COPD
Conditions
Brief 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.
Interventions
OTHERLLM
A LLM-based comparison between treatment and guideline.
Sponsors
Charite University, Berlin, Germany
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
TRIPLE (Subject, Caregiver, Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Diagnosis of COPD * Consent * Discharge after hospitalization
Exclusion criteria
* Lack of Consent
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Adherence to treatment guidelines at the time of hospital discharge | From date of admission (which is enrollment) to the date of discharge, assessed up to one month | The primary endpoint will assess whether the treatment at the time of discharge is consistent with the guidelines' recommendations. This is a binary outcome measure of yes or no. |
| Percentage of patients treated in concordance with treatment guidelines at the time of hospital discharge | From date of admission (which is enrollment) to the date of discharge, assessed up to one month | This primary endpoint will assess the percentage of guideline-concordant treatments in each study arm. |
Countries
Germany
Contacts
PRINCIPAL_INVESTIGATORMatthias Gröschel, MD PhD
Charité
Outcome results
None listed