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Reduce Canceled Procedures Due to Inventory Shortages

InterSystems Data Studio is an essential element of a modern data strategy required to enable growth, optimize business reporting, reduce risk, and support compliance for any firm in the financial services industry.

Data Integration Key to Achieving Needed Breakthroughs in Healthcare When peers from other industries ask why data hasn’t driven comparable breakthroughs in healthcare, the answer is usually hiding in plain sight: clinical and administrative data still live in different systems and “speak” different digital languages. Integrating them is a prerequisite for the next wave of progress—better care, better patient experience, and better operational performance at the same time. Fortunately, there are now multiple mandates spurring this integration, from Centers for Medicare & Medicaid Services requiring Fast Healthcare Interoperability Resources APIs, to National Committee for Quality Assurance embracing digital quality measures, to enforcement of prohibitions against information blocking. Health plans and providers, however, must guard against swapping these two longstanding data siloes for several new ones.

世界各地的农村社区正面临着一场持续且日益加剧的医疗保健危机——医疗人员短缺、数据分散、数字基础设施有限，以及一个严峻的现实：与城市居民相比，偏远地区居民的预期寿命明显更短，健康状况也更差。 在InterSystems READY 2026大会的这场小组讨论中，来自美国、 英格兰和澳大利亚的四位医疗领域领军人物，分享了弥合这一差距究竟需要什么。

用于安全高效数据分析的智能助手

在这场来自InterSystems READY 2026大会的主题演讲中，InterSystems总裁Don Woodlock阐述了一个简明而深刻的见解：“没有数据战略，就没有AI战略； 而没有互操作性战略，就没有数据战略。” Don深入剖析了这在实践中的含义，并引入了“AI数字骨干网（AI Digital Backbone）”这一概念——这是一个统一平台，用于组织数据、使自主型AI（agentic AI）能够跨企业系统执行实际行动，并提供大规模实现AI安全与有效性所需的治理与安全基础设施。

InterSystems IRIS AI Hub 提供了一套覆盖构建、部署与治理 AI 智能体及代理式工作流的综合能力。

A mid-sized independent asset management firm overseeing more than $110 billion in equity and fixed income portfolios implemented InterSystems Data Studio™ to unify disparate data across dozens of data sources and systems such as spreadsheets, external data and service providers, legacy systems, data lakes, data warehouses, and data marts.

代理式AI架构为不同任务分配专精化的AI智能体，从而使整体效能超越任何单一模型的独立运作。 学习核心组件、设计模式和决策框架。

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