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Diego Jaimes, a rheumatologist specialized in epidemiology, explains how artificial intelligence is transforming the management of patients with chronic diseases
Artificial intelligence (AI) has opened a new field in healthcare, enabling more efficient management of large amounts of data and improving clinical decision-making. In this context, Diego Jaimes, a rheumatologist with over a decade of experience in epidemiology, has worked on implementing AI and advanced analytics to enhance the treatment of patients with chronic and complex conditions.In a recent interview with Laura Velásquez for AiHeroes, Diego Jaimes shared his experience on how AI and other technologies are helping to transform the healthcare sector. Throughout this blog, we will delve into the key points Diego Jaimes highlighted, from adopting technological tools to the challenges the industry faces in optimizing healthcare.
For Diego Jaimes, artificial intelligence is “a world to explore and develop.” His focus has been on implementing AI as a key tool to improve patient care, especially for those with chronic diseases. Throughout his career, he has worked at the intersection of medicine and technology, merging clinical research with business development in the healthcare sector.In his conversation with Laura Velásquez, Diego Jaimes explained that what initially caught his attention was AI's ability to predict and analyze large volumes of data. Traditionally, medicine has been considered a profession of "means and not results," but with the advent of AI, predictions have become more accurate, opening new opportunities to directly apply these advances in patient treatment.
One of the challenges Diego Jaimes has faced in his work is implementing advanced analytics and AI tools in the clinical setting. The transition from paper records to electronic records was a fundamental step, but it also required significant investment in technology and the development of new workflows.Diego Jaimes mentions that interconnection and associated costs were significant barriers at the beginning. Although they spoke with major tech companies like Google and Microsoft, their solutions were more focused on the business realm, making it difficult to adapt them to the specific needs of healthcare institutions.However, despite these obstacles, Diego Jaimes and his team began to develop their own solutions, allowing them to advance in the implementation of descriptive and predictive analytics. This "learning by doing" approach enabled them to develop solutions that address patients' real problems, although it was not always an easy path.
Diego Jaimes emphasizes the importance of alignment between clinical teams and data developers for AI to work properly in medical practice. Without this alignment, projects tend to fail, as he experienced in one of his early attempts to implement AI solutions for a client.In his interview, Diego Jaimes explained how the lack of communication between the data team and the clinical team resulted in a solution that did not meet patients' real needs. Although the tool was technically well-developed, the clinical team continued to use Excel for their analyses, underscoring the need to ensure that all parties clearly understand the project’s goals.To avoid these issues in the future, Diego Jaimes recommends maintaining constant feedback between the various actors involved in developing healthcare technologies. This not only helps ensure that the solutions are appropriate but also allows for quick adjustments to any problems before the project is too advanced.
One of Diego Jaimes' key focuses has been treating patients with multiple and complex conditions, particularly in an outpatient setting. In his interview, he discussed how high complexity has historically been associated with hospitals and surgical interventions, but there are many needs for these patients that can be managed outside of the hospital.In this sense, artificial intelligence has played a key role in facilitating the continuous monitoring and care of patients. Diego Jaimes mentioned how telemonitoring and technological solutions can help improve patient adherence to treatments, not only in terms of medication but also in attending appointments and performing necessary tests.
Although AI is already having a positive impact on healthcare, Diego Jaimes believes there are still many challenges to overcome. One of the most important is creating a clear regulatory framework that defines how artificial intelligence solutions should be implemented in healthcare. The lack of regulation could lead to the development of solutions that do not meet ethical standards or that jeopardize patient data privacy.Diego Jaimes emphasizes the need to establish a regulatory board that oversees the development of AI technologies in healthcare, ensuring their responsible use. Moreover, he believes the industry needs more training so that healthcare professionals can use these tools effectively.
Finally, Diego Jaimes highlights the importance of staying up to date with technological advances in healthcare. As AI evolves rapidly, it is essential that doctors and researchers remain informed about the latest trends and available tools. Diego Jaimes recommends sources like the New England Journal of Medicine, which has a section dedicated to artificial intelligence applied to medicine, as an effective way to stay current.Continuous learning and training in new technologies are key for doctors to use AI effectively in their clinical practice, which in turn improves patient outcomes.
