• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.62-70
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• 2021

The purpose of this study was to identify health literacy among elderly and to investigate the relationships between healthy literacy and health status. A cross-sectional study was conducted with a sample of 158 participants between July and December 2019. The linguistic and functional health literacy (using the KHLAT and NVS) and self-rated physical and mental health were assessed. Above third of elderly have difficulties reading and understanding linguistic and functional health literacy. There were significant differences in health literacy according to residence, spouse, living together, educational level, occupation, monthly income, and number of diagnosed disease. Linguistic and functional health literacy and self-rated physical and mental health are closely related. Sociodemographic and disease related factors such as residence, educational level, monthly income, and multi-morbidity need to be considered when developing educational programs to improve health literacy. It could be possible to promote health status by improving the health literacy through individualized convergent educational program.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5238-5246
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• 2012

This study was done to identify the evaluation of CPSCS for neurocritical patients and provide effective nursing interventions for these patients. Data were collected from medical records of 203 neurocritical patients over 18 years of age who were admitted to the ICU of C University Hospital during the period from January 2008 to May 2009 and from October 2011 to December 2011. Collected data were analyzed through t-test, ANOVA test, Person's correlation analysis, trend analysis, stepwise multiple regression. The average CPSCS score was $112.09{\pm}18.91$ and there was a significant trendency for higher severity to lead to higher CPSCS's scores(survival: J-T:9.795, die: J-T:5.415, p=<.001). The scores of the respective areas follows measurement of vital sign($3.74{\pm}2.15$), monitoring($28.97{\pm}4.31$), activity daily living ($34.99{\pm}3.66$), feeding($.19{\pm}.98$), intravenous infusion ($18.20{\pm}8.27$), treatment/procedure ($16.93{\pm}4.90$), respiratory therapy($8.61{\pm}7.07$). By means of stepwise multiple regression analysis, the intravenous therapy & medication, respiratory therapy, activities of daily living, and monitoring area that contains the model showed a significant (F=2073.963, p<.001), and they explained 98.1% of CPSCS. These findings provide information that is relevant in designing interventions to enhance CPSCS among neurocritical patients in hospital.

• Health Policy and Management
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• v.26 no.4
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• pp.359-372
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• 2016

Background: The purpose of this study was to develop risk-adjustment models for acute stroke mortality that were based on data from Health Insurance Review and Assessment Service (HIRA) dataset and to evaluate the validity of these models for comparing hospital performance. Methods: We identified prognostic factors of acute stroke mortality through literature review. On the basis of the avaliable data, the following factors was included in risk adjustment models: age, sex, stroke subtype, stroke severity, and comorbid conditions. Survey data in 2014 was used for development and 2012 dataset was analysed for validation. Prediction models of acute stroke mortality by stroke type were developed using logistic regression. Model performance was evaluated using C-statistics, $R^2$ values, and Hosmer-Lemeshow goodness-of-fit statistics. Results: We excluded some of the clinical factors such as mental status, vital sign, and lab finding from risk adjustment model because there is no avaliable data. The ischemic stroke model with age, sex, and stroke severity (categorical) showed good performance (C-statistic=0.881, Hosmer-Lemeshow test p=0.371). The hemorrhagic stroke model with age, sex, stroke subtype, and stroke severity (categorical) also showed good performance (C-statistic=0.867, Hosmer-Lemeshow test p=0.850). Conclusion: Among risk adjustment models we recommend the model including age, sex, stroke severity, and stroke subtype for HIRA assessment. However, this model may be inappropriate for comparing hospital performance due to several methodological weaknesses such as lack of clinical information, variations across hospitals in the coding of comorbidities, inability to discriminate between comorbidity and complication, missing of stroke severity, and small case number of hospitals. Therefore, further studies are needed to enhance the validity of the risk adjustment model of acute stroke mortality.

• Journal of Chest Surgery
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• v.42 no.2
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• pp.226-232
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• 2009

Background: Blunt chest trauma accounts for 90% of all chest traumas in Europe and the United States and this causes 20% of all trauma-related deaths. The major cause of morbidity and mortality after blunt chest trauma is undetected injuries. For this reason, chest computerized tomography has gained popularity for the evaluation of trauma, but it is expensive and it exposes patients to radiation. This study identified the clinical features associated with the diagnosic information obtained on a CT chest scan, as compared with a standard chest X-ray, for patients who sustained blunt trauma to the chest. This study also evaluated the role of a routine computed tomographic (CT) scan for these patients. The patients who had chest computed tomography done after the initial chest x-ray were analyzed separately for the presence of occult injuries. Material and Method: We studied 100 consecutive patients from November 2006 to July 2007: 74 patients after motor vehicle crashes and 26 patients after a fall from a height >2m. Simultaneous with the initial clinical evaluation, an anteroposterior chest radiograph and a helical chest CT scan were obtained for all the patients. The data extracted from the medical record included the vital signs, the interventions and the type and severity of injury (RTS). Result: Among the 100 cases, 79 patients showed at least more than one pathologic sign on their chest radiograph, and 21 patients had a normal chest radiograph. For 17 of the patients who had a normal chest X ray, the CT scan showed multiple injuries, which were pneumothorax, hemothorax, lung contusion, sternal fracture etc. This represents that a CT scan is statistically superior to a chest radiograph to diagnose the pathologic signs. But on the other hand, as for treatment, only 31 patients were diagnosed by CT scan and they were treated with chest tube insertion ect. 42 patients needed ony conservative management without invasive thoracosurgical treatment such as chest tube insertion or open thoracotomy. 27 patients were treated based on the diagnosis made by the chest radiograph and physical examination. Conclusion: Chest computerized tomography was significantly more effective than routine chest X-ray for detecting lung contusion, pneumothorax and mediastinal hematoma, as well as fractured ribs, scapula and, sternum. Although the occult findings increased, the number of patients who needed treatment was small. Therefore, we suggest making selective use of a CT scan to avoid its overuse in ERs.