Boston Children's Hospital: AI Revolutionizes Diagnostics

AI in Pediatric Care in Boston

Boston Children's Hospital has integrated artificial intelligence (AI) into its clinical and operational infrastructure to enhance the quality of care provided to its pediatric patients, particularly those with complex and rare conditions. By incorporating AI into daily workflows, the team has successfully reduced operational costs, improved access to care, and diagnosed over 40 rare conditions that were previously unresolved.

Operating Under Pressure

Boston Children's Hospital is one of the largest pediatric institutions in the world, serving patients across more than 40 specialties with nearly 1 million outpatient visits each year. Like many healthcare systems, it operates under strict financial constraints while managing a growing administrative burden. Supply chain, billing, and operations teams handle a high volume of repetitive tasks, ranging from processing invoices to coordinating schedules. These processes, while necessary, are time-consuming and divert staff from higher-value tasks.

Meanwhile, clinical teams face different limitations. Cases of rare diseases often involve fragmented genetic data, incomplete clinical histories, and overwhelming medical literature. Even in a leading research institution, doctors cannot synthesize all this information quickly enough to reach every diagnosis. "The problem is not the effort," says John Brownstein, Chief Innovation Officer at Boston Children's Hospital. "It's the human cognitive limit."

Laying the Foundation with an Enterprise AI Layer

The hospital began with individual use cases for AI, including documentation and translation tools. However, these initial efforts quickly revealed the limitations of a fragmented approach. "You can't just rely on one-off solutions," Brownstein explains.

The hospital then decided to build what Brownstein calls an enterprise AI layer: a secure internal ChatGPT environment used by research, clinical, and administrative teams. Instead of treating AI as a set of tools, the organization created a shared foundation where new capabilities can be developed and deployed rapidly.

This system allows teams to work with AI in a way that is directly relevant to their roles, whether it's accessing internal data, synthesizing medical literature, or streamlining workflows. Governance structures have been established alongside the technology to ensure security, tracking, and consistent evaluation.

The change has altered the pace of innovation. Tools that once required lengthy development cycles can now be deployed in a matter of days, enabling the organization to respond quickly to operational and clinical demands. Today, more than a third of employees use AI as part of their daily work, covering clinical, research, and administrative functions.

Redefining Workflows in Operations

Boston Children's Hospital initially focused on areas where AI could have a measurable operational impact. In supply chain operations, AI now manages invoice entry, routing, and responses.

Simultaneously, the hospital has applied AI to surgical scheduling. By analyzing clinical notes and estimating patient acuity, the system improves operating room time allocation. This allows for more advanced scheduling, increasing utilization and enabling more patients to receive the care they need more quickly.

Additionally, physicians use AI for decision support and to synthesize complex clinical information. Researchers apply it to data analysis and cohort building. Administrative teams leverage it for document drafting, coding, and workflow improvement.

The organization directly links these changes to measurable outcomes. Through more than 50 automations, Boston Children's Hospital has captured approximately 60,000 hours of time savings, equivalent to over $7 million in redeployed labor.

The organization has focused on the relevance of AI in daily work rather than introducing it as a standalone initiative. "The key here is to meet people where they are," Brownstein asserts.

Advancing Rare Disease Diagnosis and Genetic Research

Alongside operational improvements, Boston Children's Hospital has invested in AI for clinical discovery. The hospital has developed what it describes as a "co-pilot geneticist," designed to integrate genetic data, phenotypic information, and global medical literature.

This system addresses one of the most challenging dilemmas in medicine: diagnosing rare diseases that have eluded explanation for years. Through this work, more than 40 diagnoses have been made to date that were previously considered impossible. This effort has also led to the identification of new gene targets and potential therapeutic pathways.

"We combine genetic information, phenotypic data, literary research, and AI reasoning to provide diagnoses to families who were once left without answers," Brownstein explains.

For patients and families, the impact is immediate and tangible. Cases that previously remained unresolved now yield answers and, in some instances, new treatment directions. "It was unthinkable before, but it now brings hope to so many families," concludes Brownstein.

AI-Enabled Care at Scale

The next phase of Boston Children's Hospital's AI strategy focuses on deeper integration and broader adoption. Leadership sees a significant opportunity to expand both usage and impact.

The hospital is working to more fully integrate AI into clinical decision-making, extend tools across specialties, and continue refining models through collaboration with OpenAI.

Over time, AI is expected to become a central element of medical practice. "How could you not want an incredibly trained physician alongside all the world's medical knowledge?" Brownstein questions.

At Boston Children's Hospital, AI is becoming part of the infrastructure that supports care delivery, research, and discovery, redefining what is possible for both clinicians and patients.