• Journal of Korean Critical Care Nursing
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• v.4 no.1
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• pp.1-10
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• 2011

Purpose: The study was conducted to find out clinical characteristics for coronary artery disease patients with diabetes mellitus. Methods: We retrospectively reviewed the electronic medical records which included the data of 6,792 patients, who had been diagnosed coronary artery disease (CAD) such as angina or acute myocardial infarction and admitted to a university hospital in Seoul from January, 2005 to November, 2010. Results: Of the 6,792 patients, 43% had been diagnosed diabetes as comorbidity. The CAD patients with diabetes had lower left ventricular ejection fraction, stayed longer at hospital, and spent on more time from the first symptom to hospital visit than those without diabetes. In addition, they were more likely to have multi vessel coronary artery disease. Conclusion: The CAD patients with diabetes lay on the various factors which can make more worsen condition. Hence, we need to pay attention to specialized nursing care and patient education for the CAD patients with diabetes.

• Korean Journal of Clinical Pharmacy
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• v.30 no.3
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• pp.206-208
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• 2020

An 80-year-old Korean woman who previously experienced penicillin allergy presented to a dental hospital for treatment of a fractured tooth. A dentist extracted the tooth and prescribed her A-cillin (amoxicillin hydrate) 250 mg orally 3 times a day for 3 days and Carol-F^® (ibuprofen arginine) orally 3 times a day for 3 days. She received the prescriptions, returned home, and took one dose of each drug. One hour later, she experienced hypertension, itching, shortness of breath, and was unable to move her tongue to pronounce words. Approximately 6 hours after drug administration, the symptoms persisted, and the patient was admitted to an emergency medical center (EMC). The patient was discharged from the EMC after a one-night stay in the hospital for symptomatic treatment.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.25 no.2
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• pp.93-103
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• 2020

The telecare medical information system (TMIS) supports convenient and rapid health-care services. A secure and efficient authentication and key agreement scheme for TMIS provides safeguarding electronic patient records (EPRs) and helps health care workers and medical personnel to rapidly making correct clinical decisions. Giri et al. proposed an RSA-based remote user authentication scheme using smart cards for TMIS and claimed that their scheme could resist various malicious attacks. In this paper, we point out that their scheme is still vulnerable to lost smart card attacks and replay attacks and propose an improved scheme to prevent the shortcomings. As compared with the previous authentication schemes for TMIS, the proposed scheme is more secure and practical.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.116-132
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• 2022

Automated medical claims processing and billing is a popular application domain of information technology. Managing medical related data is a tedious job for healthcare professionals, which distracts them from their main job of healthcare. The technology used in data management has a sound impact on the quality of healthcare data. Most of Information Technology (IT) organizations use conventional software development technology for the implementation of healthcare systems. The objective of this experimental study is to devise a mechanism for use of rule-based expert systems in medical related edits and compare it with the conventional software development technology. A sample of 100 medical edits is selected as a dataset to be tested for implementation using both technologies. Besides empirical analysis, paired t-test is also used to validate the statistical significance of the difference between the two techniques. The conventional software development technology took 254.5 working hours, while rule-based technology took 81 hours to process these edits. Rule-based technology outperformed the conventional systems by increasing the confidence value to 95% and reliability measure to 0.462 (which is < 0.5) which is three times more efficient than conventional software development technology.

• The Journal of Korean Medicine
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• v.41 no.2
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• pp.107-121
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• 2020

Objectives: The purpose of this study was to identify the characteristics of patients who visited the emergency room (ER) of a Korean medicine (KM) hospital and to provide basic data for further research. Methods: We conducted a retrospective analysis using electronic medical records of 263 patients who visited the ER of OO University Oriental Hospital from January 1 to December 31, 2019. Results: Of the 263 patients' medical records, 245 were included in this analysis. The male-to-female ratio was 1.09:1. The average age was 52 years, with patients in their 40s having the largest distribution. The district where the hospital was located had the largest number of patients. The distribution by visit time was the lowest in the early morning. Most patients visited on Sunday, in September, and on the day of onset. The admission rate was 39.18%, and largest number of patients was admitted to the Department of Acupuncture and Moxibustion. The percentage of patients who revisited the KM hospital as an outpatient were 26.17%. The diagnosis for most patients was musculoskeletal disease. Acupuncture was the most common treatment, accounting for 62.45% of the cases, followed by herbal medicines, accounting for 54.69% of the cases. National health insurance was the most common type of insurance registered. Most patients visited the ER of the KM hospital via the ER of the hospital. Conclusions: This clinical analysis helped us identify the characteristics of patients visiting the ER of a KM hospital. Continuous data accumulation is required in relation to this for further studies.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.19-30
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• 2021

Diabetes Mellitus (DM) is one of common chronic diseases leading to severe health complications that may cause death. The disease influences individuals, community, and the government due to the continuous monitoring, lifelong commitment, and the cost of treatment. The World Health Organization (WHO) considers Saudi Arabia as one of the top 10 countries in diabetes prevalence across the world. Since most of the medical services are provided by the government, the cost of the treatment in terms of hospitals and clinical visits and lab tests represents a real burden due to the large scale of the disease. The ability to predict the diabetic status of a patient without the laboratory tests by performing screening based on some personal features can lessen the health and economic burden caused by diabetes alone. The goal of this paper is to investigate the prediction of diabetic and prediabetic patients by considering factors other than the laboratory tests, as required by physicians in general. With the data obtained from local hospitals, medical records were processed to obtain a dataset that classified patients into three classes: diabetic, prediabetic, and non-diabetic. After applying three machine learning algorithms, we established good performance for accuracy, precision, and recall of the models on the dataset. Further analysis was performed on the data to identify important non-laboratory variables related to the patients for diabetes classification. The importance of five variables (gender, physical activity level, hypertension, BMI, and age) from the person's basic health data were investigated to find their contribution to the state of a patient being diabetic, prediabetic or normal. Our analysis presented great agreement with the risk factors of diabetes and prediabetes stated by the American Diabetes Association (ADA) and other health institutions worldwide. We conclude that by performing class-specific analysis of the disease, important factors specific to Saudi population can be identified, whose management can result in controlling the disease. We also provide some recommendations learnt from this research.

• Korea Journal of Hospital Management
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• v.25 no.4
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• pp.13-28
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• 2020

Purposes: The purpose of this study is to analyze the institutional and personal factors that affect the medical utilization of patients transferred to tertiary medical institutions. Methodology: We retrospectively analyzed the 2 weeks electronic medical records of 1,556 patients, who were referred to the tertiary hospital, from June 15 to 26, 2015. The patient's personal characteristics, referral hospital, referral path, medical experiences and expenses were analyzed for 6 months after the patient's first visit. Findings: The largest proportion (848; 54.5%) of referrals was referred from primary clinic but the referrals of the same tertiary hospital level were one in seven (228; 14.7%) of the patients. Most patients (1,401; 90%) were referred from the clinics and hospitals directly and only one in ten (155; 10%) of the patients utilized the medical referral center. Patients who had been referred from tertiary care institutions had significantly higher medical costs than those referred to primary care (7,560,000 vs 2,333,000 won). The institutional factors including the numbers of visits to outpatient clinic, previous history of hospitalization and operation, consultation to other medical departments and hospitalization fee significantly influenced on medical utility pattern. Personal factors including patient's medical diagnosis and department of disease have a highly correlation with patient's referrals. Practical implications: The medical utilization of medical expenses and experiences is influenced by institutional and individual factors, and it is important to establish a referral system considering the institutional factors of the type of referral hospital.

• Korean Medical Education Review
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• v.26 no.1
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• pp.70-76
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• 2024

This study investigates whether personality characteristics and learning behaviors can predict medical students' academic achievement in Korea, specifically in terms of successfully completing medical school without delays or achieving a high grade point average (GPA) in their final year. In May 2018, 316 medical students took the Multi-Dimensional Learning Strategy Test, 2nd edition, which provided data on their personality and learning behavioral characteristics. Their final year's GPA and any delays in completing medical school were ascertained by reviewing all electronic academic records of each semester they had been enrolled. The combination of personality and learning behavioral characteristics was significantly associated with completing medical school without delays, even after adjusting for sex and admission path. A multiple logistic regression analysis showed that the adjusted odds ratios and 95% confidence intervals for completing medical school without delays were 1.52 (95% confidence interval [CI], 0.83-2.78) and 3.64 (95% CI, 1.70-7.82) for "others" and "both high" categories, respectively, when compared with the "both low" category. For 235 students who completed medical school without delays, their learning behavioral characteristics (scores) were significantly associated with their final year's GPA even after adjusting for sex, admission path, and personality characteristics (scores) as determined by the multiple linear regression analysis. This study suggests that individual personality and learning behavior characteristics are predictors of medical students' academic achievement. Therefore, interventions such as personalized counseling programs should be provided in consideration of such student characteristics.