Wolters Kluwer Health Expands Agentic AI Capabilities to Automate Medication Workflows

The company is also providing a model context protocol (MCP) server to select AI developers to facilitate integration with its expert-curated drug data.

Wolters Kluwer Health has introduced Medi-Span Expert AI, a new offering designed to support agentic artificial intelligence applications in medication workflows and prescription automation. The company is also providing a model context protocol (MCP) server to select AI developers to facilitate integration with its expert-curated drug data.

The MCP server is intended to connect third-party AI applications and agents with Medi-Span content in a structured, machine-readable format. According to the company, the goal is to reduce development timelines and complexity for digital health and health IT developers building AI-driven medication tools.

Medi-Span provides embedded drug databases and medication data solutions used across hospital, emergency, pharmacy, and payer settings. The content supports formulary management, medication safety, claims processin,g and drug pricing decisions.

Christian Hartman, vice president of product innovation for pharmacy and health technology solutions at Wolters Kluwer Health, said the MCP infrastructure delivers structured, evidence-based medication intelligence required for automation. “What we’re announcing today with MCP provides foundational capabilities for medication workflow automation,” Hartman said in an interview.

Initial use cases for Medi-Span Expert AI include AI-ready medication lookup and reconciliation, drug interaction and duplicate therapy screening, medication order validation, and retrieval of patient-specific medication information. Additional applications could extend to formulary and benefit management, pricing and contracting, and supply chain optimization.

Industry forecasts estimate agentic AI in healthcare could grow 40% to 45% annually and exceed $5 billion within five years. The company argues that AI systems operating in medication workflows require clinically governed, validated content to support safe and consistent decision-making at scale.

Hartman said general-purpose large language models lack the structured, evidence-based layer necessary for high-stakes medication decisions. “As AI systems are increasingly used in medication workflows, accuracy and consistency are essential,” he said.

The initial group of developers gaining access to the MCP server includes innovation partners building AI-driven medication management, clinical decision support, and pharmacy automation tools.

The launch follows the company’s broader AI investments, including the rollout of an AI-powered version of its clinical decision support platform last year.

Stay tuned for more such updates on Digital Health News