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Customer Snapshot

Delivering Superior, Paperless, and Lower-Costing Care


In the Asia-Pacific region to have a fully digitalized paperless hospital


The Seoul National University Bundang Hospital is the digital cornerstone of the South Korean national healthcare system. By analyzing big data in real-time, SNUBH continually elevates its world-class standards for medical science, education, research, and patient care.


Seoul National University Bundang Hospital (SNUBH)


Bundang, South Korea

Customer Website



$US275 million

Number of Employees

515 physicians, 780 nurses, 640 staff

Implementation Partners


Line of Business

R&D, Engineering, Information Technology



Featured Products

SAP HANA, SAP Data Services


More than a century of care

The Seoul National University Bundang Hospital is one of the specialty branches of the SNUH system. It is South Korea’s national medical research hospital dedicated to the study and treatment of geriatric diseases. It is also a regional medical center that provides general and emergency care to nearby residents. When SNUBH opened in 2003, it was the first fully digital, paperless hospital in the Asia-Pacific region.


  • 1885King Gojong and the government of the Joseon Dynasty established Jejung Hospital, the first modern public hospital of Western medicine in Korea.
  • 1899The Korean government established Gyeongseong Medical School, predecessor of Seoul National University College of Medicine, and Gwangje Hospital.
  • 1903The medical school’s first graduating class of 19 students received diplomas.
  • 1907The Empire of Korea established Daehan Hospital by combining Gyeongseong Medical School, Gwangje Hospital, and the Korean Red Cross Hospital.
  • 1910Japan annexed Korea. Daehan Hospital was renamed the Government-General of Korea (GGK) Hospital.
  • 1928GKK Hospital affiliated with Gyeongseong Imperial University of College of Medicine
  • 1945 Gyeongseong Imperial University College of Medicine became Gyeongseong University.
  • 1946Gyeongseong University and Gyeongseong Medical College became Seoul National University.
  • 1978Seoul National University Hospital became a special corporation
  • 1985SNUH opened the first Children's Hospital in Korea.
  • 1998SNUH researchers determined the cause of Hodgkin's disease.
  • 2003Seoul National University Bundang Hospital opened, and was the first fully paperless hospital in Asia-Pacific region.
  • 2010SNUBH became the first hospital outside the United States to receive HIMSS Analytics Stage 7 Award.

Business Model

Driving outcomes with evidence

Through a combination of quantitative and qualitative evidence, SNUBH bridges the gap between medical research and clinical practice. Doctors, nurses, and allied health professionals use data to inform clinical decision-making in the diagnosis and management of individual patients. The hospital also combines research, clinical, and business data to inform and continually improve its operations and quality of care.

Success Strategy

Pioneering paperless recordkeeping

SNUBH is built on a foundation in which electronic medical records have replaced paper charts. Each patient’s treatment data is computerized so that clinicians and researchers can review records on any enabled device, whether they are in their offices, a laboratory, or at the point of care.


HIMSS Analytics Stage 7 designees can:



Patient clinical information electronically within the entire health information exchange network



The widespread and comprehensive use of health and wellness information by consumers and providers

More Effectively

Capture and analyze care data to improve operations, finances, and care delivery



In 2010, Healthcare Information and Management Systems Society (HIMSS) Analytics bestowed its Stage 7 designation on the hospital for achieving all the steps to become a paperless hospital.

The Challenge

Managing more data in less time

The hospital began operating its data warehouse in 2004, but data retrieval was slow and data quality was inconsistent. Much of the data was unstructured text, such as physician notes, mixed with medical imaging such as CAT scans, X-rays, or MRIs. So a query through ten years’ of data might take an hour to retrieve. If the system failed to retrieve the correct data, researchers or clinicians would have to contact IT for a manual data retrieval, which could take another three to five days.


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Finding the right medications as quickly as possible

In 2006, the hospital launched a health information exchange for sharing patient records internally and with more than 50 other clinics and hospitals. A year later, SNUBH added RFID sensors and barcode technology to better manage assets and to reduce medication errors. These changes flooded the hospital database with even more data to monitor and manage.

Enter SAP

A shared heritage of innovation

SNUBH began evaluating Big Data solutions at about the same time SAP HANA was released in 2010. Although many criteria were ultimately used to select its clinical data warehouse (CDW), the hospital was attracted by the common roots it shares with SAP HANA. The memory-centric, lightweight, online transaction processing system (OLTP) at the heart of SAP HANA was developed by engineers at Seoul National University.


The SAP Experience

Multidimensional analysis using
350 clinical indicators

To maintain its technological edge over competing hospitals in South Korea, and to mitigate legal risks and costs, SNUBH executives committed to implementing SAP HANA as its CDW. Data marts were created within the CDW according to defined conditions of 350 clinical indicators staged from the hospital information system (HIS) using SAP Data Services as the ETL tool. With business intelligence tools that support multidimensional analysis, users can pull reports and develop models.

Better Business

Improving health and healthcare research in real-time

Deployment of the SAP HANA database helps SNUBH researchers retrieve key data for their work in real-time while it helps clinicians improve patient care. With a simple operation, hospital staff can now access the clinical indicator system to view their status relative to goals, as well as analysis reports for continuous improvement.


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The speed of SAP HANA

On the research side, SAP HANA has reduced wait times for complicated data queries from more than one hour to less than five seconds. Besides improving productivity, researchers claim it helps them pursue ideas that might otherwise be forgotten, a risk they faced particularly when a manual data pull might take days to complete.


Eliminating unnecessary medication and expense

Using real-time feedback, SNUBH evaluated clinical practice guidelines for preoperative antimicrobial prophylaxis. In South Korea, the national standard was to administer third-line antibiotics for five to six days before surgery. By comparison, the standard in the United States is to administer first-line antibiotics for one to two days before surgery. Third-line antibiotics are highly potent medicines typically used to treat multidrug resistant (MDR) pathogens. First-line antibiotics, on the other hand, offer several advantages including proven safety, availability, and cost.


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Reducing antibiotic usage before surgeries

Clinical indicator analysis powered by the SAP HANA CDW, SNUBH dramatically reduced the unnecessary use of antibiotics. Third-line preoperative antibiotic use dropped to zero and the duration that antibiotics were administered to patients before surgery fell from six days to one. Besides lowering drug costs, reduced antibiotic use helps decrease inpatient lengths of stay by minimizing risks associated with antibiotic resistance.

Run Simple

Making quality decisions

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Merits of the SAP HANA system

SNUBH continues to refine how it uses SAP HANA, particularly after discovering how effectively real-time data analysis can guide clinical and business decisions.

Journey Ahead

Evolving lower cost healthcare for aging population

The clinical data warehouse at SNUBH, powered by SAP HANA, will continue to be the centerpiece of the hospital’s evidence-based medical delivery model. As healthcare delivery evolves in the region, and as an aging population begins to consume more healthcare resources, data analysis becomes even more important in determining which hospitals provide the best health outcomes at the lowest cost.


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Best choice for physicians and staff…

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