Researchers in Europe have developed a new system which could help in the war on resistance to antibiotics. 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. In addition, hospital-acquired infections caused by highly resistant bacteria, such as ‘Methicillin-resistant staphylococcus aureus’ (MRSA) are also on the rise.

Furthermore, several other infectious diseases are becoming resistant to treatment, thus reducing the efficacy of care, endangering patients’ lives, and increasing the risk of epidemics.

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 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.

Dr Colaert said:

“If you monitor bacterial resistance and can see which bacteria is becoming more resistance you can switch drugs. When bacteria starts to show resistance to the new drug, say after a couple of years, you can switch again, even going back to the antibiotic that was used before, as the bacteria’s resistance to it will have been reduced.”

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.

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.

Dr. Colaert said:

“The system could be used to aggregate and analyse data from many hospitals to determine antimicrobial resistance in a region, country, or worldwide. However, in practice hospitals are reluctant to make their data available in this way.

It’s not a privacy issue, but rather the fact that hospitals do not want to disclose information that can show how good or bad they are performing. Nonetheless, in Debugit we showed that this can be done, and we believe it should be done given the huge benefits to patients, society, and healthcare systems in being able to use antibiotics more smartly.”

Furthermore, the system could also significantly reduce hospital and healthcare system costs, as less money would be spent on ineffective treatments and patient recovery would be accelerated.

Validation trials are currently being conducted at several hospitals – the University Hospital of Geneva plans to permanently incorporate the system into its HIS.

The system will allow doctors to search for information regarding a bacterial infection at the click of a button. In addition, doctors will be able to see how resistant the bacteria is to different antibiotics, and receive decision-support about the most effective drugs to prescribe for any individual patient.

Dr. Colaert explained “Other factors can also be incorporated into the decision support mechanism, such as contraindications and side effects. In fact, our proof of concept demonstrator shows step by step that the more clinical data you provide, the more accurate and effective the system becomes.”

Agfa HealthCare is considering incorporating the system into its HIS in order to provide an antimicrobial resistance monitoring solution, and as the basis for other potential applications.

Dr. Colaert said:

“The underlying technology and semantic interoperability framework is capable of doing much more than monitoring bacterial resistance. For example, we are also looking at the potential of using it to help pharmaceutical companies find patients for clinical trials.”

Written by Grace Rattue