s problem without an expeditious response and control efforts,” he says.

Brown says the team is looking at visualizations and interfaces that will enhance model interaction. The goal is for RHEA to become a decision support tool that makes it easy for decision makers to populate and run the model. “While this sort of computational modeling is fundamental in finance, manufacturing, meteorology and other fields, it is relatively new in public health, where its impact could be substantial” Lee adds.

The CDC’s Threat Report, Antibiotic resistant threats in the United States, 2013, provides a snapshot of the burden posed by antibiotic resistant germs. Data shows that most deaths related to antibiotic resistance happen in healthcare settings such as nursing homes and hospitals. At the same time, the number of new drugs entering the market is steadily shrinking.

For every 5,000 to10,000 compounds that make the drug discovery stage, only one will actually receive US Federal Drug Administration approval. The cost to develop just one new drug is close to $800 million and can take anywhere from 10 to 15 years.

While drug makers are focusing on profitability, bacteria are gaining survival ground - many generate in a few hours or less – by developing even more advanced adaptations. This scenario makes policies and procedures to reduce the occurrence and spread of infection a critically important step in containment. RHEA is a tool for improving the way these healthcare services are administered, and ultimately the lives of millions of people.

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