• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.102-108
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• 2005

This paper studies medical data classification methods, comparing decision tree and system reconstruction analysis as applied to heart disease medical data mining. The data we study is collected from patients with coronary heart disease. It has 1,723 records of 71 attributes each. We use the system-reconstruction method to weight it. We use decision tree algorithms, such as induction of decision trees (ID3), classification and regression tree (C4.5), classification and regression tree (CART), Chi-square automatic interaction detector (CHAID), and exhausted CHAID. We use the results to compare the correction rate, leaf number, and tree depth of different decision-tree algorithms. According to the experiments, we know that weighted data can improve the correction rate of coronary heart disease data but has little effect on the tree depth and leaf number.

• Journal of Preventive Medicine and Public Health
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• v.55 no.6
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• pp.539-548
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• 2022

Objectives: The purpose of this study was to assess the organizational effectiveness of the introduction of a healthcare information system (electronic medical records and databases) in healthcare in Kazakhstan. Methods: The authors used a combination of 2 methods: expert assessment and strengths, weaknesses, opportunities, and threats (SWOT) analysis. SWOT analysis is a necessary element of research, constituting a mandatory preliminary stage both when drawing up strategic plans and for taking corrective measures in the future. The expert survey was conducted using 2 questionnaires. Results: The study involved 40 experts drawn from specialists in primary healthcare in Aktobe: 15 representatives of administrative and managerial personnel (chief doctors and their deputies, heads of medical statistics offices, organizational and methodological offices, and internal audit services) and 25 general practitioners. Conclusions: The following functional indicators of the medical and organizational effectiveness of the introduction of information systems in polyclinics were highlighted: first, improvement of administrative control, followed in descending order by registration and movement of medical documentation, statistical reporting and process results, and the cost of employees' working time. There has been no reduction in financial costs, namely in terms of the costs of copying, delivery of information in paper form, technical equipment, and paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.699-700
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• 2014

The use of Radio Frequency Identification technology (RFID) in medical context enables not only drug identification, but also a rapid and precise identification of patients, physicians, nurses or any other healthcare giver. The combination of RFID tag identification with structured and secured Internet of Things (IoT) solutions enables ubiquitous and easy access to medical related records, while providing control and security to all interactions. This paper defines a basic security architecture, easily deployable on mobile platforms, which would allow to establish and manage a medication prescription service in mobility context making use of electronic Personal Health Records. This security architecture is aimed to be used with a mobile e-health application (m-health) through a simple and intuitive interface, supported by RFID technology. This architecture, able to support secured and authenticated interactions, will enable an easy deployment of m-health applications. The special case of drug administration and ubiquitous medication control system, along with the corresponding Internet of Things context, is presented.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.2
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• pp.32-50
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• 2009

Since 1990 when order communication system(OCS) was first introduced, the use of information technology in medical service has been widely accepted in order to enhance quality and customer relationship as well as to increase managerial efficiency. Medical information system is rapidly increasing and is trying to make ubiquitous healthcare environment through telemedicine system. Especially, medical profession and government have taken interest in electronic medical record (EMR) system which can digitalize and manage all medical records in hospitals. By recording patient's medical information in real time, EMR system can improve service efficiency and customer service quality including short waiting time, various utilization of clinic information, and reduced cost.

• Journal of Korean Library and Information Science Society
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• v.47 no.1
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• pp.149-173
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• 2016

As cloud computing becomes more and more popular and ubiquitous, many organizations are deciding to move their whole information infrastructure to the cloud. The healthcare industry is one of those that is beginning to utilize cloud-based solutions en masse. Cloud based computing and storage offers numerous benefits including scalability, cost efficiency, and accessibility, which in turn have the potential to streamline hospital operations. Despite the potential benefits of acquiring this system, considerations must still be given to the migration of the massive amounts of personal and highly protected data to a cloud-based solution. Health care organizations must consider all matters of security, reliability, and availability, to ensure that patients' data remains compliant to the Health Insurance Portability and Accountability Act (HIPAA) compliant. This paper will examine the benefits and challenges of such operation to determine the best practices for the utilization of Electronic Medical Record (EMR) cloud based networking and storage for small to mid-sized hospitals.

• 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.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.153-160
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• 2024

Information technology plays an important role in healthcare. The cloud has several applications in the fields of education, social media and medicine. But the advantage of the cloud for medical reasons is very appropriate, especially given the large volume of data generated by healthcare organizations. As in increasingly health organizations adopting towards electronic health records in the cloud which can be accessed around the world for various health issues regarding references, healthcare educational research and etc. Cloud computing has many advantages, such as "flexibility, cost and energy savings, resource sharing and rapid deployment". However, despite the significant benefits of using the cloud computing for health IT, data security, privacy, reliability, integration and portability are some of the main challenges and obstacles for its implementation. Health data are highly confidential records that should not be made available to unauthorized persons to protect the security of patient information. In this paper, we discuss the privacy and security requirement of EHS as well as privacy and security issues of EHS and also focus on a comprehensive review of the current and existing literature on Electronic health that uses a variety of approaches and procedures to handle security and privacy issues. The strengths and weaknesses of some of these methods were mentioned. The significance of security issues in the cloud computing environment is a challenge.

• The Journal of Industrial Distribution & Business
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• v.9 no.9
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• pp.35-44
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• 2018

Purpose - In endless competition, companies pursue cost reduction and work efficiency. So, entrepreneurs try to increase job intensity, which may lead to job stress and high turnovers because of job burnout. But, Information systems are acknowledged as a work support tool that secures work convenience and the productivity of employees. In this study, we aimed to confirm the effects of information systems in reduing the work overload of employees in a human resource intensive industry. Research design, data and methodology - This is based on the job demands-resources model, conducting an empirical analysis of surveys given to hospital employees working in a human resource intensive industry. Results - The research revealed that information systems reduced the work overload of employees in a human resource intensive industry. Conclusion - This study confirmed the effects of information systems as a job resource based on JD-R theory, and presentation of empirical results indicated that information systems alleviate employee job overload and increases job satisfaction in the medical services industry. In the medical services industry, using electronic health record system decreases in work overload, which results in employees gaining time for self-development and time management, reducing job stress, and leading to job satisfaction.

• Korean Journal of Clinical Pharmacy
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• v.29 no.1
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• pp.25-32
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• 2019

Objective: South Korea made a list of potentially inappropriate medications (PIMs) for elderly patients in 2015 and has prompted medical professionals to prescribe proper medication by using the drug utilization review (DUR) system. It has been three years since the system was introduced, but related studies have rarely been conducted. This study aimed to evaluate the effect of the DUR system on the prescription of PIMs for elderly patients. Methods: The data on the prescription of PIMs for elderly patients (${\geq}65$ years) who received medical treatment between March 1st and May 31st in 2015 (before introduction of the DUR system) and who received medical treatment between March 1st and May 31st in 2018 (after introduction of the DUR system) were retrospectively collected from electronic medical records. Results: The prescriptions of PIMs decreased from 3,716 (7.7%) to 3,857 (6.9%) (p < 0.001). The prescription of escitalopram and paroxetine, among selective serotonin reuptake inhibitors, increased significantly, and that of short-acting benzodiazepines also increased significantly from 454 (0.93%) to 624 (1.2%). Conclusion: Prescription of PIMs for elderly patients significantly decreased (p < 0.001) after the DUR system was introduced. Further expanded studies of PIMs need to be conducted for the safety of elderly patients.

• Journal of Korean Clinical Nursing Research
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• v.21 no.3
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• pp.377-388
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• 2015

Purpose: To identify user requirements for electronic nursing record (ENR) systems so as to ensure system usability. Methods: A mixed methods approach were applied in three steps : (i) task and workflow analysis with literature review of nursing documentation, (ii) literature reviews of system usability, and (iii) Use Case idenfication and consensus-based validation. We analyzed the nursing activity logs collected from a time-motion investigation of six hospitals. The Use Cases were validated by eight clinical experts from different hospitals and two experts from academia in a sequential Delphi survey. Consensus was achieved for the significance score and agreement among the panel. Results: Eight task groups and patterns of task flow were observed, which were translated into nine Use Cases. The specification of Use Cases was derived from principles, guidelines, and recommendations on nursing documentation and electronic health record systems, which was organized into three requirements of each Use Case: functionality, information, and design characteristics. Each Use Case achieved an agreement of 50~70%, and significance scores of 4 or 5 on a 5-point Likert scale. Conclusion: The nine Use Case identified were considered to be important and adequate in terms of both clinical and informatics contexts.