Clinical Report: Assessment of Large Language Models for Extracting Structured Data

Overview

This study evaluates the performance of large language models (LLMs) in extracting structured binary data from clinical notes related to interstitial lung disease (ILD).

Background

Clinical notes often contain critical information in unstructured formats, making data extraction labor-intensive and costly. This issue is particularly significant in interstitial lung disease (ILD), where documentation can be verbose and ambiguous.

Data Highlights

No numerical data or trial data were provided in the source material.

Key Findings

• LLMs can extract binary data (yes/no answers) from clinical notes effectively.
• Prompt engineering is crucial for obtaining accurate responses from LLMs.
• The study involved a cohort of patients from the Stanford Interstitial Lung Disease Clinic.
• Ethical approval was obtained for the retrospective chart review study.
• LLMs may facilitate the creation and maintenance of ILD registries.

Clinical Implications

The use of LLMs in clinical settings may streamline the process of data extraction from unstructured clinical notes.

Conclusion

The study demonstrates the potential of LLMs to assist in the extraction of structured data from clinical notes.

Related Resources & Content

1. Frontiers in Medicine, 2026 -- Evaluation of Large Language Models in a Pulmonology Outpatient Clinic Using Structured Clinical Data and Chest Radiographs: A Single-Center Prospective Observational Study
2. npj Digital Medicine, 2025 -- Leveraging large language models to extract smoking history from clinical notes for lung cancer surveillance
3. npj Digital Medicine, 2026 -- Collaboration Between Humans and Large Language Models in Clinical Practice: A Systematic Review and Meta-Analysis
4. BMJ Health & Care Informatics -- Self-regulating the use of large language models in clinical practice: a risk-stratified approach
5. Diagnosing interstitial lung disease by multidisciplinary discussion: A review - PMC
6. Idiopathic Pulmonary Fibrosis (an Update) and Progressive Pulmonary Fibrosis in Adults: An Official ATS/ERS/JRS/ALAT Clinical Practice Guideline - PMC
7. Diagnosing interstitial lung disease by multidisciplinary discussion: A review - PMC
8. Idiopathic Pulmonary Fibrosis (an Update) and Progressive Pulmonary Fibrosis in Adults: An Official ATS/ERS/JRS/ALAT Clinical Practice Guideline - PMC