• Proceedings of the KAIS Fall Conference
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• 2003.06a
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• pp.219-221
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• 2003

This system is Emergency patient medical examination and treatment way through biosignal transmission to use PDA. Store measured biosignal that is stored to file to database by Application, This system helps doctor's treatment that transmit patient's biosignal data and patient's symptoms use wireless internet. ThenOffer more than safer medical treatment environment to a doctor and patient

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.57-59
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• 1994

In this paper, we present the software part of the intelligent data processing unit (IDPU), which plays an important role in SiMACS. The software system processes ECG, EEG, EMG, blood pressure, respiration, temperature signals, and extracts some information about patient conditions. It displays the patient condition information and the signal data synchronously, and manages them together with other patient personal data in a network-based client/server environment. The software system is designed in an object-oriented paradigm, and implemented in C++ as a window-based application program.

• Korea Journal of Hospital Management
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• v.7 no.4
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• pp.57-101
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• 2002

These days, the environment of hospital marketing is changing rapidly. The level of expectation and demand of patients have become greater and more diversified, and patients have more alternatives in selecting hospitals. The standard of hospital selection and the type of using hospital have been changed, and competition among hospitals has been accelerated due to the opening of the medical market through globalization. Accordingly, differentiation strategies are critical in hospital marketing. The quality of medical service oriented toward patient satisfaction becomes a strong strategic weapon to secure a hospital's competitive advantage. Therefore, marketing and communication strategies should be focused on patient-oriented, rather than hospital-oriented. Considering the changes in the hospital environment and the increase in the patients' expectation level, this study categorizes doctors' communication styles into four different ones: trust-type, professional-type, cooperation-type, and control-type. The effects of these communication styles on patient satisfaction were empirically examined. The moderating roles of the patient's characteristics and clinical characteristics between the doctors' communication styles and patient satisfaction were also investigated to find out managerial implications for hospital management. To achieve such goals, data were collected from patients of 12 general hospitals in Busan. The data were analyzed to test research hypotheses that examine 1) the relationships between doctors' communication styles and patient satisfaction, 2) the moderating roles of the patient characteristics and clinical characteristics in the research model, and 3) the impact of patient satisfaction on positive word-of-mouth and repurchase. The following summarizes the major results of this research. First, the data showed that patient satisfaction varied across doctors' communication styles. Trust-type style had the strongest impact on patient satisfaction while control-type style had the weakest influence on patient satisfaction. Professional-type style and cooperation-type style also had positive effects on patient satisfaction but the impact of the two are not statistically different. Second, significant differences in terms of patient satisfaction were found depending upon demographic variables such as gender, marital status, age, occupation, and education. Patient satisfaction, however, was consistent across varying income groups. Third, patients' medical insurance types were also related to patient satisfaction. It implies that a doctor may need to use different communication styles depending on a patient's medical insurance type. Fourth, out-patient and in-patient showed a different level of satisfaction with varying communication styles. Fifth, highly professional knowledge and strong control can influence patient satisfaction depending on the characteristics of the patient treatment field. Sixth, patient satisfaction were proved to have significantly positive effects on word-of-mouth and repurchase. The implications drawn from this study must be tempered by its limitations. First of all, the subjects used in this study were patients in Busan and small- and medium-size hospitals were excluded from the research. Therefore, future research should examine the research model by using a variety of hospitals and clinics throughout Korea. Another research agenda has to do with finding more determinant and moderating variables which will increase an explanatory power of the model. In short, this study may be the first empirical research that investigates the effects of doctors' communication styles on patient satisfaction. Interestingly enough, the results showed that each communication style had a unique impact on patient satisfaction. The findings from this research can be very useful in developing hospital marketing strategies.

• Journal of Korean Academy of Nursing Administration
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• v.20 no.1
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• pp.35-47
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• 2014

Purpose: The purpose of this study was to describe nurses' experiences of accidents in patient safety. Methods: Data were collected from October 8, 2011 to January 31, 2012 through in-depth interviews with seven nurses who had worked on wards or in the ICU in a university hospital. Data were analyzed by applying Colaizzi's phenomenological methodology. Results: The following six categories were extracted: Fear of the patient's condition caused by the accident, Conflict in the accident report, Blame on others and circumstances, Feeling guilty and sorry as the patient's condition is improving, Being disappointed with the unfavorable atmosphere in dealing with the accident, After the accident, being sensitive in performing nursing duties and being faithful to the principles. Conclusion: The results indicate that the organizational culture in the hospital related to accidents in patient safety is still closed and punitive, and such an atmosphere causes nurses to feel seriously hurt, but through this experience nurses are likely to mature as nursing professionals. Programs on prevention of accidents in patient safety and a system to guard against these accidents should be established. Also the organizational safety culture should be improved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.967-979
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• 2013

Now a day, Wireless Sensor Networks (WSNs) are being widely used in different areas one of which is healthcare services. A wireless medical sensor network senses patient's vital physiological signs through medical sensor-nodes deployed on patient's body area; and transmits these signals to devices of registered medical professionals. These sensor-nodes have low computational power and limited storage capacity. Moreover, the wireless nature of technology attracts malicious minds. Thus, proper user authentication is a prime concern before granting access to patient's sensitive and private data. Recently, P. Kumar et al. claimed to propose a strong authentication protocol for healthcare using Wireless Medical Sensor Networks (WMSN). However, we find that P. Kumar et al.'s scheme is flawed with a number of security pitfalls. Information stored inside smart card, if extracted, is enough to deceive a valid user. Adversary can not only access patient's physiological data on behalf of a valid user without knowing actual password, can also send fake/irrelevant information about patient by playing role of medical sensor-node. Besides, adversary can guess a user's password and is able to compute the session key shared between user and medical sensor-nodes. Thus, the scheme looses message confidentiality. Additionally, the scheme fails to resist insider attack and lacks user anonymity.

• 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 Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.9
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• pp.1680-1687
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• 2007

A hospital room has multiple patient monitoring devices at the bedside to monitor his or her status. However, vital sign monitors, ventilator and other bedside devices are made by a variety of different manufacturers and often cannot easily interface to the hospital information system. Medical environments incorporate complex and integrated data networks to transfer vast amounts of patient information, such as images, waveforms, and other forms of digital data. Hence, to assure interoperability of images, waveforms and patient data, Health Level Seven (HL7) was developed as an international standard to facilitate the communicating and storing of medical data. In this study, we developed middleware capable of receiving data from mCare 300 vital signs monitoring devices and converting the data to HL7 data format. The HL 7 middleware streamline clinical workflow and support patients. Therefore, clinical expertise are empowered to respond to dynamic healthcare situation as soon as they emerged, and consequently quality of care while helping to reduce the length of a patient's stay in a hospital.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1049-1065
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• 2023

Recently, with the development of IoT, AI, and mobile terminals, medical information platforms are expanding. The medical information platform can determine a patient's emergency situation, and medical staff can easily access patient information through a mobile terminal. However, in the existing platform, emergency situation decision is delayed, and faster and stronger authentication is required in emergency situations. Therefore, we propose an edge computing-based medical information platform for automatic authentication using patient situations. We design an edge computing-based medical information platform architecture capable of rapid transmission of biometric data of IoT and quick emergency situation decision, and implement the platform data flow in emergency situations. Relying on this platform, we propose the automatic authentication using patient situations. The automatic authentication protects patient information through patient-centered authentication by using the patient's situation as an authentication factor, and enables quick authentication by automatically proceeding with mobile terminal authentication after user authentication in emergencies without user intervention. We compared the proposed platform with existing platforms to show that it can make quick and stable emergency decisions. In addition, comparing the automatic authentication with existing authentication showed that it is fast and protects medical information centered on patient situations in emergency situations.

• Journal of Korean Academy of Nursing Administration
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• v.19 no.2
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• pp.315-327
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• 2013

Purpose: The purpose of this study was to investigate the patient safety culture in Korean nursing homes using the Nursing Home Survey Patient Safety Culture (NHS-PC), a valid tool, provided by the Agency for Healthcare Research and Quality (AHRQ) and to compare the results with AHRQ data. Methods: Administrators and staff (N=151) of six nursing homes in Seoul, Busan, Kyeonggi Province and Gyeongsangnam Province completed the survey in July, 2010. The data were analyzed using descriptive statistics, positive response rate, t-test, ANOVA, DUNCAN, Cronbach's ${\alpha}$. Results: The total mean (SD) positive response rate for patient safety culture was not significantly different from the AHRQ data. For composite levels, the results of 'handoffs' were significantly higher, and the results of 'feedback and communication about incidents' and 'nonpunitive responses to mistakes' were significantly lower than the AHRQ data. Conclusion: More effective strategies related to nonpunitive responses to mistakes and management activities for patient safety are needed to improve patient safety culture in nursing homes.

• Genomics & Informatics
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• v.12 no.1
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• pp.21-34
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• 2014

A visual analysis approach and the developed supporting technology provide a comprehensive solution for analyzing large and complex integrated genomic and biomedical data. This paper presents a methodology that is implemented as an interactive visual analysis technology for extracting knowledge from complex genetic and clinical data and then visualizing it in a meaningful and interpretable way. By synergizing the domain knowledge into development and analysis processes, we have developed a comprehensive tool that supports a seamless patient-to-patient analysis, from an overview of the patient population in the similarity space to the detailed views of genes. The system consists of multiple components enabling the complete analysis process, including data mining, interactive visualization, analytical views, and gene comparison. We demonstrate our approach with medical scientists on a case study of childhood cancer patients on how they use the tool to confirm existing hypotheses and to discover new scientific insights.