# Toward Safer Diagnoses: A SEIPS-Based Narrative Review of Diagnostic Errors

## TL;DR

This paper reviews diagnostic errors in healthcare using a systems-based approach to identify factors affecting accurate and timely diagnoses.

## Contribution

The paper integrates literature on diagnostic errors using the SEIPS model to highlight interconnected factors across six domains.

## Key findings

- Diagnostic effectiveness is influenced by complex factors across six SEIPS domains.
- Socio-behavioral and environmental factors are significant contributors to diagnostic errors.
- Traditional data resources like EHRs often fail to capture these complex factors.

## Abstract

Diagnostic errors have been a critical concern in healthcare, leading to substantial financial burdens and serious threats to patient safety. The Improving Diagnosis in Health Care report by the National Academies of Sciences, Engineering, and Medicine (NASEM) defines diagnostic errors, focusing on accuracy, timeliness, and communication, which are influenced by clinical knowledge and the broader healthcare system. This review aims to integrate existing literature on diagnostic error from a systems-based perspective and examine the factors across various domains to present a comprehensive picture of the topic. A narrative literature review was structured upon the Systems Engineering Initiative for Patient Safety (SEIPS) model that focuses on six domains central to the diagnostic process: Diagnostic Team Members, Tasks, Technologies and Tools, Organization, Physical Environment, and External Environment. Studies on contributing factors for diagnostic error in these domains were identified and integrated. The findings reveal that the effectiveness of diagnostics is influenced by complex, interconnected factors spanning all six SEIPS domains. In particular, socio-behavioral factors, such as team communication, cognitive bias, and workload, and environmental pressures, stand out as significant but difficult-to-capture contributors in traditional and commonly used data resources like electronic health records (EHRs), which limits the scope of many studies on diagnostic errors. Factors associated with diagnostic errors are often interconnected across healthcare system stakeholders and organizations. Future research should address both technical and behavioral elements within the diagnostic ecosystem to reduce errors and enhance patient outcomes.