mlsanityData to 14 Oct 2026

From Single Chatbots to Governed Agent Ecosystems: An Agentic AI Pattern Catalogue and Orchestration Framework for Mission-Critical Hospital Information Management Systems

arXiv 2608.07627 ↗First posted 7 Aug 2026cs.AI cs.CL cs.LGcited by 0

On the map: LLM agents and tool use → Medical and scientific domain agents

Abstract (arXiv)

Hospitals are racing to embed AI, while coping with the surge in adaptation of the technology in other industries, into the triage management, documentation, scheduling, and revenue-cycle workflows, yet most deployments remain as fragmented pilots that stall at the edge of production, exposing patients and institutions to operational fragility, ungoverned risk, and mounting technical debt. At the same time, the global AI-in-healthcare market is projected to exceed nearly USD 1 trillion by 2034, according to the report of Fortune Business Insights, amplifying the financial consequences of architectural missteps and failed scaling strategies. This research proposes a compliance-first Agentic AI pattern catalogue and orchestration framework, purposely built for HIMS, moving beyond the single LLM chatbots and towards a governed ecosystem of autonomous and semi-autonomous agents. The framework extends by adding (i) a taxonomy of Agentic roles, (ii) a formal risk-stratification model that maps each pattern to risk tiers, human-in-the-loop checkpoints, and governance hooks, and (iii) a unified orchestration runtime capable of coordinating multi-agent workflows across EHR/HIMS landscapes such as Epic, Cerner, and MEDITECH. Technically the framework combines vLLM-based inference, optimized paging memory, confidential computing, and MCP based on-premise deployment, enforcing end-to-end encryption and policy-as-code controls aligned with HIPAA, GDPR, the EU AI Act, India's DPDP and DISHA Acts, ISO 27001, ISO 27002, ISO 14971 and IEC 62304. We exhibit how the proposed architecture is capable and efficient to reduce the documentation time, integration effort, and AI pilot attrition while constricting the governance and auditability, offering hospital leaders and governing authorities an urgently needed blueprint to convert AI investment into sustainable clinical, operational, and financial ROI

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use. Builds on 25 of its 139 references that are in the map. First posted on arXiv 7 Aug 2026.

Builds on

25 of 139 references.

Closest ancestors · 3

Same direction, newest first

  1. 2026ClinicalAgents: Multi-Agent Orchestration for Clinical Decision Making with Dual-Memory27 Mar
  2. 2026Empowering Locally Deployable Medical Agent via State Enhanced Logical Skills for FHIR-based Clinical Tasks6 Mar
  3. 2024AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction Simulator15 Feb

Other references · 22

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  4. 2023MetaGPT: Meta Programming for A Multi-Agent Collaborative Frameworkcited by 1,808
  5. 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Societycited by 1,395
  6. 2023SGLang: Efficient Execution of Structured Language Model Programscited by 1,141
  7. 2023MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoningcited by 316
  8. 2025Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directionscited by 265
  9. 2024LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Aheadcited by 155
  10. 2026AgentLeak: A Benchmark for Internal-Channel Privacy Leakage in Multi-Agent LLM Systemscited by 25
  11. 2025Large Language Model-based Data Science Agent: A Surveycited by 23
  12. 2025Large Language Models in Healthcarecited by 6
10 more
  1. 2023An Empirical Study of Self-Admitted Technical Debt in Machine Learning Softwarecited by 5
  2. 2025PEAR: Planner-Executor Agent Robustness Benchmarkcited by 5
  3. 2026Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directionscited by 4
  4. 2025Generative AI for Healthcare: Fundamentals, Challenges, and Perspectivescited by 3
  5. 2025Data Poisoning Vulnerabilities Across Healthcare AI Architectures: A Security Threat Analysiscited by 3
  6. 2026SoK: Privacy-aware LLM in Healthcare: Threat Model, Privacy Techniques, Challenges and Recommendationscited by 3
  7. 2025Can I Trust This Chatbot? Assessing User Privacy in AI-Healthcare Chatbot Applicationscited by 2
  8. 2024Post-Quantum Cryptography: Securing Digital Communication in the Quantum Eracited by 1
  9. 2025Developing a Responsible AI Framework for Healthcare in Low Resource Countries: A Case Study in Nepal and Ghanacited by 1
  10. 2026From Siloed Algorithms to Compliance-First Agentic Platforms: A Multi-Layered Architecture for Hospital AI Systemscited by 1

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