• Environmental Analysis Health and Toxicology
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• v.23 no.4
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• pp.231-245
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• 2008

Various methods for detecting changes in response behaviors of indicator specimens are presented for monitoring effects of toxic treatments. The movement patterns of individuals are quantitatively characterized by statistical (i.e., ANOVA, multivariate analysis) and computational (i.e., fractal dimension, Fourier transform) methods. Extraction of information in complex behavioral data is further illustrated by techniques in ecological informatics. Multi-Layer Perceptron and Self-Organizing Map are applied for detection and patterning of response behaviors of indicator specimens. The recent techniques of Wavelet analysis and line detection by Recurrent Self-Organizing Map are additionally discussed as an efficient tool for checking time-series movement data. Behavioral monitoring could be established as new methodology in integrative ecological assessment, tilling the gap between large-scale (e.g., community structure) and small-scale (e.g., molecular response) measurements.

• Korean Journal of Clinical Pharmacy
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• v.18 no.2
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• pp.124-131
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• 2008

The impacts of guideline for digestives on physicians' prescription of GI medication Clinical practice guidelines provide benefits to physicians, patients, and researchers. It also helps doctors to make decisions in medical services. In many countries, practice guidelines lead to activities of quality improvement and are developed using evidence based methods. This research was to assess the impacts of Korean Medical Association's guideline for digestives on the change of physicians' behavior. This study was progressed as one-group pre-test post-test quasi-experimental design using health insurance claims data. The unit of analysis was institution. Data was analyzed using paired t-test for change of prescription rate before and after the distribution of practice guidelines. And the multiple regression analysis was performed to examine the independent impact of the guideline on the prescribing rate of GI medication. Prescription rates of GI medication per claim by medical institution increased significantly, 1.98%point (from 50.27% to 52.25%) and multivariate regression analysis showed significant increase in the prescription rate of GI medication after the distribution of guideline (p<0.001). In conclusion, the distribution of guideline for digestive might not have the effects on the change in provider's behavior. Furthermore, to activate the use of practice guideline, it would be necessary to educate the contents to physicians as well as to develop practice guideline.

• Health Policy and Management
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• v.28 no.2
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• pp.138-144
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• 2018

Background: Diagnostic imaging fee had been reduced in May 2011, but it was recovered after 6 months because of strong opposition of medical providers. This study aimed to analyze the behavior of medical providers according to fee changes. Methods: The National Health Insurance claims data between November 2010 and December 2012 were used. The number of exams per computed tomography was analyzed to verify that the fee changes increased or decreased the number of exams. Multivariate regression model were applied. Results: The monthly number of exams increased by 92.5% after fee reduction, so the diagnostic imaging spending were remained before it. But medical provider decreased the number of exams after fee return. After adjusting characteristic of hospitals, fee reduction increased the monthly number of exams by 48.0% in a regression model. Regardless type of hospitals and severity of disease, the monthly number of exams increased during period of fee reduction. The number of exams in large-scaled hospitals (tertiary and general hospital) were increased more than those of small-scaled hospitals. Conclusion: Fee-reduction increased unnecessary diagnostic exams under the fee-for-service system. It is needed to define appropriate exam and change reimbursement system on the basis of guideline.

• Ocean and Polar Research
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• v.26 no.1
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• pp.11-22
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• 2004

Benthic pollution assessment based on macrobenthic community structure with environmental variables was carried out at twelve stations during two periods on a presumed pollution gradient in Gamak Bay. Univariate and multivariate methods were applied to investigate structural changes in the benthic communities. A clear gradient of pollution effects on the macrobenthic community was observed from the interior to the exterior of the bay. The community on the northwestern basin was severely disturbed due to a low level of hydrodynamics and a large amount of pollutant input from nearby cities. Exterior regions on the southern basin appeared to have the best benthic environmental characteristics among all stations according to most methods of analysis. Central ridge regions and two stations around the islets in the mouth of the bay exhibited intermediate levels of perturbation when compared to the more disturbed interior and undisturbed exterior regions. Pollution effects on the communities were attenuated at the southern area of the central ridge during spring compared to those of summer, where aquacultural farming was densely distributed. The environmental variables primarily correlated to the macrobenthic community structure were total organic carbon (C), organochlorine pesticides (OCPs), and tributyltins (TBTs), contents found on the surface sediment, as anthropogenic variables indicating organic materials.

• Journal of Korean Biological Nursing Science
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• v.16 no.4
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• pp.259-266
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• 2014

Purpose: The purpose of this study was to analyze risk factors in predicting medical patients transferred to Intensive Care Unit (ICU) on the general ward. Methods: We reviewed retrospectively clinical data of 120 medical patients on the general ward and a Modified Early Warning Score (MEWS) between ICU group and general ward group. Data were analyzed with multivariate logistic regression and the area under the receiver operating characteristic curves using SPSS/WIN 18.0 program. Results: Fifty-two ICU patients and 68 general ward patients were included. In multivariate logistic regression, the MEWSs (Odds Ratio [OR], 1.91; 95% confidence interval [CI], 1.32-2.76), sequential organ failure assessment score (OR, 1.28; 95% CI, 1.10-1.72), $PaO_2/FiO_2$ ratio (OR, 0.98; 95% CI, 0.98-0.99), and saturation (OR, 0.93; 95% CI, 0.88-0.99) were predictive of ICU transfer. The sensitivity and the specificity of the MEWSs used with a cut-off value of six were 80.8% and 70.6% respectively for ICU transfer. Conclusion: These findings suggest that early prediction and treatment of patients with high risk of ICU transfer may improve the prognosis of patients.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.21 no.4
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• pp.413-422
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• 2014

Purpose: The purpose of this study was to identify the nutrition-related factors influencing the prevalence of pressure ulcers among patients admitted to an intensive care unit. Methods: Research participants were 112 patients who were admitted to the ICU of a university hospital. Data were collected through questionnaires which included general characteristics, diet-related characteristics, nutritional status, and pressure ulcer status. Multivariate logistic regression was used to identify independent factors association with prevalence of pressure ulcer Results: The prevalence of pressure ulcers was 58 patients (51.8%) at 10th day after ICU admission. In multivariate analysis, prevalence of pressure ulcers at 10th day in ICU was significantly higher in the nutritional risk group (OR=6.43), malnutrition group (OR=88.02), and deceased serum albumin group (OR=28.83). Conclusion: The results of this research indicate that scores on MNA (Mini Nutritional Assessment) and serum albumin were significant predictors of pressure ulcer prevalence in ICU patients. Therefore, regular MNA-SF and albumin checkups are needed to identify risk for pressure ulcer for ICU patients. In the case of decreased MNA-SF scores and serum albumin levels, more intensive pressure ulcer care is needed for ICU patients.

• Smart Structures and Systems
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• v.15 no.5
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• pp.1329-1344
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• 2015

The stiffness of a structure is one of several structural signals that are useful indicators of the amount of damage that has been done to the structure. To accurately estimate the stiffness, an equation of motion containing a stiffness parameter must first be established by expansion as a linear series model, a Taylor series model, or a power series model. The model is then used in multivariate autoregressive modeling to estimate the structural stiffness and compare it to the theoretical value. Stiffness assessment for modeling purposes typically involves the use of one of three statistical model refinement approaches, one of which is the efficient Akaike information criterion (AIC) proposed in this paper. If a newly added component of the model results in a decrease in the AIC value, compared to the value obtained with the previously added component(s), it is statistically justifiable to retain this new component; otherwise, it should be removed. This model refinement process is repeated until all of the components of the model are shown to be statistically justifiable. In this study, this model refinement approach was compared with the two other commonly used refinement approaches: principal component analysis (PCA) and principal component regression (PCR) combined with the AIC. The results indicate that the proposed AIC approach produces more accurate structural stiffness estimates than the other two approaches.

• Korea Journal of Hospital Management
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• v.25 no.3
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• pp.53-66
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• 2020

This study is aimed at investigated and compared the differences in the affect of hospital specialization according to hospital size using claims data of the Health Insurance and Review Assessment National Inpatient Sample in 2018 for diseases of the musculoskeletal system and connective tissue. To this end, we used multivariate hierarchical linear models(a.k.a., multi-level models) using two-tier data from 106,599 patients discharged after diseases of the musculoskeletal system and connective tissue from 734 hospitals. Multivariate results indicate that patients who were discharged with diseases of the musculoskeletal system and connective tissue from specialized hospitals with 200 beds or less stayed shorter and paid less inpatient charge than those who were discharged from less specialized hospitals. But for hospitals with 201-300 beds, no positive impact relationship was found between hospital specialization and operational performance. This finding may be limited evidence that the affect of a hospital's specialization strategy may vary depending on the size of the hospital. We discussed several managerial and health policy implications below.

• Journal of Ginseng Research
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• v.43 no.4
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• pp.508-516
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• 2019

Background: Ginsenosides are not only the principal bioactive components but also the important indexes to the quality assessment of Panax ginseng Meyer. Their contents in cultivated ginseng vary with the growth environment and age. The present study aimed at evaluating the significant difference between 36 cultivated ginseng of different cultivation areas and ages based on the simultaneously determined contents of 14 ginsenosides. Methods: A high-performance liquid chromatography (HPLC) coupled with triple quadrupole mass spectrometer (MS) method was developed and used in the multiple reaction-monitoring (MRM) mode (HPLC-MRM/MS) for the quantitative analysis of ginsenosides. Multivariate statistical analysis, such as principal component analysis and partial least squares-discriminant analysis, was applied to discriminate ginseng samples of various cultivation areas and ages and to discover the differentially accumulated ginsenoside markers. Results: The developed HPLC-MRM/MS method was validated to be precise, accurate, stable, sensitive, and repeatable for the simultaneous determination of 14 ginsenosides. It was found that the 3- and 5-yr-old ginseng samples were differentiated distinctly by all means of multivariate statistical analysis, whereas the 4-yr-old samples exhibited similarity to either 3- or 5-yr-old samples in the contents of ginsenosides. Among the 14 detected ginsenosides, Rg1, Rb1, Rb2, Rc, 20(S)-Rf, 20(S)-Rh1, and Rb3 were identified as potential markers for the differentiation of cultivation ages. In addition, the 5-yr-old samples were able to be classified in cultivation area based on the contents of ginsenosides, whereas the 3- and 4-yr-old samples showed little differences in cultivation area. Conclusion: This study demonstrated that the HPLC-MRM/MS method combined with multivariate statistical analysis provides deep insight into the accumulation characteristics of ginsenosides and could be used to differentiate ginseng that are cultivated in different areas and ages.

• Toxicological Research
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• v.28 no.2
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• pp.81-91
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• 2012

Many risk factors exist for chemotherapy-induced nausea and vomiting (CINV). This study utilized a multivariate projection technique to identify which risk factors were predictive of CINV in clinical practice. A single-centre, prospective, observational study was conducted from January 2007~July 2010 in Singapore. Patients were on highly (HECs) and moderately emetogenic chemotherapies with/without radiotherapy. Patient demographics and CINV risk factors were documented. Daily recording of CINV events was done using a standardized diary. Principal component (PC) analysis was performed to identify which risk factors could differentiate patients with and without CINV. A total of 710 patients were recruited. Majority were females (67%) and Chinese (84%). Five risk factors were potential CINV predictors: histories of alcohol drinking, chemotherapy-induced nausea, chemotherapy-induced vomiting, fatigue and gender. Period (ex-/current drinkers) and frequency of drinking (social/chronic drinkers) differentiated the CINV endpoints in patients on HECs and anthracycline-based, and XELOX regimens, respectively. Fatigue interference and severity were predictive of CINV in anthracycline-based populations, while the former was predictive in HEC and XELOX populations. PC analysis is a potential technique in analyzing clinical population data, and can provide clinicians with an insight as to what predictors to look out for in the clinical assessment of CINV. We hope that our results will increase the awareness among clinician-scientists regarding the usefulness of this technique in the analysis of clinical data, so that appropriate preventive measures can be taken to improve patients' quality of life.