The revolution brought about by the introduction of artificial intelligence affects all areas of activity. Some of them, such as banking, telecommunications or industry, have been using artificial intelligence algorithms and advanced analytics for many years to improve decision-making and automate their activities. However, in healthcare, AI is usually associated with cutting-edge research, such as evidence-based research (RWE, Real World Evidence), usually conducted by large pharmaceutical companies or large equipment manufacturers. companies. This is already having a very positive impact, for example in supporting the early diagnosis of diseases or the development of new drugs. But these technologies still have little presence in the daily lives of healthcare workers, managers and patients.

Fortunately, we are now living in a time when this is about to change radically. The sector is investing in the implementation of data management platforms (known as “data lakes” or “data lakes” in English) that enable the development of use cases (analytic models applied to solve a specific problem) that doctors can use in their daily lives. A real example developed in Spain is a model that allows you to predict the date of birth with high probability. Until now, this has been done on the basis of information obtained from a screening ultrasound of the first trimester of pregnancy. Now, by incorporating other data sources into the model, such as the patient’s medical history and the results of her diagnostic tests during pregnancy, a personalized date prediction can be made. This has a direct benefit for her, since it allows her to anticipate when that long-awaited moment will come and be better prepared for it. But at the same time, it has an impact on the health system because it allows, for example, to reduce the number of induced births – a procedure that is now used in many hospitals for any pregnancy exceeding a certain number of days.

Although we often talk about “big data,” in many cases in healthcare, great advances can be made by working with existing data that is not necessarily voluminous. A good example of this is the optimization of a hospital’s emergency services. In emergency situations, as in other areas of the hospital, the use of coding based on the International Classification of Diseases (ICD-10) allows us to collect all relevant information about each patient who contacts the service. Based on this data, the use of analytics and artificial intelligence makes it possible to understand the work of the emergency service and predict the number of patients in the coming days, in what specialties and how many of them may need to be seen. This makes it easier to make the right choice between different services, ensuring better quality of care and patient experience, and helps reduce the burden on healthcare professionals.

The intensive use of data analytics and artificial intelligence is aimed at realizing the concept of so-called personalized precision medicine, in which care and treatment are tailored to the characteristics of each patient. Incorporating genomic information along with the data sources mentioned above, such as medical history and the results of increasingly accurate diagnostic tests thanks to AI, allows the development of personalized predictive models. All this contributes to the advancement of medicine based on health promotion and prevention, improving quality of life and reducing the burden on the healthcare system.

To bring this vision to life, it is necessary not only to have data platforms, but also to ensure the so-called “data governance”: a set of processes and procedures aimed at guaranteeing the quality of data and the traceability of its use. and your privacy. “Data governance” is a way to achieve “data democratization,” whereby any healthcare professional can access the data needed to make the best decisions for a patient. To succeed, this government must be accompanied by a transformation plan that promotes a data culture and drives change in the way professionals work, helping them develop new capabilities. Thanks to the financial support of European funds and available technologies, there are no more excuses: now is the time of healthcare.

Carlos Martinez Miguel He is the Global Director of Artificial Intelligence and Big Data Solutions and Services at Telefónica Tech.