Big Data for Medicine in Korea

South Korea, a world leader in information technology (IT) infrastructure, has been taking big data to the next level over the past years. So far, Korea excelled in engaging big data in service delivery in the public sector, policy making, and building foundations for the future by effectively utilizing its solid IT infrastructure. Of the big data developments yet, one that especially stands out from a global standpoint is the advancement of big data in Korea’s medical system.

Progress and Efforts in Korea

n 2011, the President’s Council on National ICT Strategies, launched a big data task-force under the Big Data Initiative. This initiative aimed to establish:

  • a pan-governmental big data network & analysis systems
  • data convergence between government and private sector
  • a diagnosis system for public big data
  • big data management & analytical technologies

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The initiative also included several public and private collaboration with Big Data Strategy Center, a national institute of Korea under National Information Society Agency (NIA), and Big Data Institute, an academic institute of Seoul National University. The Korean Bio-Information Center (KOBIC), along with the initiative, also planned to operate the National DNA Management System which can provide customized diagnosis and medical treatment for patients by integrating big data on various types of medical patient information.

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Entrance to the Big Data Institute at Seoul National University. Source: Big Data Institute

In January 2014, South Korea’s Ministry of Science, ICT and Future Planning (MSIP) and the NIA released the Medical Information Consulting program. The program suggests a big data service which can help diagnose and customize treatment for patients which will help promote public health and streamline the management of medical facilities. The program’s end goal is to naturally bring the program’s collected medical data together with the existing statistical data from the Health Insurance Review & Assessment Service (HIRA).

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This big data service is designed to provide to the patients:

  • Information of the exact name of patients’ illness through a natural language search of medical dictionaries
  • Estimated duration of illness
  • Costs of medical treatments for the diseases based on HIRA’s 7.58 billion evaluated cases (which have been recorded previously) and 11.6 billion cases of prescription information
  • The supply and demand of medical service (such as medical centers and medical nursing homes) in specific regions based on 22,000 cases of medical institutes, local populations, and the institutes’ incomes

The service will also benefit the medical industry by providing:

  • Information regarding distribution of medicine
  • Prescription tendencies
  • Medical equipment distribution on a national scale based on the cases of pharmaceutical production, supply of pharmaceutical goods and medical devices.

 

Case Study of Seoul National University Bundang Hospital

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Seoul National University Bundang Hospital. Source: Archdaily

The Seoul National University Bundang Hospital (SNUBH) is the first hospital in the Asia-Pacific region to be fully digitalized and paperless. Established in 2003, SNUBH is a national medical research hospital and hosts a regional medical center that provides general and emergency care to patients in the area.

At SNUBH, the doctors use in-memory computing to improve preoperative care with real-time feedback by featured products from SAP HANA and SAP Data Services. With the digitalized big data service, doctors and nurses are able to configure the systems with precise clinical information. Currently at SNUBH, there are approximately 3,000 different end-user configurations. This real-time data feedback reduced the time of patient referral from 48-hours to 4-6 hours. For instance, the doctors are able to efficiently reduce the dosage of antibiotics accordingly before in time for surgery thanks to the real-time big data feedback. This small, yet, noteworthy reduction of antibiotics cuts costs for patients and also helps prevent the growth of drug-resistant bacteria, which can be a “huge clinical significance to the patient” according to Dr. Hee Hwang, the CIO at SNUBH.

 

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SNUBH’s executive staff with smart devices that are used in the hospital on a daily basis. Source: SNUBH Presentation on Introduction of SNUBH’s Healthcare System

In 2006, SNUBH introduced the Hospital Information Exchange System for easy sharing of patient records through big data. SNUBH has shared its digitalized medical records with more than fifty primary clinic hospitals up to year 2014. These data guides clinical decision-making, diagnosis and management of individual patients for other clinic hospitals. Through a combination of quantitative and quantitative data, SNUBH combined research, clinical, and business data to take its operations and quality of patient care to another level.

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Wireless device and system used in SNUBH. Source: SNUBH Presentation on Introduction of SNUBH’s Healthcare System

 

Challenges and Prospects

There are still many challenges to the big data medical system. However, these points do not necessarily mean the current system is at a complete impasse.

Challenge 1: Accuracy and Speed

Whether accuracy and speed can work hand-in-hand in big data analytics to provide the best diagnosis possible is the most important question since there is no advantage of the system if the retrieved data is not relevant or accurate. Patient to doctor interaction and patient care are both significant components of medical service; yet, the digitalized system may overlook these elements. However, if the IT platform can combine speed with visualization tools and guided analytics, data can be used as an insight, and it may help mend the possible shortcoming of the technology.

Challenge 2: Regulatory Barrier

Due to some concerns regarding privacy and security, some may hesitate to fully install the big data system in medical facilities. If the private information is not properly managed and protected, there can be an infringement on privacy, which may have critical effects on patient’s privacy. Also, if the links are weak between the authority managing the data and accountability of hospital’s administration system, there is always a possibility that patient’s information can leak through the internal staff. Thus, a strong link between those that manage data and hospital administration is a necessity for the patient’s information to be protected.

Challenge 3: Human Resource

Although Korea’s IT infrastructure is strong, Korean IT healthcare industry is lacking capable professionals who can develop and fully utilize the digitalized big data services. But this problem can be somewhat resolved. Providing more educational curriculum in an electronically equipped learning/practice environment for health professionals can simply generate more human resource in the relevant specialty. As such, the South Korean government has been recruiting foreign talent and pushing IT-related programs in some of Korea’s universities.

Challenge 4: Familiarity with the New System

Korea Institute for Industrial Economics and Trade surveyed local patient’s the awareness level of the big data services in 2011. The results showed that the general public was not accustomed to the digitalized service. The recognition level of telemedicine service was at 33.8% and the telehealth management service was at 27.2%. Participation (patients’ decision to use the digitalized health service) was even lower – 29.2% for telemedicine and 26.8% for telehealth management. However, when asked if the surveyors would consider using the digitalized service 5 years after the service has been fully implemented, the responses were more positive. 62.4% answered “yes” for using telemedicine in the future, and for telehealth management program, 64.2% answered “yes.” If technological stability is proven in the next several years, there will not be a major problem of popularizing the system.

Challenge 5: Compatibility

The last challenge for Korea is compatibility. Some institutional regulations such as medical insurance support, medical fees, and responsibility for medical accidents may stand as obstacles during the stage of implementation of big data service. The South Korean government has been continuously making an effort to implement the service in areas with limited access of medical facilities. Nevertheless, without modifying the existing laws and regulations (in medical insurance, fees and accidents) more compatible with the big data system, enforcing the big data service in medical institutions will be difficult in the near future.

Concluding Words

As the potential of big data in medical environment is widely recognized, Korean government actors and stakeholders are largely investing in big data projects which help the advancement of big data research. These efforts’ success will be determined by the expansion of technical capability in effectively integrating and accurately analyzing the collected medical information by taking a step-by-step approach with realistic expectations.