The application of artificial intelligence to the provision of health services is a technology that can revolutionize clinical processes. However, to take full advantage of these benefits, it is necessary to overcome significant challenges such as data privacy and security, data bias, lack of transparency, regulation and governance, and lack of understanding. Finding high-quality medical data is another major challenge in implementing AI in the health sector. The sensitive nature and ethical restrictions associated with medical data make it difficult to collect them.
Since annotating a single model can require about 10,000 images, this can make processing time consuming and expensive, even when automated. While AI can enhance health and diagnostic processes by integrating automation, there are some challenges. The lack of annotated data makes it difficult to train deep learning algorithms. In addition, the black-box nature leads to the opacity of the results of deep learning algorithms. Clinical practice faces critical challenges when it comes to incorporating AI into healthcare workflows. In addition, there are challenges in the definition of personal data, in laws that regulate personal integrity, and in the risk of people being identified when the data is used for advanced computerized analysis.
The leaders emphasized that this would represent a challenge for the implementation of AI systems in healthcare. It is essential to understand the perspectives of health leaders, because they play a key role in the process of implementing new technologies in health care. Health leaders described the need for new professions and professional roles in health care for the implementation of AI systems. They also mentioned conditions external to the health system, internal capacity to manage strategic change, and the transformation of health professions and practice as challenges when implementing AI in healthcare. It must be easy to use and generate value for patients and health professionals. However, when implementing AI technology in practice, certain problems and challenges may require an optimization of the method in combination with the specific configuration.
Health leaders described managing existing laws and policies for the implementation of AI systems in healthcare as a challenge and a problem that was essential to address. It is crucial to involve and collaborate with stakeholders and users of the regional health system itself and with other actors outside the organization in order to develop and apply systemic thinking on the implementation of AI. Health leaders also agreed that the county council should collaborate with companies in implementing AI systems and should not manage such processes on its own.
