AI Saves Old Hospital Systems! Instant Upgrade for Medical Data

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This article addresses the challenge of medical data stored in outdated hospital information systems (HIS). Previously, utilizing this data required complex programming. However, new AI connector tools allow for conversion by simply linking old data fields to new formats, making it as intuitive as a 'connect-the-dots' game. Furthermore, instead of simple batch processing (ETL), the system employs a real-time engine that responds instantly even to minor changes in the old system. This ensures the data is always up-to-date. The application scope is broad; AI can automatically handle complex logic like converting historical calendar years or extracting surnames from Chinese names. Ultimately, this instantaneously and accurately updated data powers Clinical Decision Support Systems (CDSS). This enables 'precision medicine,' allowing doctors to receive precise alerts based on the patient's latest data during consultation. The system also adopts a 'strangling pattern,' enabling gradual expansion from existing old architectures. This allows for safe and low-risk upgrades without disrupting daily hospital operations. The successful implementation promises a substantial improvement in both the patient care experience and the realization of precision medicine.