Grace Rattue reports that, "Researchers in Europe have developed a new system which could help in the war on resistance to antibiotics" using ICT technology and a semantic interoperability framework. Rattue explains, "According to the World Health Organization, approximately 440,000 new cases of multidrug-resistant tuberculosis emerge each year, resulting in at least 150,000 deaths… Dr. Dirk Colaert, Chief Medical Officer at Agfa HealthCare in Belgium, said: 'Clinically, antimicrobial resistance is a huge challenge. Pharmaceutical companies simply can't come up with new antibiotics fast enough to counter the resistance of bacteria to existing antibiotics and medications. By definition, it's a war that can't be won by antibiotics alone.' Antibiotic resistance occurs when strains of bacteria in the human body evolve and adapt to resist the treatment. The resistance is made worse by some factors, such as the improper use and abuse of antibiotics. Dr. Colaert explained 'On top of new antibiotics, we need new tools to apply antibiotics more smartly'."
The article goes on, "The researchers' system is simple: use data from different hospitals to monitor antimicrobial resistance and identify trends showing which types of bacteria are becoming resistant to certain types of antibiotics. With this data, the researchers can then implement courses of treatment with more effective drugs… However, implementing the Debugit system is challenging. Some hospitals monitor patient data and conduct lab tests (antibiograms) for antimicrobial resistance. The researchers note that often the data is incomplete and stored in different formats and systems, thus making it difficult to analyze the data."
Rattue continues, "Dr. Colaert explained 'The main challenge is the poor quality of clinical data. In an ideal world you have nicely coded and structured data, but in reality you have to deal with free text and incomplete data.' In order to overcome this challenge, the investigators used ICT technology (information and communications technology) as well as a semantic interoperability framework to extract data from hospital information systems (HIS), and use it to determine trends in antimicrobial resistance."
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