• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.175-185
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• 2021

Purpose: Vital sign are used to help assess the general physical health of a person, give clues to possible diseases, and show progress toward recovery. Researchers are using vital sign data and AI(artificial intelligence) to manage a variety of diseases and predict mortality. In order to analyze vital sign data using AI, it is important to select and extract vital sign data suitable for research purposes. Methods: We developed a method to visualize vital sign and early warning scores by processing retrospective vital sign data collected from EMR(electronic medical records) and patient monitoring devices. The vital sign data used for development were obtained using the open EMR big data MIMIC-III and the wearable patient monitoring device(CareTaker). Data processing and visualization were developed using Python. We used the development results with machine learning to process the prediction of mortality in ICU patients. Results: We calculated NEWS(National Early Warning Score) to understand the patient's condition. Vital sign data with different measurement times and frequencies were sampled at equal time intervals, and missing data were interpolated to reconstruct data. The normal and abnormal states of vital sign were visualized as color-coded graphs. Mortality prediction result with processed data and machine learning was AUC of 0.892. Conclusion: This visualization method will help researchers to easily understand a patient's vital sign status over time and extract the necessary data.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.107-114
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• 2020

This paper studies a method for estimating the scale of a Hadoop cluster to process big data as a cost-effective manner. In the case of medical institutions, demands for cloud-based big data analysis are increasing as medical records can be stored outside the hospital. This paper first analyze the Amazon EMR framework, which is one of the popular cloud-based big data framework. Then, this paper presents a efficiency model for scaling the Hadoop cluster to execute a Mapreduce application more cost-effectively. This paper also analyzes the factors that influence the execution of the Mapreduce application by performing several experiments under various conditions. The cost efficiency of the analysis of the big data can be increased by setting the scale of cluster with the most efficient processing time compared to the operational cost.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.609-612
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• 2014

With the development of recent IT is spreading and dissemination of smart terminals, telemedicine and electronic medical records (EMR) and other common anywhere due to medical advances are being digitized environment. This trend is in line with the information to take advantage of smart terminals in the mobile medical information system increasing. In this paper, the recent trend to examine healthcare information technology standardization, predicting the future prospects look healthcare information systems. In addition, the security of mobile medical information system, to look at aspects of mobile-based health information systems in the country's need to discuss the trends and standards.

• Journal of Information Technology Services
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• v.11 no.2
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• pp.197-211
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• 2012

This paper describes how to derive audit criterion, audit domain, detail technology, and functional check items which are core of hospital information system, consisting of OCS, EMR, and PACS. Using the check items listed above, we investigated the objective validity for the construction audit of hospital information system. As a result, the derived audit criterion, audit domain, detail technology, and functional check items were verified as check items for audit. Since using the current audit check items of public area is insufficient to construct efficient, reliable, and stable hospital information system, we suggest adopting the hospital information system audit area, audit check items, and process that are presented in this paper.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.27 no.1
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• pp.117-129
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• 2014

Objective : To study current status on characteristics of allergic rhinitis patients by using the electronic medical record (EMR) data and to explore the feasibility of clinical studies using the EMR data in three different Korean medical hospitals. Methods : We studied allergic rhinitis patients who visited the department of ophthalmology, otolaryngology and dermatology in the three different Korean hospitals from January 1, 2012 to December 31, 2012. We retrospectively collected medical history and characteristics of study subjects using data of EMR. Results : In hospital A, we were able to collect data of 18 years of age or older. In hospital C, we could only collect data after July 1, 2012. Therefore, each hospital's data had different settings in measuring them. Men and women were accounted for similar percentage, and teens were the highest in the age group. J30.4, unspecified allergic rhinitis, was the highest in diagnosis of the allergic rhinitis. Most of the patients have received acupuncture treatments. Moreover, 74.6 percent of the total patients were prescribed with Chinese medicine. Conclusions : Based on this exploratory study, further studies were needed on clinical studies using data of systematic EMR.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.114-115
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• 2018

This paper studies a mechanism for cost-effective analysis of big data in the cloud environment. Recently, as a storage of electronic medical records can be managed outside the hospital, there is a growing demand for cloud-based big data analysis in small-and-medium hospitals. This paper firstly analyze the Amazon Elastic MapReduce which is a popular cloud framework for big data analysis, and proposes a cost model for analyzing big data using Amazon EMR with less cost. Using the proposed model, the user can construct a cost-effective computing cluster, which maximize the effectiveness of the analysis per operational cost.

• Korean Journal of Digital Imaging in Medicine
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• v.10 no.2
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• pp.33-37
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• 2008

To keep the online medical records available to anyone without constraint of time and space, introducing EMR (Electronic medical record), which is a clinical support management system. The purpose of this study is to develop interface standard of clinical test device. Integration and sharing of medical information is faced with enormous obstacles because medical organizations and associated companies are separately developing the interface. I hope that multi-function management system with workstation concept is operated to efficiently transmit clinical device result data based on this study. Transfer of precise medical result data available for decision making will improve quality of health care service.

• Journal of Digital Forensics
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• v.12 no.3
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• pp.83-96
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• 2018

Electronic medical records in the hospital information system are the important evidence related to the crime and are subject to search and seizure. In the case of a large general hospital, it is possible to search for seizures through cooperation of the staff, but it is impossible in small hospitals. The investigation agency copies the database of electronic medical records and then selects relevant content. This approach has an issue of excessive search and seizure. In this paper, we propose field selection procedures and methods for electronic medical records while ensuring integrity, reproducibility, and chain of custody. Currently, it is necessary to study the procedures and methods of search and seizure of medical information system so that it can respond to next changing cloud hospital information system.

• Journal of Digital Convergence
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• v.10 no.4
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• pp.279-286
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• 2012

The purpose of this study was identified the influence of introducing Electronic Medical Records (EMR) on reception attitude, based on literature investigation, the study converted utility and serviceability from Davis TAM Model into awareness of effects in computerized database except attitude variable. The electronic survey for doctors, nurses, medical technicians of a general hospital located in Gangwon-do was performed for 4 weeks from Nov, 11th, 2009 to Dec, 2nd and the collected data was computerized through SPSS 12.0. The factors influencing reception attitude were divided into 4 categories; basic characteristics of the individual, awareness of privacy protection, awareness of effects in computerized database, technological preparation and measured detailed specific variables. As the result of this, the factors influencing reception intention were different depending on recognizing the effectiveness caused by computerization of medical information. Especially, in terms of the difference between basic characteristics of the individual and awareness of privacy protection, there were significant distinctions among 3 sectors; general, transactional, online information management. The significant effects were identified from information management related to business or online information management depending on experiencing security education.

• Quality Improvement in Health Care
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• v.14 no.2
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• pp.125-132
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• 2008

Background : The number of outpatient injected anticancer drug is increasing. and the pathway of prescribing, compounding, and injecting anticancer drug is processed very rapidly in out-patient department. Moreover, Dose of anticancer drug is often changed depending on side effect of patients. So we need more effective inspection of anticancer drug prescriptions. The purpose of this study was to analyze the prescription errors for anticancer drugs in Out-Patient Department and to suggest system to prevent them. Method : The study took place at Asan Medical Center from July to September 2007. The pharmacists performed inspection of anticancer drug prescriptions before compounding and injecting. We used protocol-based anticancer drug order program and Electronic Medical Record (EMR). Result : During the study period, we analyzed 4683 prescriptions for out-patient. And we detected 55 medication errors (1.2%). Most common errors included dosage above or below the correct ones (56.3%), followed by incorrect treatment duration. Because most of dosing errors were in the range of usual dosage, it was hard to detect them. So when inspecting the prescription, we considered the medical records of individual patients. As a result, we could raise the efficiency of intervention. Therefore inspection using EMR could possibly reduce the number of anticancer drug errors. Conclusion : we are preventing the medication errors on stability and dosage above or below the maximum therapeutic dose according to the previous inspection system. However most of dosing errors were in the range of usual dosage according to the result of this study. Because of there was interpatient variability of dosage depending adverse effect. For improvement of quality assurance, we suggest inspection system based on patient's medical history.