*By Allan Conti
In Brazil, the use of Artificial Intelligence in healthcare is showing a growing trend among private hospitals, considering that 821% of institutions already offer AI resources or solutions for pre-established processes. This indicates that the sector is increasingly updating itself and seeking innovations to improve the quality of patient care, from diagnosis to treatment, while optimizing workflows and internal processes within organizations.
The initial data, present in Research on quality, patient safety, and the importance of clinical decision support tools., A study by the National Association of Private Hospitals (ANAHP) in partnership with Wolters Kluwer reveals a greater engagement of professionals and institutions in adopting these tools, whether due to competitive pressure or the promise of efficiency, with the main objective of reducing variability in care in order to improve patient outcomes and optimize the management of financial resources in companies.
This reflects the speed at which new technologies are being developed and implemented in business. A paper from the University of Rochester in partnership with NYU Langone Medical Center traced the history of AI, dating its emergence to 1950.
History and evolution of Artificial Intelligence in healthcare.
The study points out that, at that time, the early models presented limitations for the health sector that were only overcome in the early 2000s with the deep learning. With the evolution of technology, healthcare institutions have begun using AI for more accurate searches and pattern recognition. Currently, with Artificial Intelligence systems capable of analyzing and learning from data, these tools are gaining new ground within the sector.
Today, the adoption of AI tools is driven by the need to balance increased process efficiency with reduced operating costs. They emerged as an opportunity to address the excess demand in healthcare systems and are present in areas ranging from administration to direct patient care, through resource management, electronic health records, interactive chatbots, access to test results, and more.
However, when it comes to the arrival of Generative Artificial Intelligence (Gen AI), it promotes a highly relevant transformation for healthcare. The sector, which was previously characterized by focusing on technical advancements, is now turning its attention to the dynamism and personalization of care.
AI Gen presents a context for generating knowledge through interaction with machines. The technology is capable of creating summaries, supporting medical education, continuous training and decision-making, direct interaction with patients and professionals, generating detailed reports with diagnostic and treatment hypotheses, and assisting the administrative area in managing regulatory documents. In this sense, the relationship with this tool can revolutionize how the healthcare sector operates, provided it is developed and used responsibly, linking technological advancement to evidence-based practices.
Complexities of integrating Artificial Intelligence in healthcare.
So far, this implementation has been carried out cautiously. According to the report ICT Health 2024, The adoption of Generative AI among physicians in Brazil was 17%. However, when considering collective use, this number reaches only 4% of healthcare facilities. As the process of engaging with the technology is still in an early stage, it is not possible to fully understand the positive and negative aspects of the full integration of AI and Generative AI tools into the healthcare field.
One of the main challenges in applying Artificial Intelligence in healthcare concerns costs and the preparedness of healthcare teams. This is a resource that requires greater training for professionals, and 74% from private hospitals still feel poorly prepared to apply this technology in clinical areas, according to research by ANAHP with Wolters Kluwer.
The growing popularity of AI in institutions also directly impacts university education, as well as the advanced IT infrastructure and sustainable optimization of its energy consumption necessary to maintain this operation—factors that involve significant expenses for implementation.
Another significant bottleneck in the integration of AI in healthcare and the corporate world as a whole is the ethical question. Implementing this resource is a process that involves ethical and legal responsibilities, as it needs to comply with data security and protection. Furthermore, the information requires continuous monitoring to ensure compliance with mandatory legislation and standards.
Future with AI
Artificial Intelligence in healthcare has proven to be an important tool for advancing the quality of care, especially when supported by reliable content. Projections for the future indicate that the use of AI Gen should increase and chat applications will become key players in the Healthcare 5.0 scenario.
In this context, the responsibility of institutions also includes seeking out solutions that have a database with scientifically curated references, capable of providing reliable guidance that contributes to the practice of Evidence-Based Medicine (EBM) and offers support not only to clinical decisions, but to business operations as a whole.
Therefore, with well-established, reliable standards and foundations, healthcare can minimize inconsistencies and errors while becoming more efficient and personalized.
*Allan Conti is Commercial Director of Wolters Kluwer Health in Brazil.
Notice: The opinion presented in this article is the responsibility of its author and not of ABES - Brazilian Association of Software Companies
