• Title/Summary/Keyword: 환자 데이터 표준화

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A Study on analysis of severity-adjustment length of stay in hospital for community-acquired pneumonia (지역사회획득 폐렴 환자의 중증도 보정 재원일수 분석)

  • Kim, Yoo-Mi;Choi, Yun-Kyoung;Kang, Sung-Hong;Kim, Won-Joong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.3
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    • pp.1234-1243
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    • 2011
  • Our study was carried out to develop the severity-adjustment model for length of stay in hospital for community-acquired pneumonia so that we analysed the factors on the variation in length of stay(LOS). The subjects were 5,353 community-acquired pneumonia inpatients of the Korean National Hospital Discharge In-depth Injury Survey data from 2004 through 2006. The data were analyzed using t-test and ANOVA and the severity-adjustment model was developed using data mining technique. There are differences according to gender, age, type of insurance, type of admission, but there is no difference of whether patients died in hospital. After yielding the standardized value of the difference between crude and expected length of stay, we analysed the variation of length of stay for community-acquired pneumonia. There was variation of LOS in regional differences and insurance type, though there was no variation according whether patients receive their care in their residences. The variation of length of stay controlling the case mix or severity of illness can be explained the factors of provider. This supply factors in LOS variations should be more studied for individual practice style or patient management practices and healthcare resources or environment. We expect that the severity-adjustment model using administrative databases should be more adapted in other diseases in practical.

Expression of MicroRNA-221 in Korean Patients with Multiple Myeloma (한국인의 다발성골수종 환자에서 MicroRNA-221의 발현)

  • Choi, Woo-Soon
    • Korean Journal of Clinical Laboratory Science
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    • v.50 no.2
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    • pp.197-204
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    • 2018
  • Multiple myeloma (MM) is the leading cause of death among hematologic neoplasms. Recently, microRNA has been reported to be useful in the diagnosis of multiple myeloma. This study examined whether miR-221 could be used as a diagnostic marker for multiple myeloma. The study was performed on 20 patients with multiple myeloma without any other hematological diseases. MicroRNA extraction was performed using formalin-fixed paraffin-embedded (FFPE) tissues obtained from the bone marrow of patients with multiple myeloma. miR-15a, miR-16, miR-21, miR-181a, and miR-221 were selected as the microRNA target genes for multiple myeloma. The significance of microRNA was based on a fold change of <1.5. To quantify the fold changes, data normalized to the human gene, SNORD43, were used as the values of the patient group. Fold change values greater than 1.5 were defined as "overexpression", whereas values less than -1.5 were defined as "underexpression". Of note, 65.0% (13/20) of samples showed significant "overexpression" in the levels of miR-221 expression and plasma cells with a group of more and less than 30% in MM patients did not show any significance of plasma cell (P<0.05). The results of other studies showing a correlation between the expression of miR-221 and MM in Caucasians were confirmed. These results suggest that miR-221 may be a useful indicator for diagnosing patients with MM. In conclusion, miR-221 is useful in the diagnosis and determining the prognosis of multiple myeloma in Koreans.

Finite Element Method Modeling for Individual Malocclusions: Development and Application of the Basic Algorithm (유한요소법을 이용한 환자별 교정시스템 구축의 기초 알고리즘 개발과 적용)

  • Shin, Jung-Woog;Nahm, Dong-Seok;Kim, Tae-Woo;Lee, Sung Jae
    • The korean journal of orthodontics
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    • v.27 no.5 s.64
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    • pp.815-824
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    • 1997
  • The purpose of this study is to develop the basic algorithm for the finite element method modeling of individual malocclusions. Usually, a great deal of time is spent in preprocessing. To reduce the time required, we developed a standardized procedure for measuring the position of each tooth and a program to automatically preprocess. The following procedures were carried to complete this study. 1. Twenty-eight teeth morphologies were constructed three-dimensionally for the finite element analysis and saved as separate files. 2. Standard brackets were attached so that the FA points coincide with the center of the brackets. 3. The study model of a patient was made. 4. Using the study model, the crown inclination, angulation, and the vertical distance from the tip of a tooth was measured by using specially designed tools. 5. The arch form was determined from a picture of the model with an image processing technique. 6. The measured data were input as a rotational matrix. 7. The program provides an output file containing the necessary information about the three-dimensional position of teeth, which is applicable to several finite element programs commonly used. The program for a basic algorithm was made with Turbo-C and the subsequent outfile was applied to ANSYS. This standardized model measuring procedure and the program reduce the time required, especially for preprocessing and can be applied to other malocclusions easily.

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A Design of Clinical Information Exchange Framework for Performance Improvement based on Lazy Response Model (지연 응답 모델에 기반한 성능 개선 진료정보 교류 프레임워크의 설계)

  • Lee, Se-Hoon;Shim, Woo-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.9
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    • pp.157-164
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    • 2012
  • Recently medical service environment, the clinical information exchange which contribute to medical safety, promotion of service quality and patient's convenience, efficiency of medical procedures and medical management is essential medical service model. But, practical exchange of clinical information which variation of information level, absence of standardization system, build of heterogeneous information systems is difficult in each medical institute. In this paper, We analyzed the related technical standardizations and the models of clinical information exchange. So, we designed the clinical information exchange system based on the ideal lazy response model which is aimed at vitalizations the exchange of clinical information under domestic law environment. In case of exchange the clinical information, we separate CDA document flow from metadata flow. As a experimental result we acquired 24% improved performance compared with existed system based on the lazy response model.

Efficient Transmission Structure and Key Management Mechanism Using Key Provisioning on Medical Sensor Networks (의료 센서 네트워크에서의 효율적인 전송 구조 및 Key Provisioning을 사용한 키 관리 기법 연구)

  • Seo, Jae-Won;Kim, Mi-Hui;Chae, Ki-Joon
    • The KIPS Transactions:PartC
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    • v.16C no.3
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    • pp.285-298
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    • 2009
  • According to the development of ubiquitous technologies, sensor networks is used in various area. In particular, medical field is one of the significant application areas using sensor networks, and recently it has come to be more important according to standardization of the body sensor networks technology. There are special characteristics of their own for medical sensor networks, which are different from the one of sensor networks for general application or environment. In this paper, we propose a hierarchical medical sensor networks structure considering own properties of medical applications, and also introduce transmission mechanism based on hierarchical structure. Our mechanism uses the priority and threshold value for medical sensor nodes considering patient's needs and health condition. Through this way Cluster head can transmit emergency data to the Base station rapidly. We also present the new key establishment mechanism based on key management mechanism which is proposed by L. Eschenauer and V. Gligor for our proposed structure and transmission mechanism. We use key provisioning for emergency nodes that have high priority based on patients' health condition. This mechanism guarantees the emergency nodes to establish the key and transmit the urgent message to the new cluster head more rapidly through preparing key establishment with key provisioning. We analyze the efficiency of our mechanism through comparing the amount of traffic and energy consumption with analysis and simulation with QualNet simulator. We also implemented our key management mechanism on TmoteSKY sensor board using TinyOS 2.0 and through this experiments we proved that the new mechanism could be actually utilized in network design.

The Influence Evaluation of $^{201}Tl$ Myocardial Perfusion SPECT Image According to the Elapsed Time Difference after the Whole Body Bone Scan (전신 뼈 스캔 후 경과 시간 차이에 따른 $^{201}Tl$ 심근관류 SPECT 영상의 영향 평가)

  • Kim, Dong-Seok;Yoo, Hee-Jae;Ryu, Jae-Kwang;Yoo, Jae-Sook
    • The Korean Journal of Nuclear Medicine Technology
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    • v.14 no.1
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    • pp.67-72
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    • 2010
  • Purpose: In Asan Medical Center we perform myocardial perfusion SPECT to evaluate cardiac event risk level for non-cardiac surgery patients. In case of patients with cancer, we check tumor metastasis using whole body bone scan and whole body PET scan and then perform myocardial perfusion SPECT to reduce unnecessary exam. In case of short term in patients, we perform $^{201}Tl$ myocardial perfusion SPECT after whole body bone scan a minimum 16 hours in order to reduce hospitalization period but it is still the actual condition in which the evaluation about the affect of the crosstalk contamination due to the each other dissimilar isotope administration doesn't properly realize. So in our experiments, we try to evaluate crosstalk contamination influence on $^{201}Tl$ myocardial perfusion SPECT using anthropomorphic torso phantom and patient's data. Materials and Methods: From 2009 August to September, we analyzed 87 patients with $^{201}Tl$ myocardial perfusion SPECT. According to $^{201}Tl$ myocardial perfusion SPECT yesterday whole body bone scan possibility of carrying out, a patient was classified. The image data are obtained by using the dual energy window in $^{201}Tl$ myocardial perfusion SPECT. We analyzed $^{201}Tl$ and $^{99m}Tc$ counts ratio in each patients groups obtained image data. We utilized anthropomorphic torso phantom in our experiment and administrated $^{201}Tl$ 14.8 MBq (0.4 mCi) at myocardium and $^{99m}Tc$ 44.4 MBq (1.2 mCi) at extracardiac region. We obtained image by $^{201}Tl$ myocardial perfusion SPECT without gate method application and analyzed spatial resolution using Xeleris ver 2.0551. Results: In case of $^{201}Tl$ window and the counts rate comparison result yesterday whole body bone scan of being counted in $^{99m}Tc$ window, the difference in which a rate to 24 hours exponential-functionally notes in 1:0.114 with Ventri (GE Healthcare, Wisconsin, USA), 1:0.249 after the bone tracer injection in 12 hours in 1:0.411 with 1:0.79 with Infinia (GE healthcare, Wisconsin, USA) according to a reduction a time-out was shown (Ventri p=0.001, Infinia p=0.001). Moreover, the rate of the case in which it doesn't perform the whole body bone scan showed up as the average 1:$0.067{\pm}0.6$ of Ventri, and 1:$0.063{\pm}0.7$ of Infinia. According to the phantom after experiment spatial resolution measurement result, and an addition or no and time-out of $^{99m}Tc$ administrated, it doesn't note any change of FWHM (p=0.134). Conclusion: Through the experiments using anthropomorphic torso phantom and patients data, we found that $^{201}Tl$ myocardium perfusion SPECT image later carried out after the bone tracer injection with 16 hours this confirmed that it doesn't receive notable influence in spatial resolution by $^{99m}Tc$. But this investigation is only aimed to image quality, so it needs more investigation in patient's radiation dose and exam accuracy and precision. The exact guideline presentation about the exam interval should be made of the validation test which is exact and in which it is standardized about the affect of the crosstalk contamination according to the isotope use in which it is different later on.

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A Study on the Practice Model for Practical Education for Health and Medical Information Management (보건의료정보관리 실습교육을 위한 실습모델 연구)

  • Choi, Joon-Young
    • Journal of the Health Care and Life Science
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    • v.8 no.2
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    • pp.83-93
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    • 2020
  • In this study, a practical model for health information management education using the EMR education system at universities for nurturing health care information managers was studied. Currently, there is no practical training course for health care information management in the standards for evaluation and certification of health care information management education introduced to strengthen the job competency of health care information managers. Accordingly, the program was constructed so that the practice program suggested as an educational environment in the Health and Medical Information Management Education Evaluation and Certification Manual can be practiced in the EMR education system. In addition, a practical model that can be performed according to the on-site practice guidelines for health and medical information management for each program was studied. Using the health care information management education EMR system, master data management, patient registration, doctor prescription, medical cost calculation, health insurance claim management, form management, discharge registration, cancer registration, unrecorded management, health care data management, health care statistics, A practice model was studied so that practice on information protection/security management can be performed. It will be possible to play a role as a health care information management expert by raising the quality level of health care information management education through systematic and standardized health care information management practice courses at universities. Accordingly, it is necessary to cultivate health care information management experts who develop and manage medical services based on medical data analysis through practical training of health care information managers.

Use of SNOMED CT to Represent Traditional Korean Medicine Concepts : A Semantic Characterization of Migraine-Related Concepts from Korean Medicine Clinical Practice Guideline (SNOMED CT를 활용한 한의약 개념 매핑 : 한의임상진료지침에서 도출된 편두통 관련 개념의 의미론적 표현)

  • Ahjung Byun;Hyeoun-Ae Park;Byung-Kwan Seo;EunYong Lee;Hyeoneui Kim
    • Journal of Society of Preventive Korean Medicine
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    • v.28 no.2
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    • pp.85-97
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    • 2024
  • 목적 : 본 연구는 한의약에서 사용하는 용어가 SNOMED CT로 매핑 가능한지 여부를 조사하고, 한의약 용어를 표현하기 위해 기존 SNOMED CT 온톨로지를 개선할 수 있는 방안을 제안하는 것을 목표로 하였다. 방법 : 선행 연구의 매핑 가이드라인에서 제시된 7단계 과정을 수정하여 활용하였다. 매핑의 목적 및 범위 정의, 용어 추출, 개념 추출, 매핑을 위한 소스 용어 작업, SNOMED CT 개념 검색, 매핑 관계 분류 및 매핑 검증의 과정을 수행하였다. 매핑의 목적은 한의약 임상 아이디어를 표현하는 표준 용어로서 SNOMED CT를 평가하는 것이고, 범위에는 편두통 환자 관리의 평가, 진단, 치료 및 예방을 포함하였다. 결과 : 총 546개의 용어가 추출되었다. 중복된 용어를 제거한 후, 271개의 개념이 SNOMED CT 매핑에 사용되었다. 이중 43.2%는 SNOMED CT 개념과 의미론적으로 동등하게 매핑되었고(117개 개념), 39.1%는 SNOMED CT 개념이 더 포괄적인 의미를 가지도록 매핑되었다(106개 개념). 상대적으로 포괄적인 의미를 가지는 SNOMED CT 개념에 매핑된 한의약 개념 106개 중 19개는 SNOMED CT 후조합을 이용하여 의미론적으로 동등하게 표현이 가능하였다. 나머지 17.7%의 한의약 개념은 SNOMED CT에 매핑할 수 없었다. 결론 : 본 연구는 한의약에서 사용되는 개념을 SNOMED CT에 매핑하여 한의약 용어를 표준화하였다. 연구 결과를 바탕으로, 한의약에서 사용되는 용어를 표준의료용어로 표현하기 위하여 SNOMED CT에 새로운 개념과 속성을 추가하는 것을 제안한다.

Building the Process for Reducing Whole Body Bone Scan Errors and its Effect (전신 뼈 스캔의 오류 감소를 위한 프로세스 구축과 적용 효과)

  • Kim, Dong Seok;Park, Jang Won;Choi, Jae Min;Shim, Dong Oh;Kim, Ho Seong;Lee, Yeong Hee
    • The Korean Journal of Nuclear Medicine Technology
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    • v.21 no.1
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    • pp.76-82
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    • 2017
  • Purpose Whole body bone scan is one of the most frequently performed in nuclear medicine. Basically, both the anterior and posterior views are acquired simultaneously. Occasionally, it is difficult to distinguish the lesion by only the anterior view and the posterior view. In this case, accurate location of the lesion through SPECT / CT or additional static scan images are important. Therefore, in this study, various improvement activities have been carried out in order to enhance the work capacity of technologists. In this study, we investigate the effect of technologist training and standardized work process processes on bone scan error reduction. Materials and Methods Several systems have been introduced in sequence for the application of new processes. The first is the implementation of education and testing with physicians, the second is the classification of patients who are expected to undergo further scanning, introducing a pre-filtration system that allows technologists to check in advance, and finally, The communication system called NMQA is applied. From January, 2014 to December, 2016, we examined the whole body bone scan patients who visited the Department of Nuclear Medicine, Asan Medical Center, Seoul, Korea Results We investigated errors based on the Bone Scan NMQA sent from January 2014 to December 2016. The number of tests in which NMQA was transmitted over the entire bone scan during the survey period was calculated as a percentage. The annual output is 141 cases in 2014, 88 cases in 2015, and 86 cases in 2016. The rate of NMQA has decreased to 0.88% in 2014, 0.53% in 2015 and 0.45% in 2016. Conclusion The incidence of NMQA has decreased since 2014 when the new process was applied. However, we believe that it will be necessary to accumulate data continuously in the future because of insufficient data until statistically confirming its usefulness. This study confirmed the necessity of standardized work and education to improve the quality of Bone Scan image, and it is thought that update is needed for continuous research and interest in the future.

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A Study on the Development Direction of Medical Image Information System Using Big Data and AI (빅데이터와 AI를 활용한 의료영상 정보 시스템 발전 방향에 대한 연구)

  • Yoo, Se Jong;Han, Seong Soo;Jeon, Mi-Hyang;Han, Man Seok
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.9
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    • pp.317-322
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    • 2022
  • The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.