Assessing Digital Readiness in Diagnostic and Clinical Pathology: A Human Factors Approach

Abstract

The practice of diagnostic and clinical pathology (DCP) is rapidly changing given recent advancements in imaging technologies and the application of diagnostic algorithms through artificial intelligence (AI). Proficiency in digital literacy is critical for both laboratorians and diagnosticians to safely and effectively interact with these new technologies as diagnostic pathology enters the digital era. This transformation raises many important questions regarding the human factors and ergonomic considerations including workload, situation awareness, usability, and cognitive load. To date, compared with algorithm-development studies, relatively little formal research has focused on the interface between the diagnostician and AI-augmented diagnostic systems within routine practice. This paper proposes a human factors-informed digital readiness framework for diagnostic and clinical pathology that maps the interfaces among hardware, software, and end users, with particular attention to cognitive workload, usability, and alignment with existing clinical workflow practices. One critical gap that continues to emerge is that no assessment tool to determine the digital readiness of existing diagnostic pathology workflows is currently available. In the absence of such standards, this emerging field risks fragmentation and inconsistent implementation. We advocate for the development of best-practice frameworks for digital readiness that are explicitly grounded in human factors and ergonomics principles applicable to urban centres, and extensible to rural and remote healthcare environments. This framework represents a foundational model intended for prospective validation and implementation across diverse diagnostic medicine practice environments.

Keywords: Artificial Intelligence, Digital Readiness, Human Factors, Digital Literacy

DOI: 10.54941/ahfe1007463