• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.234-236
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• 2000

최근 국내의 모든 병원에서 PACS(Picture Atchiving and Communication System) 도입에 관한 관심을 보이고 있다. PACS가 구축이 되면 병원 내 모든 진료 과에서 디지털 데이터의 전송으로 정보를 공유할 수 있고, 진료가 자동화 되는 장점이 있다. 하지만, 환자가 다른 병원으로 이송될 경우 과거 진료 내역을 다른 병원으로 함께 전송하여야 되는데, 다른 병원의 시스템과 연계할 방법이 현재로는 존재하지 않는다. HIES 시스템은 의료 데이터 전송의 표준문서로 XML(eXtensible Markup Language)을 제안하고 있다. XML은 문서를 정의하는 메타 마크업(meta-markup) 언어로써 DICOM 프로토콜을 통하여 산출된 의료 데이터를 표현하기에 적당하다. 또한 병원 간 이질 데이터베이스 시스템 통합을 위하여 일관된 스키마 정보를 유지하는 정보 공유 관리자를 설계, 구현하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.12
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• pp.1403-1410
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• 2015

The purpose of this study is to provide ways to utilize and create valuable medical information utilizing Medical Big Data created by field in hospital information system. The results of this study first creates new medical information of Medical Information system through medical big data analysis and integration of created data of PACS linked with many kinds of testing equipment and medical image equipment along with medical treatment information. Medical information created in this way produces various health information for treatment and prevention of disease and infectious disease. Second, it creates profit statistics information in various ways by analyzing medical big data accumulated through integration of billings and receipt, admission breakdown of patients. Profit statistics information created in this way produces various administration information to be utilized in profit anaysis and operation of medical institution. Likewise, data integration of personal health history, medical information of public institutions, medical information created in hospital information system produces valuable medical health information utilizing medical data.

• Smart Media Journal
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• v.7 no.3
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• pp.22-28
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• 2018

Air pollution problems in Korea are gradually becoming a higher concern due to various reasons such as fine dust, causing anxiety among people with regard to their health. Although various studies have been carried out on the relationship between the influence of fine dust and a certain disease, they are mostly focusing on the analyzation that fine dust is related to specific illnesses such as respiratory and cardiovascular diseases, hypertension and diabetes. In this paper, we utilize the public data of medical history information to extract ten medical care subjects with the highest number of monthly care in 2016, and analyze the relation of fine dust with certain medical subjects using Pearson correlation coefficient. We also subdivide and analyze the correlation between fine dust and the medical subjects according to their gender and age. Middle-aged Female group with the strongest positive correlation between fine dust and the medical subjects is analyzed with the correlation from 2011 to 2015, with its relevance coefficient extracted by regression analysis in order to predict the correlation with the medical subjects according to the fine dust concentration.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.207-212
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• 2018

As a data analysis tool which is becoming popular in the Big Data era, R is rapidly expanding its user range by providing powerful statistical analysis and data visualization functions. Major advantage of R is its functional scalability based on open source, but its scale scalability is limited, resulting in performance degrades in large data processing. RHadoop, one of the extension packages to complement it, can improve data analysis performance as it supports Hadoop platform-based distributed processing of programs written in R. In this paper, we evaluate the validity of RHadoop by evaluating the performance improvement of RHadoop in real medical big data analysis. Performance evaluation of the analysis of the medical history information, which is provided by National Health Insurance Service, using R and RHadoop shows that RHadoop cluster composed of 8 data nodes can improve performance up to 8 times compared with R.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.368-370
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• 2022

WHO 산하의 국제암연구소는 2013 년부터 미세먼지를 1 급 발암 물질로 분류하고 있으며 미세먼지 노출에 대한 질병 발생의 심각성은 점점 수면 위로 드러나고 있는 추세다. 본 연구에서는 국민건강보험공단의 진료 내역 정보 데이터와 2015 년부터 2021 년까지의 미세먼지 및 초미세먼지 월 평균 농도 데이터를 이용하여 미세먼지 및 초미세먼지 농도와 순환기계와 호흡기계 질병 간의 상관 관계를 보이고, 연관성있는 질병을 찾아내었다. 이를 위해 시계열분석, 상관분석, 빈도분석을 시행하였으며 실험 결과 호흡기질환에서는 급성 부비동염, 코의 농양 등의 질병과 순환기질환에서는 상세불명의 원발성 고혈압, 폐색전증이 상관관계가 높은 질병으로 판명되었다.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.184-191
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• 2022

This study aims to provide basic information necessary to find an efficient management plan for patients using auto insurance. The analysis was conducted on the five-year auto insurance medical expenses review data registered in the health care bigdata Hub from 2016 to 2020. As a result of the analysis, the number one composition ratio of auto insurance inpatient treatment expenses was treatment and surgery fees for Certified tertiary hospitals, hospitalization fees for general hospitals, hospitals and clinics, and treatment and surgery fees for oriental medical institutions and dental hospitals. outpatient treatment expenses was doctor's fee for medical institution, treatment and surgery fees for oriental medical institutions and dental hospitals. The ratio of medication, anesthesia, and special equipment significantly affected the cost of inpatient. And the ratio of physical therapy significantly affected the cost of outpatient.

• Journal of the Health Care and Life Science
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• v.11 no.1
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• pp.11-23
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• 2023

In this study, a practice model that can improve healthcare information management ability using Chat GPT and SQL was studied. For SQL utilization, learners were asked to use Chat GPT to easily access the database and write SQL for data extraction. For the contents analyzed in the claims database, the sum of insurance claim amount, insurance claim amount by treatment item, claim details corresponding to a specific amount, other diagnosis names of specific prescription patients, examination details of specific diagnosis names, and total amount by item were calculated. As a result of executing SQL statements written for each subject in Chat GPT, it was confirmed that the analysis contents were the same. It is believed that the use of ChatGPT as progressed in this study will contribute to improving the ability of healthcare data management to increase accuracy and efficiency in database management and analysis work, rather than simply simplifying or automating tasks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.115-117
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• 2017

R has become a popular analytics platform as it provides powerful analytic functions as well as visualizations. However, it has a weakness in which scalability is limited. As an alternative, the RHadoop package facilitates distributed processing of R programs under the Hadoop platform. This paper investigates usefulness of the RHadoop package when analyzing healthcare big data that is widely open in the internet space. To do this, this paper has compared analytic performances of R and RHadoop using the medical treatment records of year 2015 provided by National Health Insurance Service. The result shows that RHadoop effectively enhances processing performance of healthcare big data compared with R.

• Journal of the Health Care and Life Science
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• v.9 no.1
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• pp.1-9
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• 2021

In this study, a model in which certification standards were added to the health information management practice program was studied and presented in order to understand the EMR certification standards implemented by the Korea Health and Medical Information Service. In the practice program, the certification standard function for patient information management was added to the health information management education system to practice and understand patient information management that corresponds to the functional standard of the EMR certification system. The EMR certification standard practice program for patient information management is composed of the following certification standards. registration number and personal information management, treatment reservation schedule management, personal information revision history management, identification of people with the same name, integrated management of multiple registration numbers, patient search by identification information, patient search by health care type, surgical procedure consent record and inquiry, record/inquiry of consent form for personal information use, display of life-sustaining medical decision information, registration/inquiry of external medical institution documents, registration and inquiry of external examination results. In this way, by operating and practicing the functions of the health information system according to the certification standards, it is possible to understand and practice the certification standards and details of patient information management in the functional area of the certification standards. In addition, since the function of the EMR certification standard can be checked, it will be possible to improve the management ability of the electronic medical record system of the health information manager in the medical institution.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.10
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• pp.1009-1016
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• 2016

In this study, an educational program was developed. The program can perform the claim for examination of medical expense, which is one of NCS Competence Unit Elements for hospital administration. Considering various coding to complex compute and process, VB.Net was employed for this development. For database, ACCESS Database was used because it is easy to learn and use. The learning effects by the developed program are expected to be as follows. First, the composition of medical expense can be understood by analyzing Medical history and then selecting insurance code according to the Standard of Medical Care Code. Second, unit cost per score can be learned according to hospital class. Third, selection of Column (medical materials) and Column II(medical practice) can classify items of additional ratio. Fourth, because patient's payment rate on hospitalization and meal expense and use of special equipment are differently applied, user can know patient's payment rate by type and can calculate it. Fifth, additional amount is the amount calculated by additional ratio of Column II(medical practice), and user can learn additional ratio according by insurance type and hospital class. Sixth, user can learn self-pay rate by hospital class and understand the process that self-pay amount and claim amount are calculated according by self-pay rate.