NCT06410547

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

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 78 (actual)
• Sponsor: Charite University, Berlin, Germany · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

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

• COPD

Interventions

Type	Name	Description
OTHER	LLM	A LLM-based comparison between treatment and guideline.

Timeline

• Start date: 2024-05-15
• Primary completion: 2025-04-01
• Completion: 2025-04-01
• First posted: 2024-05-13
• Last updated: 2026-03-20

Locations

1 site across 1 country: Germany