• 한국병원경영학회지
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• 제28권3호
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• pp.1-14
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• 2023

Purposes: It is very important to establish a clinical data warehouse based on a common data model to offset the different data characteristics of each medical institution and for drug surveillance. This study attempted to establish a clinical data warehouse for Dankook university hospital for drug surveillance, and to derive the main items necessary for development. Methodology/Approach: This study extracted the electronic medical record data of Dankook university hospital tracked for 9 years from 2013 (2013.01.01. to 2021.12.31) to build a clinical data warehouse. The extracted data was converted into the Observational Medical Outcomes Partnership Common Data Model (Version 5.4). Data term mapping was performed using the electronic medical record data of Dankook university hospital and the standard term mapping guide. To verify the clinical data warehouse, the use of angiotensin receptor blockers and the incidence of liver toxicity were analyzed, and the results were compared with the analysis of hospital raw data. Findings: This study used a total of 670,933 data from electronic medical records for the Dankook university clinical data warehouse. Excluding the number of overlapping cases among the total number of cases, the target data was mapped into standard terms. Diagnosis (100% of total cases), drug (92.1%), and measurement (94.5%) were standardized. For treatment and surgery, the insurance EDI (electronic data interchange) code was used as it is. Extraction, conversion and loading were completed. R language-based conversion and loading software for the process was developed, and clinical data warehouse construction was completed through data verification. Practical Implications: In this study, a clinical data warehouse for Dankook university hospitals based on a common data model supporting drug surveillance research was established and verified. The results of this study provide guidelines for institutions that want to build a clinical data warehouse in the future by deriving key points necessary for building a clinical data warehouse.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 국제컨퍼런스 디지털컨텐츠 활용을 통한 지식경영의 확산
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• pp.113-118
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• 1999

본 연구는 통합병원정보시스템 (Integrated Hospital Information System) 에서 의료용 데이터 웨어하우스 (Medical Data Warehouse) 부분의 보안 프로토타입 시스템을 메타데이터 기반으로 설계하고 구현하는 데 주안점을 두었다. 특히, 의료용 데이터 웨어하우스 중에서도 임상 데이터 웨어하우스 (Clinical Data Warehouse) 에 초점을 두었으며 이에 대한 프로토타입은 ㅈ 병원에 적용되어서 개발되었다.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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• pp.393-402
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• 1999

과거와 다르게 최근의 병원들은 정보화로 인해서 상당한 양의 의료 데이터가 저장되어 있어서 이의 효과적인 이용에 관심을 가지고 있다. 그러나 기존 통합병원정보시스템 (Integrated Hospital Information System)은 아직까지 일반관리와 원무관리 중심에서 벗어나지 못하고 있다. 품질 좋은 의료 서비스를 제공하기 위해서 환자 중심의 진료 및 진료지원, 임상연구 등을 종합적으로 지원하기 위한 데이터 웨어하우스 (Data Warehouse)의 필요성이 대두되기 시작했다. 이에 본 연구는 병원 전체 차원에서 데이터 웨어하우스의 아키텍쳐를 설계하고 개발하는 데 주안점을 두었다. 특히, 임상 데이터 웨어하우스 (Clinical Data Warehouse)에 초점을 두었으며 이에 대한 프로토타입은 J 병원에 적용되어서 개발되었다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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• pp.393-402
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• 1999

과거와 다르게 최근의 병원들은 정보화로 인해서 상당한 양의 의료 데이터가 저장되어 있어서 이의 효과적인 이용에 관심을 가지고 있다. 그러나 기존 통합병원정보시스템(Integrated Hospital Information System)은 아직까지 일반관리와 원무관리 중에서 벗어나지 못하고 있다. 품질 좋은 의료 서비스를 제공하기 위해서 환자 중심의 진료 및 진료지원, 임상연구 등을 종합적으로 지원하기 위한 데이터 웨어하우스(Data Warehouse)의 필요성이 대두되기 시작했다. 이에 본 연구는 병원 전체 차원에서 데이터 웨어하우스의 아키텍쳐를 설계하고 개발하는 데 주안점을 두었다. 특히, 임상 데이터 웨어하우스(Clinical Data Warehouse)에 초점을 두었으며 이에 대한 프로토타입은 J 병원에 적용되어서 개발되었다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2002년도 추계정기학술대회
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• pp.203-212
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• 2002

This study examined the predictive power of data mining algorithms by comparing the performance of logistic regression and decision tree algorithm, called CHAID (Chi-squared Automatic Interaction Detection), On the contrary to the previous studies, decision tree performed better than logistic regression. We have also developed a CDSS (Clinical Decision Support System) with three modules (doctor, nurse, and patient) based on data warehouse architecture. Data warehouse collects and integrates relevant information from various databases from hospital information system (HIS ). This system can help improve decision making capability of doctors and improve accessibility of educational material for patients.

• 디지털융복합연구
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• 제11권8호
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• pp.293-302
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• 2013

지금까지의 병원의 DW(Data Warehouse)는 주로 원무중심의 데이터를 분석하는 용도로 사용되어 왔다. 하지만, 전자의무기록(Electronic Medical Record) 시스템이 구축되면서 원무중심의 기존의 DW와 달리 진료 기록과 영상 촬영 기록의 판독내용 등의 비정형 데이터도 환자의 진료 및 치료의 중요한 정보를 얻는데 매우 유익하게 활용될 수 있다. 따라서 본 논문에서는 지금까지 병원에서 활용되는 원무 중심의 DW(Medical DW)가 아닌 진료 중심의 DW(Clinical DW)의 구축의 필요성을 제기하였다. 또한 CDW가 실제로 어떤 부분에 어떻게 활용되는 지를 기술하였다. 마지막으로 병원의 실제 진료 데이터를 시소러스(Thesaurus)검색 방법을 사용하여 과거 이력에 따른 연관 상병 간의 상관관계를 도출하여 환자 조기치료의 기반을 마련하고자 한다.

• Genomics & Informatics
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• 제11권4호
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• pp.186-190
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• 2013

The advances in electronic medical records (EMRs) and bioinformatics (BI) represent two significant trends in healthcare. The widespread adoption of EMR systems and the completion of the Human Genome Project developed the technologies for data acquisition, analysis, and visualization in two different domains. The massive amount of data from both clinical and biology domains is expected to provide personalized, preventive, and predictive healthcare services in the near future. The integrated use of EMR and BI data needs to consider four key informatics areas: data modeling, analytics, standardization, and privacy. Bioclinical data warehouses integrating heterogeneous patient-related clinical or omics data should be considered. The representative standardization effort by the Clinical Bioinformatics Ontology (CBO) aims to provide uniquely identified concepts to include molecular pathology terminologies. Since individual genome data are easily used to predict current and future health status, different safeguards to ensure confidentiality should be considered. In this paper, we focused on the informatics aspects of integrating the EMR community and BI community by identifying opportunities, challenges, and approaches to provide the best possible care service for our patients and the population.

• 동의생리병리학회지
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• 제35권5호
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• pp.132-138
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• 2021

Artificial intelligence technology sheds light on new ways of innovating acupuncture research. As acupoint selection is specific to target diseases, each acupoint is generally believed to have a specific indication. However, the specificity of acupoint selection may be not always same with the specificity of acupoint indication. In this review, we propose that the specificity of acupoint indication can be inferred from clinical data using reverse inference. Using forward inference, the prescribed acupoints for each disease can be quantified for the specificity of acupoint selection. Using reverse inference, targeted diseases for each acupoint can be quantified for the specificity of acupoint indication. It is noteworthy that the selection of an acupoint for a particular disease does not imply the acupoint has specific indications for that disease. Electronic medical record includes various symptoms and chosen acupoint combinations. Data mining approach can be useful to reveal the complex relationships between diseases and acupoints from clinical data. Combining the clinical information and the bodily sensation map, the spatial patterns of acupoint indication can be further estimated. Interoperable medical data should be collected for medical knowledge discovery and clinical decision support system. In the era of artificial intelligence, machine learning can reveal the associations between diseases and prescribed acupoints from large scale clinical data warehouse.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권4호
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• pp.268-275
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• 2014

In future, hospitals are expected to automatically issue remote transcriptions. Many general hospitals are planning to encrypt their medical database to secure personal information as mandated by law. The electronic medical record system, picture archiving communication system, and the clinical data warehouse, amongst others, are the preferred targets for which stronger security is planned. In the near future, medical systems can be assumed to be automated and connected to remote locations, such as rural areas, and islands. Connecting patients who are in remote locations to medical complexes that are usually based in larger cities requires not only automatic processing, but also a certain amount of security in terms of medical data that is of a sensitive and critical nature. Unauthorized access to patients' transcription data could result in the data being modified, with possible lethal results. Hence, personal and sensitive data on telemedicine and medical information systems should be encrypted to protect patients from these risks. Login passwords, personal identification information, and biological information should similarly be protected in a systematic way. This paper proposes the use of electronic acupuncture with a built-in multi-pad, which has the advantage of being able to establish a patient's physical condition, while simultaneously treating the patient with acupuncture. This system implements a sensing pad, amplifier, a small signal drive circuit, and a digital signal processing system, while the use of a built-in fuzzy technique and a control algorithm have been proposed for performing analyses.

• 디지털콘텐츠
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• 7호통권74호
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• pp.44-49
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• 1999

과거와 다르게 최근의 병원들은 정보화로 인해서 상당한 양의 의료 데이터가 저장되어 있어서 이의 효과적인 이용에 관심을 가지고 있다. 그러나 기존 통합병원정보시스템(Integrated Hospital Information System)은 아직까지 일반관리와 원무관리 중심에서 벗어나지 못하고 있다. 품질 좋은 의료 서비스를 제공하기 위해서 환자 중심의 진료 및 진료지원, 임상연구 등을 종합적으로 지원하기 위한 데이터 웨어하우스의 필요성이 대두되기 시작했다 .이 글에서는 최근 임상 데이터 웨어하우스(Clinical Data Warehouse)에 초점을 둔 J병원 사례와 연구를 중심으로 기술한다.