To propose the use of generative artificial intelligence (GenAI) for supervised pre-consultation triage in disorders of gut-brain interaction (DGBI), emphasizing its potential to enhance patient outcomes.
Key Findings:
DGBI is characterized by complex symptom patterns and psychosocial factors that are often poorly captured in standard referral pathways, highlighting the need for improved assessment methods.
Early recognition of psychosocial processes can enhance treatment engagement and symptom management, leading to better patient outcomes.
A GenAI-enabled triage system could streamline the initial consultation process and improve clinical efficiency, reducing unnecessary delays in care.
Interpretation:
DGBI presents a suitable context for GenAI applications due to its reliance on nuanced symptom narratives and psychosocial context rather than singular test results, which can inform more tailored treatment approaches.
Limitations:
The effectiveness of GenAI tools depends on clear definitions of triage tasks and clinician oversight, necessitating ongoing training and evaluation.
There is a need for prospective evaluation of GenAI systems across various dimensions including workflow, patient acceptability, and ethical considerations.
Conclusion:
DGBI offers a realistic opportunity to develop GenAI tools that are constrained, auditable, and integrated into multidisciplinary care, potentially transforming patient management and outcomes.
