Digital Transformation in Healthcare and Nephrology.

Area of Science:

• Digital Health
• Medical Informatics
• Artificial Intelligence in Medicine

Background:

• Current medical workflows, particularly in nephrology, are hindered by manual tasks and a lack of interoperability.
• This digital fragmentation impedes the creation of high-quality, structured data essential for artificial intelligence (AI) development.
• The focus on advanced AI tools overshadows the fundamental need for digital transformation in clinical practice.

Purpose of the Study:

• To advocate for a human-centered approach to digitalization in healthcare to maximize AI's potential.
• To emphasize the importance of co-creation with healthcare professionals and patients in developing digital health tools.
• To highlight nephrology as a "living lab" for digital transformation due to its complex patient population and care requirements.

Main Methods:

• Review of current challenges in clinical digitalization and AI implementation.
• Application of service design principles to prioritize end-user needs and workflows.
• Proposal for co-creation, interoperability via common data standards, and structured data capture.

Main Results:

• A human-centered digitalization strategy is essential for successful AI integration in healthcare.
• Co-creation and interoperability are vital for developing valuable and usable digital health tools.
• Nephrology's unique characteristics make it suitable for piloting digital transformation initiatives.

Conclusions:

• Prioritizing robust digital infrastructure in nephrology can address immediate clinical needs and prepare for safe AI deployment.
• Effective digitalization, driven by user needs and collaboration, will enhance patient care through AI.
• A foundational digital transformation is necessary before AI can be fully leveraged in clinical settings.