Streamlining organ donation: impact of an artificial intelligence-based protocol post-brain death

Area of Science:

• Medical Informatics
• Transplantation Medicine
• Public Health

Background:

• Delays in organ retrieval after brain death (BD) compromise organ viability and increase post-transplant complications.
• In 2021, an AI application was implemented in Tamil Nadu, India, to expedite organ procurement data verification.
• This study retrospectively evaluated the AI intervention's impact on organ retrieval timelines.

Purpose of the Study:

• To assess the effectiveness of an AI-based application in reducing organ retrieval delays.
• To identify factors contributing to delays in organ procurement.
• To evaluate the impact of AI on transparency and efficiency in organ donation.

Main Methods:

• Retrospective observational study of organ donors declared dead by neurological criteria (DND) from January 2018 to December 2023.
• Comparison of organ retrieval times between pre-AI (P1) and post-AI (P2) implementation periods.
• Fishbone analysis to identify root causes of delays across family, physician, institution, and government domains.

Main Results:

• Median organ retrieval time was 1657 minutes (IQR, 1499-1899).
• A statistically significant increase in retrieval time was observed post-AI implementation (P2: 1660 min vs. P1: 1587 min, p=0.04).
• Delays in operating room transfer post-legal verification significantly increased from 125 min (P1) to 384 min (P2) (p=0.002).

Conclusions:

• The AI protocol enhanced data verification and transparency but introduced unforeseen procedural delays.
• Key factors affecting organ retrieval timelines in a low-to-middle-income setting were identified.
• Iterative refinement of AI tools is crucial for optimizing organ procurement efficiency and clinical outcomes.