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Using Large Language Models Such As GPT-4 to Assess Guideline Adherence in Patients With Chronic Obstructive Pulmonary Disease

NCT06410547 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 78

Last updated 2026-03-20

No results posted yet for this study

Summary

According to studies in the US and the Netherlands, 33-40% of patients with chronic conditions receive care that does not follow guideline recommendations. These findings have also been demonstrated in the management of COPD. This leads to under- or over-treatment of patients and, in the case of COPD, to exacerbations and hospitalisations. These exacerbations are a significant clinical problem, affecting patient's lung function, quality of life and mortality. They are also a burden on the healthcare system. Technological advances in artificial intelligence offer the opportunity to address these issues in COPD management. In the past year, there have been remarkable innovations in the field of natural language processing, especially through large language models such as GPT-4 from OpenAI and Bard or Gemini from Google. These models offer an opportunity to improve the implementation of evidence-based care in clinical practice.

This study is a prospective, randomised trial that will compare therapy on discharge for patients with COPD. One arm will receive no intervention, while the other arm will receive a treatment recommendation from an LLM. The study will compare the percentage of patients treated according to the guideline.

Conditions

Interventions

OTHER

LLM

A LLM-based comparison between treatment and guideline.

Sponsors & Collaborators

  • Charite University, Berlin, Germany

    lead OTHER

Principal Investigators

  • Matthias Gröschel, MD PhD · Charité

Study Design

Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
TRIPLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-05-15
Primary Completion
2025-04-01
Completion
2025-04-01

Countries

  • Germany

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06410547 on ClinicalTrials.gov