An Observational Longitudinal Study to Explore the Concordance between an Advanced Generative AI Model, Live Clinical Prescription, and a Gold Standard Prescription of Drug Appropriateness, Dosing, and Drug-Drug Interactions in a Medical ICU.
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 50
- 试验地点
- 1
- 主要终点
- Number and severity of clinically significant DDIs
研究概览
简要总结
Short Description / Primary Purpose & Hypothesis
This study aims to compare prescriptions generated by an advanced generative AI model with live clinician prescriptions and gold standard prescriptions in a Medical ICU. The primary purpose is to evaluate concordance in drug appropriateness, dosing, and identification of drug–drug interactions.
Hypothesis: AI-assisted prescription review will reduce inappropriate drugs, clinically significant drug–drug interactions, and dosing errors compared to conventional clinician-driven prescriptions, thereby improving medication safety.
研究设计
- 研究类型
- Observational
入排标准
- 年龄范围
- 18.00 Year(s) 至 80.00 Year(s)(—)
- 性别
- All
入选标准
- •All adult patients admitted to the Medical ICU at Medanta The Medicity with ICU stay more than or equal to 6 hours whose retrospective prescription data is available through eHIS for at least 5 days.
排除标准
- •ICU stay less than 6 hours Patients admitted with poisoning or snake bite Trauma patients.
结局指标
主要结局
Number and severity of clinically significant DDIs
时间窗: Within 5 days of ICU stay (daily prescription review)
次要结局
- Instances of inappropriate drug, dose, frequency, or duration.(Concordance rates between AI, live clinician and gold standard)
研究者
Dr Sushila Kataria
Medanta The Medicity
