GMV contributes with its technology to disease prevention and adherence to a healthy lifestyle
The technology multinational GMV has finalized the technological developments that will enable the healthcare services in the Canary Islands and Valencia to promote personalized and precision medicine using big data and artificial intelligence (AI) in healthcare and the promotion of healthy lifestyles.
GMV has worked on the Medicina Personalizada Big Data (MedP-Big Data*) project in two phases. In the first phase, eight use cases were developed with competitive dialogue with two other companies. Three focused on analyzing the capabilities of predictive analytics, based on natural language processing (NLP) and image and data processing. The other five focused on promoting healthy habits by developing an app called Cuidat-e, which involved the participation of over 4,000 voluntary individuals from the Canary Islands and the Valencian Community.
This app collects information about users' eating habits, physical activity, emotional state, possible addictions, or unwanted loneliness to personalize healthy habit recommendations for each user profile. It also provides access to healthy menus and recipes, physical activities, and tailored recommendations and tracks trends in eating, exercise, and mood.
The large volumes of data—technically referred to as big data—processed in the project are a valuable asset from which evidence can be extracted by applying AI, thereby assisting healthcare professionals in clinical decision-making. Specifically, this technology will be crucial for earlier diagnosis of patients with prevalent pathologies or rare diseases. It will also assist in direct and remote care by healthcare professionals and alternative virtual assistance systems.
It is worth noting that, in the second phase, the project continued to be implemented with GMV as the sole contractor, covering up to 10 additional use cases and expanding on some of the use cases from the previous phase, such as the Cuidat-e case, with the same objective: improving personalized care by using artificial intelligence and big data.
Significant examples of innovative technologies and use cases in this second phase include the development of bots for pre-consultation or telephone follow-up with patients, support for patients with clinical prescriptions to reduce drug consumption, tools to speed up the pre-selection of candidates for studies or clinical trials, and the transcription of consultations using an intelligent voice recorder.
Applications of artificial intelligence and big data
For the project's completion, the Department of Universal Healthcare and Public Health, together with the Canary Islands Health Service and the Barcelona Supercomputing Center, recently hosted an Infoday on artificial intelligence to present the MedP-Big Data results. The developed tools were explored in-depth, such as the app for monitoring chronic patients, which can engage in real-time text or voice conversations through a chatbot or telephone bot that provides advice for both users and professionals. It is worth noting that applying artificial intelligence to people's interaction with the healthcare system facilitates greater accessibility and better guidance in the work carried out by healthcare professionals.
Another application, the intelligent pre-consultation, provides the healthcare professional to have data from the patient's medical history or information collection before the patient visits the clinic. Prior to the visit, the patient, assisted by a chatbot, provides important information to the healthcare professional, allowing the doctor to have more time and improve the medical history. In addition, the smart dictation or automated transcription system developed by GMV offers the possibility to focus on the patient instead of taking notes, as the conversations held during the consultation are automatically transcribed. As a result, after the consultation, the doctor only needs to review the transcript and make any necessary checks before approving it for inclusion in the patient’s medical record.
Inmaculada Pérez Garro, Director of Digital Health at GMV, stated during her participation in the Infoday that "the application of natural language processing (NLP) technologies in the healthcare environment is a means to streamline care processes between the public and professionals. This technology will improve accessibility to healthcare services and, consequently, contribute to the sustainability of healthcare services, especially in primary care.”
Another use case developed by GMV is focused on analyzing medical images using AI. The automatic processing with AI of simple chest X-rays and lumbar magnetic resonance imaging has achieved useful results both for screening, to identify individuals at high risk of acquiring a disease or disorder, and for getting a second opinion. Similarly, the analytical tools developed to identify patients at higher risk of hospitalization or readmission after discharge will contribute to higher-quality healthcare and optimal resource management. They are also of highly useful in conducting screenings in emergency departments.
In the AI application developed to detect rare diseases, combinations of signs and symptoms have been identified that, individually, would not lead to early diagnosis. However, when certain sequences and associations are performed with advanced analytics, early diagnosis and treatment can be implemented, while achieving more accurate tests.
In her presentation during the Infoday, Inmaculada Pérez Garro also emphasized that “healthcare services should rely on the analysis of data from the public and patients to prescribe services aimed at more personalized and precise medicine, while being sustainable thanks to the digital transformation.” According to her, the MedP-Big Data project has been of outstanding value in establishing the cycle of AI development and implementation in current healthcare services. She considers it is essential for there to be ongoing cooperation between the two autonomous communities and their healthcare systems with technology companies and specialized professionals: technology teams, healthcare professionals (doctors, nurses, psychologists, nutritionists), and sports professionals, etc. It serves as an example of a high-priority national project. “The digitization of healthcare centers means that professionals can use of intelligent decision support systems and continuously monitor patients both at the centers and elsewhere. And of course, in prevention, it serves as a health promotion school for the public in general."
The project has brought together many use cases, and now the task is to determine whether they should be implemented. The Canary Islands Health Service and the Department of Universal Health and Public Health of the Valencian Generalitat are interested in sharing the results gathered with other communities. Consequently, the Barcelona Supercomputing Center (BSC), in coordination with the Secretary of State for Digitalization and Artificial Intelligence, has promoted the Infodays in different autonomous communities to publicize the opportunities provided by NLP-based tools to improve healthcare quality and efficiency.
(*) The Medicina Personalizada Big Data project, as part of the Public Procurement of Innovation through the FID Salud Program, has been co-funded by the European Regional Development Fund (ERDF) with 85% of the budgeted 3,833,774 euros for the Canary Islands Health Service, and 50% of the budgeted 2,000,000 euros for the Generalitat through a grant from the Ministry of Science and Innovation totaling 4,258,707.90 euros.
