Agentic AI Pattern Catalogue for Hospital Information Systems
A recent research article introduces a compliance-first catalogue of Agentic AI patterns and an orchestration framework tailored for Hospital Information Management Systems (HIMS). This approach transcends the limitations of individual LLM chatbots, creating a regulated ecosystem of both autonomous and semi-autonomous agents. It tackles the disjointed nature of AI implementations in hospitals, which frequently falter before full deployment, leading to risks for patients and healthcare institutions, as well as unresolved technical challenges. According to Fortune Business Insights, the global AI-in-healthcare market is expected to surpass nearly USD 1 trillion by 2034, highlighting the financial risks associated with poor architectural decisions. The paper, which includes a taxonomy of Agentic roles, is available on arXiv under identifier 2608.07627v1.
Key facts
- The paper proposes a compliance-first Agentic AI pattern catalogue and orchestration framework for HIMS.
- The framework moves beyond single LLM chatbots to a governed ecosystem of autonomous and semi-autonomous agents.
- Hospitals are racing to embed AI into triage management, documentation, scheduling, and revenue-cycle workflows.
- Most AI deployments in hospitals remain as fragmented pilots that stall at the edge of production.
- The global AI-in-healthcare market is projected to exceed nearly USD 1 trillion by 2034.
- The projection is according to a report by Fortune Business Insights.
- The framework extends by adding a taxonomy of Agentic roles.
- The paper is available on arXiv with identifier 2608.07627v1.
Entities
Institutions
- Fortune Business Insights
- arXiv