A qualitative, multi-framework methodology for analysing health information technology-related patient safety...

The increasing reliance on health information technology (HIT) has introduced new and often unforeseen risks to patient safety in complex healthcare systems. Many HIT-related safety problems emerge only after systems are embedded in routine clinical practice and are difficult to identify using prospective or purely quantitative methods. Incident reports provide valuable insights into real-world failures, but systematic methodologies for analysing HIT-related incidents remain underdeveloped.

This article aims to describe and formalise a qualitative, multi-framework methodology for analysing health information technology-related patient safety incidents, based on retrospective incident report data.

The methodology integrates multiple data sources, including incident reporting systems, existing incident databases, and supplementary interview-derived narratives. HIT-related incidents are identified through a structured screening process combining keyword-based searches and manual narrative review. Analysis is conducted using complementary deductive and inductive approaches, including established patient safety classification systems, HIT-specific frameworks, workflow-based analysis, and thematic analysis. Structured coding procedures, independent review, consensus-building, and reflexive practices are employed to enhance analytical rigour. Findings are systematically translated into preventive and corrective strategies grounded in sociotechnical principles.

The proposed methodology enables systematic identification and characterisation of HIT-related patient safety incidents, capturing sociotechnical mechanisms, contributing factors, and outcomes that are not readily identified through single analytical frameworks. By combining multiple perspectives, the approach supports analysis of low-frequency, high-impact events, workflow disruptions, and system-level failures, and facilitates the development of context-sensitive preventive and corrective strategies.

This multi-framework qualitative methodology provides a structured, transferable approach to learning from HIT-related patient safety incidents in complex healthcare systems. The framework supports researchers, clinicians, and safety analysts in understanding how digital systems fail in real-world practice and offers a robust foundation for improving the safety and resilience of digital healthcare.