About
Bunkerhill Health is an enterprise-grade generative AI platform purpose-built for health systems. It gives clinical and operational teams the tools to build, deploy, and scale AI agents—called Carebricks—that reason over patient data and trigger automated actions without manual intervention. By synthesizing a patient's complete clinical context from structured and unstructured data sources, Bunkerhill enables organizations to surface actionable findings, close care gaps, and operationalize complex clinical logic at scale. The platform supports a wide range of healthcare workflows, including streamlining prior authorization, automating quality registry mapping (e.g., stroke, hip fracture, cancer registries), identifying clinical trial candidates based on nuanced eligibility criteria, boosting preventive screening rates, and preventing hospital-acquired infections such as CAUTIs and CLABSIs. Carebricks can alert nursing leadership, pre-fill registry forms, auto-enroll eligible patients, and notify stewardship teams—all in real time. Bunkerhill is designed for health systems that need to move beyond dashboards and toward a true 'system of action.' It integrates with existing EHR and clinical data environments, enabling teams to translate clinical insights into coordinated operational steps. The platform is validated through real-world deployments, including a published KLAS case study with UTMB Health. It is best suited for large health systems, academic medical centers, and integrated delivery networks looking to operationalize AI at enterprise scale.
Key Features
- Carebricks AI Agents: A modular framework that lets clinical and operational teams build and deploy AI agents tailored to specific workflows—without writing custom code from scratch.
- Full Clinical Context Reasoning: Synthesizes structured and unstructured patient data to give AI agents a complete picture of each patient's clinical status before triggering any action.
- Automated Workflow Execution: Triggers real-time alerts, form pre-fills, care team notifications, and patient outreach across service lines 24/7, eliminating manual follow-up.
- Clinical Trial Candidate Identification: Automatically screens patients against complex eligibility criteria (e.g., MSI-high, EGFR mutations, ECOG scores) and adds qualified candidates to trial rosters.
- Quality Registry Automation: Detects registry-eligible patients, pre-fills registry forms, and alerts data abstractors for programs like stroke, hip fracture, and NAACCR cancer registries.
Use Cases
- Automatically identifying clinical trial candidates by screening patients against complex molecular, performance status, and treatment history criteria.
- Automating quality registry mapping by detecting eligible patients, pre-filling forms, and alerting data abstractors for programs like stroke, hip fracture, and cancer registries.
- Preventing hospital-acquired infections by proactively alerting care teams when patients meet CAUTI, CLABSI, or VAP risk thresholds.
- Boosting preventive screening rates by auto-generating referral orders and patient outreach for eligible patients who have missed screenings like mammography or genetics counseling.
- Streamlining prior authorization workflows by using patient clinical context to pre-populate and submit authorization requests automatically.
Pros
- End-to-End Clinical Automation: Goes beyond dashboards by automating downstream actions—alerts, enrollments, form fills, and referrals—closing the loop from insight to action.
- Broad Use Case Coverage: Supports diverse clinical and operational priorities, including infection prevention, prior authorization, preventive screening, and registry compliance under one platform.
- Enterprise Validated: Backed by real-world deployments and published KLAS research with major health systems, providing credibility and implementation confidence for large organizations.
Cons
- Enterprise-Only Positioning: Designed exclusively for large health systems and academic medical centers, making it inaccessible or cost-prohibitive for smaller clinical practices.
- Implementation Complexity: Deploying AI agents across multiple service lines requires significant integration work with existing EHR and clinical data infrastructure.
- Opaque Pricing: No public pricing is available; cost is determined through enterprise sales conversations, making budget estimation difficult upfront.
Frequently Asked Questions
What are Carebricks?
Carebricks are modular AI agents built on Bunkerhill's platform that clinical and operational teams can configure and deploy to automate specific healthcare workflows, such as identifying trial candidates, mapping registry entries, or triggering infection-prevention alerts.
How does Bunkerhill integrate with existing health system infrastructure?
Bunkerhill integrates with existing EHR systems and clinical data environments to ingest and reason over patient data, then surfaces results through existing communication channels like MyChart, nursing dashboards, and care team notifications.
What types of clinical workflows can Bunkerhill automate?
The platform can automate prior authorization, preventive screening outreach, hospital-acquired infection prevention alerts, clinical trial candidate identification, quality registry mapping, case-mix accuracy improvement, and more.
Who is Bunkerhill Health designed for?
Bunkerhill is designed for large health systems, academic medical centers, and integrated delivery networks that need to operationalize AI across multiple clinical and operational service lines at scale.
Is there published evidence of Bunkerhill's real-world impact?
Yes. Bunkerhill has a published KLAS case study documenting how UTMB Health operationalizes AI using the Carebricks platform, providing independent validation of the platform's clinical and operational outcomes.
