Korea University Anam Hospital to develop new AI models, medicines with cloud-based HIS

Korea University Anam Hospital, a public tertiary hospital under the Korea University Medical Center, has recently implemented a cloud-based hospital information system.

Developed with the support of the Korean government, the HIS provides the 1,000-bed health facility with modules such as a mobile EMR, mobile personal health record, and AI analysis. KU Anam has been using the system since March.

The hospital is currently undergoing a HIMSS Digital Health Indicator (DHI) assessment to evaluate the system’s quality.


Aside from KU Anam, the cloud HIS has been expanded to KU Guro and Ansan hospitals, enabling the three tertiary medical facilities to share clinical data via cloud. This also facilitates their collaboration for developing new AI models and medicines. 

By using HIS, KU Anam sees potential reduction in medical expenses as duplicate examinations are eliminated through the exchange of medical data between the hospitals. 

“The cloud hospital information system will lay the foundation for high-quality medical data collection, enabling more accurate diagnosis and treatment to be provided to patients,” Dr Sangheon Lee, leader of the Biomedical Information Center at KU Anam, said in an interview with HealthcareIT News.

Following its DHI assessment, the hospital wants to compare its system with other HIS across the world to determine if there is further room for improvement. 


During the interview, KU Anam also mentioned a few other initiatives that they are undertaking. One of these is standardised medical big data on its cloud HIS and building a clinical data warehouse that can run analysis and perform AI modelling based on big data. Through these initiatives, the hospital aims to promote the discovery of AI medical devices, new digital drugs and AI-based drug substances. 

KU Anam is undergoing the HIMSS DHI assessment, which was introduced in April last year. The DHI helps health systems assess their current levels of digital maturity and how they can improve that over time. It looks at four key measurements or outcomes: governance and workforce, interoperability, person-enabled health, and predictive analytics.

In August last year, the DHI framework was used in a project in Queensland, Australia that sought to craft a data-driven roadmap for the digital transformation of the state’s hospitals and health facilities.


“How well patient-specific precision medicine is implemented using data will be the most important variable for future hospitals. It is critical to encourage AI companies with the world’s best precision medicine technology to work with patients and hospitals to develop the world’s best AI solution. Furthermore, using accumulated medical big data for research could be important for precision medical AI development and new drug development,” Dr Lee said.

“Hospitals cooperating with AI companies will be important for future medical care. We think that utilising the cloud system is the best way and the world’s best hospitals will gradually move this direction. We clouded the [HIS] to create the world’s best quantitative and qualitative medical big data. The cloud system can be used by tertiary hospitals with more than 1,000 beds and enables several hospitals to use the same terminology, same code, and same program. We developed a medical big data platform so that medical data can be collected from multiple hospitals. Based on this, we plan to continuously develop and improve patient-tailored precision medical solutions and conduct research on big data,” he added.

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