For years, Low- and Middle-income Countries (LMICs) – Mexico being one of them – have faced an epidemic of chronic noncommunicable diseases (NCDs), such as diabetes, hypertension, obesity and lipid disorders. This means that people with these diseases may not be aware of this, as conditions are discovered after several studies and symptoms do not manifest very clearly. This demonstrates the need for broader studies, testing and screening programs.

Carlos Slim Foundation created an initiative called Integrated Measurement for Timely Detection (MIDO), a proactive NCD detection and prevention policy that uses Big Data and Artificial Intelligence to create a a broad portfolio of accurate information that supports diseases such as hypertension or diabetes through clinical registration systems that classify, analyze and track potential threats.

The foundation set out to collaborate with the Mexican Secretariat of Health and has already evaluated more than 500,000 patients who would not have been screened.

The creation of MIDO has helped to restructure existing detection programs and expand them. They have been modernized and finally learned how to systematize strategies and incorporate appropriate lifestyle changes through counseling.

The following study of the implementation of the MIDO program in Mexico suggests that primary and secondary prevention programs in other Low- and Middle-income Countries should consider the application of this method in their health systems. Undoubtedly, this will provide better population-based detection targets, focusing mostly on the pre-disease stages and simplifying the transition between detection, diagnosis confirmation and incorporation of Patients.