The Korean government ranked 3rd among 193 UN member countries in the UN's 2022 e-Government Development Index. Korea, which has consistently been evaluated as a top country, can clearly be said to be a leading country in the world of e-government. The lubricant of e-government is data. Data itself is neither information nor a record, but it is a source of information and records and a resource of knowledge. Since administrative actions through electronic systems have become widespread, the production and technology of data-based records have naturally expanded and evolved. Technology may seem value-neutral, but in fact, technology itself reflects a specific worldview. The digital order of new technologies, armed with hyper-connectivity and super-intelligence, not only has a profound influence on traditional power structures, but also has an a similar influence on existing information and knowledge transmission media. Moreover, new technologies and media, including data-based generative artificial intelligence, are by far the hot topic. It can be seen that the all-round growth and spread of digital technology has led to the augmentation of human capabilities and the outsourcing of thinking. This also involves a variety of problems, ranging from deep fakes and other fake images, auto profiling, AI lies hallucination that creates them as if they were real, and copyright infringement of machine learning data. Moreover, radical connectivity capabilities enable the instantaneous sharing of vast amounts of data and rely on the technological unconscious to generate actions without awareness. Another irony of the digital world and online network, which is based on immaterial distribution and logical existence, is that access and contact can only be made through physical tools. Digital information is a logical object, but digital resources cannot be read or utilized without some type of device to relay it. In that respect, machines in today's technological society have gone beyond the level of simple assistance, and there are points at which it is difficult to say that the entry of machines into human society is a natural change pattern due to advanced technological development. This is because perspectives on machines will change over time. Important is the social and cultural implications of changes in the way records are produced as a result of communication and actions through machines. Even in the archive field, what problems will a data-based archive society face due to technological changes toward a hyper-intelligence and hyper-connected society, and who will prove the continuous activity of records and data and what will be the main drivers of media change? It is time to research whether this will happen. This study began with the need to recognize that archives are not only records that are the result of actions, but also data as strategic assets. Through this, author considered how to expand traditional boundaries and achieves reterritorialization in a data-driven society.
Purpose: This research seeks to identify differences between general characteristics, disease-related characteristics, glycated hemoglobin (HbAlc) levels, and aspects of chronic complications of diabetes mellitus in type 2 diabetes. Methods: This research was conducted from the 1st to the 15th of February in 2016, on 263 in patients. Patients' electronic medical records were used to identify their general characteristics, disease-related characteristics, HbAlc, and chronic diabetic complications. Chi-square test, ANOVA, ANCOVA, and the Cochran-Mantel-Haenszel test were used for data analysis. Results: Statistical significance was observed for general characteristics, based on smoking status, such as age, and education level; disease-related characteristics differed according to the duration of diabetes. Smoking status did not differ according to HbAlc level. In term of chronic diabetic complications, statistically significance was observed for diabetic nephropathy, based on smoking status. Conclusion: Patients who had a history of smoking, but were not currently smoking, were likely to display higher HbAlc levels and diabetic nephropathy. Therefore, there is need for regular checkups for diabetic complications among patients with a history of smoking and it is important to emphasize smoking cessation.
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.
Purpose: The purpose of the study was to validate fall risk assessment scales among hospitalized adult patients in South Korea using the electronic medical records by comparing sensitivity, specificity, positive predictive values, and negative predictive values of Morse Fall Scale (MFS), Bobath Memorial Hospital Fall Risk Assessment Scale (BMFRAS), and Johns Hopkins Hospital Fall Risk Assessment tool (JHFRAT). Methods: A total of 120 patients who experienced fall episodes during their hospitalization from June 2010 to December 2013 was categorized into the fall group. Another 120 patients, who didn't experience fall episodes with age, sex, clinical departments, and the type of wards matched with the fall group, were categorized to the comparison group. Data were analyzed for the comparisons of sensitivity, specificity, positive and negative predictive values, and the area under the curve of the three tools. Results: MFS at a cut-off score of 48 had .806 for ROC curves, 76.7% for sensitivity, 77.5% for specificity, 77.3% for positive predictive value, and 76.9% for negative predictive value, which were the highest values among the three fall assessment scales. Conclusion: The MFS with the highest score and the highest discrimination was evaluated to be suitable and reasonable for predicting falls of inpatients in med-surg units of university hospitals.
Purpose: This study was done to examine the incidence of oral mucositis in hematopoietic stem cell transplantation patients and to identify factors influencing oral mucositis and patient outcomes according to severity. Methods: In this retrospective study, data were collected from electronic medical records of 222 patients who had received hematopoietic stem cell transplantation. Oral mucositis was evaluated using WHO's assessment scale. Data were analyzed using Chi-square test, Fisher exact test, Spearman's correlation, Ordinal logistic regression, ANOVA and Kruskal-Wallis test. Results: A total of 69.8% of the patients evaluated developed oral mucositis (grade II and over). As a results of ordinal regression, factors influencing oral mucositis severity were found to be diagnosis, type of transplantation, oxygen inhalation and the number of antiemetics administration before transplantation. The severity of oral mucositis was found to increase the days of hospitalization, days of TPN administration, days of using antibiotics and the number and dosage of analgesics. Conclusion: The results would help predict severity of oral mucositis in hematopoietic stem cell transplantation patients and suggest that provision of appropriate nursing assessment and oral care would improve patient outcomes.
Purpose: To provide accurate information on induced labor and find strategies to enhance women's childbirth satisfaction. Methods: Participants were pregnant women expected to have normal vaginal delivery. A total of 113 women with induced labor and 61 women with spontaneous labor were surveyed. Data were collected using a questionnaire and electronic medical records. Results: The following variables related to labor progress showed significant differences between the induced labor group and the spontaneous labor group: length of the first stage of labor in primigravidas, use of analgesic, incidence of uterine hyperstimulation, incidence of fetal distress, and medical treatment for the expectant mother. Delivery type and the incidence of postpartum complications showed significant difference between the two groups. Induced labor women's childbirth satisfaction was mainly affected by the process of labor whereas spontaneous labor women's childbirth satisfaction was affected by the outcome of childbirth. Conclusion: Medical staff should have accurate information on the risk of induced labor and the benefits of a natural delivery. Moreover, medical staff should provide necessary information and environment for women to participate in the decision-making process.
Kim, Chungsoo;Lee, Jimin;Park, Rae Woong;Lee, Sukhyang
Korean Journal of Clinical Pharmacy
/
v.29
no.4
/
pp.254-266
/
2019
Background: Patients with cardiovascular risks are recommended to use statins and antiplatelet agents to prevent major cerebro-cardiovascular events (MACCE). Antiplatelet agents also possess anti-inflammatory and antioxidant effects, in addition to their inhibitory activity on platelets. The differences in clinical outcomes in ischemic heart disease (IHD) based on the type of antiplatelet therapy combined with statin treatment were investigated in this study. Methods: We conducted a retrospective cohort study using electronic medical records of IHD patients from January 2010 to December 2014 at Ajou University Hospital. Patients on combination therapy of antiplatelet drugs and statins were grouped based on antiplatelet drug types: clopidogrel, cilostazol, or sarpogrelate. Propensity score matching was applied to balance the baseline of the groups of clopidogrel vs. cilostazol and the groups of clopidogrel vs. sarpogrelate. The incidence and risk of MACCE as primary outcomes were assessed between the groups of antiplatelet drugs. Results: Among the approximately 128,500 patients with IHD, 1,049 patients had taken a combination therapy of statin and antiplatelet agents. The cohorts of patients administered clopidogrel, cilostazol, or sarpogrelate were 906, 79, and 64, respectively. The incidence of MACCE was not significantly different among the cohorts (p=0.58), and there were no differences between clopidogrel vs. cilostazol (p=0.72) or clopidogrel vs. sarpogrelate (p=1.00) after propensity score matching. Conclusion: There was no difference in the incidence of MACCE based on the type of antiplatelet drug (clopidogrel, cilostazol, or sarpogrelate) in combination with a statin in patients with IHD.
Purpose: The purpose of this study was to analyze the content of nursing interventions applied to patients with thoracic injury who visited a trauma emergency room (TER) or an emergency room (ER). Methods: Of 3,938 trauma patients admitted to this hospital between January 1, 2019 and December 31, 2020, 320 adult patients with thoracic injury (94 to TER, 226 to ER) who met the inclusion criteria were enrolled. Patients' data were acquired from their electronic medical records. General and clinical characteristics of these subjects along with nursing interventions were analyzed. Results: There were statistically significant differences in the length of stay, treatment outcome, and level of consciousness between thoracic injury patients who visited TER and ER. Average thoracic Abbreviated Injury Scale score and average Injury Severity Score of thoracic injury patients who visited TER were 3.13 and 13.54, respectively, which were significantly higher than those of patients who visited ER. The numbers of nursing actions applied was 4,819 for TER and 3,944 for ER, which were classified into five domains, 18 classes, and 56 interventions. The most domain of interventions carried out in both TER and ER was physiological: complex. Classes including Crisis management and Thermoregulation were not carried out in ER. On average, 16 more types of interventions were carried out in TER than in ER. Conclusion: This study demonstrated characteristics of thoracic injury patients and nursing interventions by emergency room type. Based on results of this study, standardized nursing interventions need be applied to thoracic injury patients visiting TER and ER.
Kim, H.S.;Kim, B.W.;Kim, H.C.;Lee, K.W.;Ha, J.K.;Jeon, J.T.;Lee, J.G.
Journal of Animal Science and Technology
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v.45
no.6
/
pp.917-922
/
2003
This study was conducted to investigate effects of farm, type of sow Landrace${\times}$Yorkshire, LY; Yorkshire${\times}$ Landrace, YL; Yorkshire${\times}$Yorkshire, YY and multi-cross bred sow, MBS), parity, farrowing year, farrowing season and mating method on reproductive traits such as total number born per litter, number of born alive per litter, number of weaned per litter, number of mummified per litter, number of stillbirth. The Reproductive Records of 3,387 litters from January, 1999 to September, 2002 were obtained from four pig farms managed by Electronic Data Processing(EDP) system. Reproductive performances for two types of F1 Sows(YL and LY) were estimated as 11.34${\pm}$0.266 and 11.57${\pm}$0.263 heads for total number of born per litter, 10.56${\pm}$0.216 and 11.81${\pm}$0.251 heads for number of born alive per litter, and 10.05${\pm}$0.131 and 9.96${\pm}$0.153 heads for number of weaned per litter, respectively. These records are significantly higher(P〈0.05) than those of YY and MBS. However, number of mummified per litter, number of stillborn per litter, number of dead by diarrhea per litter, number of dead by other reasons during lactating period per litter and estrus interval did not show significant difference between types of sows. There were more total number of born per litter and number of weaned per litter in year 2001 than other year. As year passed, number of dead by crush per litter, number of dead by diarrhea per litter and number of dead by other reasons during lactating period per litter reduced from 0.18${\pm}$0.023 to 0.07${\pm}$0.022 head, 0.12${\pm}$0.21 to 0.02${\pm}$0.020 head and 0.43${\pm}$0.041 to 0.22${\pm}$0.040 head, respectively and weaning rate increased from 0.94${\pm}$0.005% to 0.97${\pm}$0.005%. The total number of born per litter and number of born alive per litter were higher(P〈0.05) in the case of mating twice than mating once. The number of weaned per litter, number of mummified per litter and number of stillborn per litter were not significant(P〈0.05) between mating methods. Estrus interval was shorter on the occasion of twice artificial insemination(5.24${\pm}$0.153days) than twice natural mating(6.51${\pm}$0.466days).
With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.
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