概要
公開日: 2026-05-29
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原文
May 29, 2026 Boston Children’s uses AI to unlock new diagnoses Boston Children’s treats AI as infrastructure to cut costs, expand capacity and diagnose cases once thought impossible. Contact sales Company size: Enterprise Region: North America Industry: Healthcare Products: ChatGPT Results 40+ rare conditions diagnosed that had previously gone unresolved Results 60,000 hours saved across AI-enabled workflows Results $7M+ in redeployed labor from operational time savings Results 50+ automations supporting operational workflows Loading… Share Boston Children’s Hospital did not pursue artificial intelligence simply to experiment with new technology. The hospital embedded AI across the organization as a core part of its clinical and operational infrastructure to improve how care is delivered to its pediatric patients, particularly those with complex and rare conditions. By integrating AI into daily workflows, the team has reduced operational costs, improved access to care, and helped diagnose more than 40 rare conditions that had previously gone 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 close to 1 million outpatient visits each year. Like many health systems, it operates under tight financial constraints while managing increasing administrative burden. Teams across supply chain, billing and operations handle high volumes of repetitive tasks, from processing invoices to coordinating schedules. These processes are necessary but time-intensive, pulling staff away from higher-value work. At the same time, clinical teams face a different kind of limitation. Rare disease cases often involve fragmented genetic data, incomplete clinical histories and an overwhelming body of medical literature. Even in a leading research institution, physicians cannot synthesize all of that information fast enough to reach every diagnosis. “The problem isn’t effort,” says John Brownstein, Chief Innovation Officer at Boston Children’s. “It’s human cognitive limits.” Setting the foundation with an enterprise AI layer Boston Children’s began with individual AI use cases, including documentation and translation tools. But those early efforts quickly exposed the limits of a fragmented approach. “You cannot just rely on one-off solutions,” Brownstein says. The hospital shifted to building what Brownstein calls an enterprise AI layer: a secure internal ChatGPT environment used across research, clinical, and administrative teams. Instead of treating AI as a collection of tools, the organization created a shared foundation where new capabilities could be developed and deployed quickly. This system allows teams to work with AI in ways that are directly relevant to their roles, whether that involves accessing internal data, synthesizing medical literature or streamlining workflows. Governance structures were built alongside the technology to ensure safety, monitoring and consistent evaluation. The shift changed the pace of innovation. Tools that once required extended development cycles can now be deployed in days, allowing the organization to respond quickly to both operational demands and clinical needs. Today, more than one-third of employees use AI as part of their daily work, spanning clinical, research and administrative functions. Redesigning workflows across operations Boston Children’s focused first on areas where AI could deliver measurable operational impact. In supply chain operations, AI now manages invoice intake, routing and responses. In parallel, the hospital applied AI to surgical scheduling. By analyzing clinical notes and estimating patient acuity, the system improves how operating room time is allocated. This allows schedules to be planned further in advance, increasing utilization and enabling more patients to receive the care that they need faster. Additionally, physicians use AI for decision support and to synt