Jan-Joost Eveleens

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AAMC (2018) expects the United States expects to have a shortage of 120,000 doctors by 2030. One can expect that this will cause trouble in the availability and quality of health care in the United States. However, it is not just the United States or the western world that can expect this kind of trouble. By 2030, the global shortage in health workers is expected to be around 15 million (Liu et al., 2017). Luckily, new technologies can help solving this major problem. One of these technologies is Ada, an application that can partly replace the general practitioner.

Ada is an application that is available in the App Store and the Play Store. By asking a series of questions on personal details (e.g. gender, age) and medical complaints, it tries to do an assessment on which disease the user might have. The mission of Ada is to make personalized healthcare available to everybody in this world. At this stage, more than 4 million people have used Ada and a new assessment is made every 3 seconds.

Ada is especially helpful to people in third-world countries who are unable to see an educated doctor to discuss their troubles. However, the application can save a lot of time for doctors in more developed countries too. The general practitioner often only functions as middleman between the patient and a more specialized doctor. Cutting out this step and directly seeing a specialized doctor can save a lot of time for both parties.

Of course, Ada lacks basic human intuition and cannot see the real situation of a patient. This will surely lead to errors, which is a serious issue. However, Ada can stay up-to-date when it comes to the thousands of new developments in all kind of medical areas, while a general practitioner can only learn as much as one human can. Ada will not cure our problems, but it can at least help determining what our problems are.

References

AAMC. (2018). New Research Shows Increasing Physician Shortages in Both Primary and Specialty Care. Retrieved from https://news.aamc.org/press-releases/article/workforce_report_shortage_04112018/

Liu, J. X., Goryakin, Y., Maeda, A., Bruckner, T., & Scheffler, R. (2017). Global health workforce labor market projections for 2030. Human resources for health, 15(1),

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As the world becomes more connected, diseases are able to spread more rapidly. To prevent this from happening, the World Health Organization (WHO) has used various Epidemic Intelligence Tools over the last couple of decades. By monitoring various data sources, these tools try to detect future epidemics and monitor current outbreaks. These tools are becoming increasingly important to fight diseases and save lives. In 2017, the Epidemic Intelligence from Open Sources (EIOS) initiative was launched by WHO. The system was released on August 6^th, 2018 and had already proven to be valuable.

Epidemic intelligence works in a continuous cycle of 8 steps. The first step is the collection of data from various sources. Examples of these sources are social media, national surveillance and laboratory networks. After the data is collected, it is processed to make sure that duplicate data is deleted and the data is linked to the correct diseases and locations. Thereafter, the system tries to detect patterns which suggest disease outbreaks. These possible outbreaks then need to be verified by lab confirmation, field verification or credible local sources. The situation gets analysed and the risk is determined. After making a visual representation of the current (and future) situation, action is taken if necessary. As new data is collected continuously, this cycle never stops.

The key feature from the new EIOS system is the large number of data sources. Over 8000 data sources are used to detect over half a million pieces information per month. This leads to 7000 signals, which are manually screened for relevance by the staff of WHO. After investigation, 100 events are investigated and 10 risk assessments are made each month.

During the first weeks that the EIOS system has been used, it has already detected several outbreaks which would have been detected in a later stage otherwise. For example, the cholera outbreak in Algeria and the leptospirosis outbreak in India have been detected in an early stage, enabling WHO to react quickly and save lives. These cases show demonstrate the potential to use data to improve global health.

Over the next period of time, WHO plans to further improve the EIOS system. One of the main priorities is to use speech-to-text technology to include radio sources to the system. This is especially valuable in poor regions, where radio still is one of the main methods of communication. Features like this could help WHO to further improve EIOS and save more lives.

This article is based on a presentation by Dr Oliver Morgan, Director Health Emergency and Risk Assessment – WHO Health Emergencies Program. Dr Oliver Morgan was one of the speakers at Intelligent Health 2018, an international congress on the use of artificial intelligent in health care. For more information about Intelligent Health, visit https://intelligenthealth.ai/

This presentation is not online accessible. However, a similar PowerPoint presentation can be found at: http://www.oie.int/eng/BIOTHREAT2017/Presentations/6.2_BARBOZA-presentation.pdf
Please note that this is not the version of that was used at Intelligent Health on September 13^th 2018.

Article on cholera outbreak in Algeria: https://www.aljazeera.com/news/2018/08/algeria-person-dies-cholera-outbreak-180825173701802.html

Article on leptospirosis outbreak in India: https://www.news18.com/news/india/as-leptospirosis-threat-looms-after-floods-kerala-plots-30-day-micro-plan-1860783.html

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