Health Information Technology-Related Loss of Central Surveillance Data in a Heart Intensive Care Unit:...

Centralized electronic surveillance systems are widely used in intensive care settings to support continuous physiological monitoring and patient safety. Failures in health information technology (HIT) infrastructure can disrupt workflows, reduce situational awareness, and create latent risks for serious harm. Understanding such events requires analytic approaches that go beyond single-classification frameworks.

This study aimed to classify and analyze an HIT-related incident that involved loss of central surveillance data in a heart intensive care unit using multiple complementary patient safety and human factors frameworks.

This study is a qualitative case report analysis of an incident in which a central surveillance system intermittently lost server connectivity, resulting in unavailability and loss of monitoring data. The narrative was derived from an incident report and supporting documentation and was translated and linguistically adapted for publication. The incident was independently classified using 5 frameworks: the International Classification for Patient Safety (ICPS), the Health Information Technology Classification System (HIT-CS), Systems Engineering Initiative for Patient Safety (SEIPS) 2.0, the sociotechnical model by Sittig and Singh, and the Human Factors Analysis and Classification System for health care (HFACS-Healthcare). Findings were synthesized across frameworks.

All 5 frameworks characterized the event as an HIT-driven system failure involving information unavailability, delayed detection, and multi-patient impact. The HIT-CS identified a technical failure in system availability and recovery. The ICPS classified the event as a documentation or information incident with potential for severe harm. The SEIPS 2.0 and sociotechnical models highlighted disruptions to monitoring tasks and the organization's reliance on IT intervention. The HFACS-Healthcare attributed the event primarily to organizational influences and preconditions for unsafe acts, with no frontline unsafe acts identified. Convergence across frameworks emphasized system-level contributors.

HIT-related monitoring failures in high-acuity settings are best understood as sociotechnical system events rather than isolated technical faults or individual errors. A multi-framework approach provided complementary insights into detection, recovery, and governance vulnerabilities, supporting improved learning and resilience in clinical surveillance systems.