Using Large Language Models Such As GPT-4 to Assess Guideline Adherence in Patients with Chronic Obstructive Pulmonary Disease (IMPL-AI-MENT)

Charité University Medicine Berlin

Status: Enrolling

Conditions: COPD

Treatments: Other: LLM

Study type: Interventional

Funder types: Other

Identifiers

NCT06410547

EA2/322/23

Details and patient eligibility

About

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.

Enrollment: 70 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Diagnosis of COPD
• Consent
• Discharge after hospitalization

Exclusion criteria

• Lack of Consent

Trial design

Primary purpose: Treatment

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Triple Blind

---

70 participants in 2 patient groups

No Intervention

No Intervention group

Description:

This arm will be treated as usual. No intervention will be performed.

LLM Assessement

Active Comparator group

Description:

During hospital stay and after written informed consent, an LLM is asked to indicate if the treatment the patient receives is guideline-concordant. The information is ascertained by two study physicians (human-in-the-loop) and later provided to the treating physician who can recommend a change in therapy to the patient (outside of the study).

Treatment:

Other: LLM