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Cuídat-e: a Pioneering Personalized Medicine Project Developed with GMV’s Technology

26/01/2023
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The purpose of this Spanish healthcare project is to improve personalized care for patients with chronic illnesses, cancer, and degenerative and rare diseases. It uses tools that assist with clinical decision-making to offer the public a more advanced and efficient healthcare system

Cuídat-e is one of the use cases of the Big Data Personalized Medicine project, which has a budget of €5,833,774, including €3,833,774 from the Canary Islands region (85% co‑funded by the Spanish Rare Disease Federation (FEDER), and €2,000,000 from the Valencian Community region (50% co‑funded by FEDER)

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Caring for our health is increasingly seen as a shared objective between patients and healthcare professionals, supported by a healthy physical and emotional lifestyle that includes exercise, a balanced diet, and the appropriate medical prescriptions. Artificial intelligence technology and new apps are giving healthcare professionals the ability to make better decisions, while offering patients guidance and assistance for “self-care” and for preventing new adverse episodes.

One example of this is the initiative in Spain known as Cuídat‑e, which is focused on personalized medicine and health promotion. It has been jointly developed by the public health services in the Canary Islands and Valencian Community regions, using technology from GMV. As part of the project, this multinational technology firm is responsible for developing a personalized medicine solution that brings together clinical information and information collected from the patient during everyday life, to improve clinical data and assist with healthcare decisions.

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This personalized medicine initiative will help the residents of those two regions look after their own health with a self‑care approach, while also assisting social and healthcare professionals with their work.  In addition, ongoing follow‑up will encourage healthy lifestyles and adherence to the recommendations received from doctors and other healthcare workers.

Patient participation

From the beginning, Cuídat-e has been developed in collaboration with the local residents. Their experiences are being used as a way to adjust the apps to their needs, with an initial phase included to validate the project’s suitability. The public health services from the Canary Islands and Valencian Community first invited 4,000 volunteers to participate, who were asked to provide information about their habits, nutritional profiles, exercise routines, moods, and any situations of substance use or loneliness. To record this information, the participants were given a mobile app to use 3 days a week for 5 months, and they devoted about 5‑10 minutes to using it on each of those days. In addition to those initial volunteers, anyone else living in one of those regions could also participate if interested, after signing an informed consent form.

GMV used a variety of channels to find the volunteers needed, such as by posting online notices and through short video clips recorded for social media sites like Instagram, YouTube, Facebook, and Twitter. The objective was to enroll as many participants as possible in a friendly and approachable way, with a message focused on health management in general, and on adopting healthy habits in particular. Those who volunteered were given a direct channel for communication during this first phase, which was used to answer any questions they had and provide explanations about the purpose of this pilot phase of the project. 

Cuídat-e is a good example of how technology can help improve health, by encouraging members of the public to adopt a healthier lifestyle through exercise, healthy eating, and emotional support. The apps help motivate their users to play an active role in their own healthcare, using a direct communication channel that is always available.

Artificial intelligence for clinical decision-making

The technological side of this project’s development also involves solutions that use artificial intelligence (AI) to assist with healthcare decisions, and chatbot software that simulates real conversations, as a way to help gather and record data and information. All of this has been planned and configured to be interoperable, intelligent, and secure.

As explained by Inmaculada Pérez Garro, “it is important to understand that the solutions used to assist with clinical decision-making are not isolated systems. Instead, the usage cases now being tested are designed to be integrated in a transparent manner, fully adapted to the workflows and daily needs of healthcare professionals, with an emphasis on usability”.

The project is now working on developing numerous specific uses, including:

  • Chatbots that are accessible 24 hours a day, so that users can ask questions and get information about physically and emotionally healthy lifestyles. This part of the solution will also be used to collect the personal information that is typically included in a patient’s clinical record;
  • Home monitoring of patients with complex cases, after they have been discharged from the hospital;
  • Making decisions regarding hospital admissions, by segmenting patients according to the severity of their pathologies;
  • Improving efficiency in primary care units by estimating and optimizing costs;
  • Assisting hospitals and other healthcare facilities with their needs for managing groups of patients during clinical trials and observational studies;
  • Reducing the time required for diagnosing rare diseases, by analyzing symptoms and combining data from various sources such as genealogical and clinical records;
  • Implementing an automated transcription system, known as smart dictation, which allows specialists to remain focused on the patients and their non‑verbal reactions;
  • Identifying and analyzing long COVID, including evolution of its severity and impact, together with a predictive model that allows early identification of high-risk cases and the extent of their effects, to help develop intervention programs;
  • Improving management of healthcare resources by predicting and preventing unplanned re‑admissions during the month after patients leave the hospital, and a new diagnostic system based on high-resolution pixel analysis, which can be applied to single X‑rays or electrocardiographs.

The Big Data Personalized Medicine Project (MedP Big Data) is part of the Research and Development (R&D) for Innovative Public Procurement initiative, with joint participation by the Canary Islands Public Health Service (SCS in Spanish) and the Valencian Community’s Department of Universal Healthcare and Public Health (CSUiSP in the Valencian language). It is taking place in the context of the Spanish Ministry of Science and Innovation’s Demand-Based Innovation Funding for Health program (FID Salud in Spanish), which is a funding instrument used to promote innovative public procurement initiatives. It has a budget €5,833,774, including €3,833,774 from the Canary Islands region (85% co‑funded by FEDER), and €2,000,000 from the Valencian Community region (50% co‑funded by FEDER).

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