Related Experiment Video
Updated: Jun 14, 2025

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Root cause analysis of cases involving diagnosis
Mark L Graber1, Gerard M Castro2, Missy Danforth3
1Plymouth, MA, USA.
Improving diagnostic safety requires analyzing successful or failed diagnoses. This study provides guidance on adapting root cause analyses (RCAs) to investigate diagnostic errors, focusing on clinical reasoning and system factors.
Area of Science:
- Healthcare
- Patient Safety
- Medical Diagnostics
Background:
- Diagnostic errors are a primary threat to patient safety.
- Analyzing diagnostic successes and failures offers a path to improve safety.
- Existing root cause analysis (RCA) methods need adaptation for diagnostic cases.
Purpose of the Study:
- To provide guidance on modifying root cause analyses (RCAs) for studying diagnostic errors.
- To detail how to investigate both successful and failed diagnostic processes.
- To offer a framework for improving diagnostic safety through case analysis.
Main Methods:
- Adapting existing root cause analysis (RCA) methodologies for diagnostic case reviews.
- Emphasizing immediate investigation post-incident.
- Including involved clinicians in the RCA team.
- Incorporating analysis of clinical reasoning and human-factors/systemic context.
Main Results:
- Modified RCAs should begin immediately after a diagnostic incident.
- Inclusion of frontline clinicians in RCA teams is crucial.
- Analysis must encompass the clinical reasoning process and system-related factors.
- Provides instructions for identifying root causes, contributing factors, and interventions.
Conclusions:
- Adapting root cause analysis (RCA) is essential for studying diagnostic errors.
- A human-factors approach is vital for understanding diagnostic failures and successes.
- Implementing modified RCAs can enhance patient safety by addressing diagnostic vulnerabilities.
Related Concept Videos
Documentation of Nursing Diagnosis
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
Formulating and Validating Nursing Diagnosis II
Risk nursing diagnoses represent clinical judgments of an individual, family, or community more vulnerable to developing the health problem than others...
Formulating and Validating Nursing Diagnosis I
There are thirteen domains...
Nursing Diagnosis
The nursing diagnosis focuses on evidence-based...
Methods of Documentation VI: Case Management Model
For example, a patient with a chronic...
Criteria for Causality: Bradford Hill Criteria - II

