Innovations and AI for Enhancing Efficiency, Effectiveness, Safety, and Satisfaction in Working with Electronic Records in Health and Care

Electronic records are essential for modern health and care, yet they often present usability challenges that impact the efficiency, effectiveness, safety, and satisfaction of both patients/service users and health and care providers. Advances in artificial intelligence (AI) and innovative design solutions offer promising opportunities to optimize usability of electronic records, reduce cognitive burden, enhance decision-making, and streamline workflows.

AI-driven solutions, such as natural language processing, predictive analytics, and intelligent automation, have the potential to improve data accessibility, reduce documentation time, and ensure the right information is available at the right moment. At the same time, human-centered design approaches focus on improving the usability and user experience of electronic records, fostering better engagement and reducing burnout amongst health and care professionals. However, implementing these innovations in complex health and care environments requires careful consideration of ethical, regulatory, and change management factors.

This research topic seeks to explore how AI and innovative approaches can enhance the interaction between health and care providers, patients and service users, and electronic record systems. The goal is to foster a seamless, intuitive, and safe digital health and care experience that supports efficiency and person-centered care.

We welcome manuscripts that cover the following themes:
· AI-driven enhancements for improving the efficiency and usability of electronic record systems
· Strategies to reduce cognitive load and burnout amongst health and care professionals through intelligent automation and decision support
· Human-centered design approaches to optimize electronic record interfaces and workflows
· The impact of AI-driven summarization and predictive analytics on health and care decision-making
· Methods for balancing automation with oversight by health and care professionals to ensure safety
· Ethical and regulatory considerations in AI-powered electronic record systems
· Case studies of successful AI and innovation-driven improvements in electronic record usability
· Patient and service user perspectives on accessing and interacting with electronic records

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: AI, Artificial Intelligence, Innovation, EHR, EPH Electronic, Records, Effectiveness, Safety, Acceptability, Human-Centered, human computer interaction, efficiency, usability, trust, human factors

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.