• Journal of Preventive Medicine and Public Health
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• v.11 no.1
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• pp.123-127
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• 1978

The major objective of this research is to identify those hospital characteristics that best explain cost variation among hospitals and to formulate linear models that can predict hospital costs. Specific emphasis is placed on hospital output, that is, the identification of diagnosis related patient groups (DRGs) which are medically meaningful and demonstrate similar patterns of hospital resource consumption. A casemix index is developed based on the DRGs identified. Considering the common problems encountered in previous hospital cost research, the following study requirements are estab-lished for fulfilling the objectives of this research: 1. Selection of hospitals that exercise similar medical and fiscal practices. 2. Identification of an appropriate data collection mechanism in which demographic and medical characteristics of individual patients as well as accurate and comparable cost information can be derived. 3. Development of a patient classification system in which all the patients treated in hospitals are able to be split into mutually exclusive categories with consistent and stable patterns of resource consumption. 4. Development of a cost finding mechanism through which patient groups' costs can be made comparable across hospitals. A data set of Medicare patients prepared by the Social Security Administration was selected for the study analysis. The data set contained 27,229 record abstracts of Medicare patients discharged from all but one short-term general hospital in Connecticut during the period from January 1, 1971, to December 31, 1972. Each record abstract contained demographic and diagnostic information, as well as charges for specific medical services received. The 'AUT-OGRP System' was used to generate 198 DRGs in which the entire range of Medicare patients were split into mutually exclusive categories, each of which shows a consistent and stable pattern of resource consumption. The 'Departmental Method' was used to generate cost information for the groups of Medicare patients that would be comparable across hospitals. To fulfill the study objectives, an extensive analysis was conducted in the following areas: 1. Analysis of DRGs: in which the level of resource use of each DRG was determined, the length of stay or death rate of each DRG in relation to resource use was characterized, and underlying patterns of the relationships among DRG costs were explained. 2. Exploration of resource use profiles of hospitals; in which the magnitude of differences in the resource uses or death rates incurred in the treatment of Medicare patients among the study hospitals was explored. 3. Casemix analysis; in which four types of casemix-related indices were generated, and the significance of these indices in the explanation of hospital costs was examined. 4. Formulation of linear models to predict hospital costs of Medicare patients; in which nine independent variables (i. e., casemix index, hospital size, complexity of service, teaching activity, location, casemix-adjusted death. rate index, occupancy rate, and casemix-adjusted length of stay index) were used for determining factors in hospital costs. Results from the study analysis indicated that: 1. The system of 198 DRGs for Medicare patient classification was demonstrated not only as a strong tool for determining the pattern of hospital resource utilization of Medicare patients, but also for categorizing patients by their severity of illness. 2. The wei틴fed mean total case cost (TOTC) of the study hospitals for Medicare patients during the study years was $11,27.02 with a standard deviation of $117.20. The hospital with the highest average TOTC ($1538.15) was 2.08 times more expensive than the hospital with the lowest average TOTC ($743.45). The weighted mean per diem total cost (DTOC) of the study hospitals for Medicare patients during the sutdy years was $107.98 with a standard deviation of $15.18. The hospital with the highest average DTOC ($147.23) was 1.87 times more expensive than the hospital with the lowest average DTOC ($78.49). 3. The linear models for each of the six types of hospital costs were formulated using the casemix index and the eight other hospital variables as the determinants. These models explained variance to the extent of 68.7 percent of total case cost (TOTC), 63.5 percent of room and board cost (RMC), 66.2 percent of total ancillary service cost (TANC), 66.3 percent of per diem total cost (DTOC), 56.9 percent of per diem room and board cost (DRMC), and 65.5 percent of per diem ancillary service cost (DTANC). The casemix index alone explained approximately one half of interhospital cost variation: 59.1 percent for TOTC and 44.3 percent for DTOC. Thsee results demonstrate that the casemix index is the most importand determinant of interhospital cost variation Future research and policy implications in regard to the results of this study is envisioned in the following three areas: 1. Utilization of casemix related indices in the Medicare data systems. 2. Refinement of data for hospital cost evaluation. 3. Development of a system for reimbursement and cost control in hospitals.

• Sleep Medicine and Psychophysiology
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• v.24 no.1
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• pp.24-31
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• 2017

Objectives: Periodic limb movement disorder (PLMD) has been debated with regard to its clinical significance and diagnostic criteria. The current diagnostic criterion for PLMD in adults has been changed from periodic limb movement index (PLMI) > 5/hour to PLMI > 15/hour by the International Classification of Sleep Disorders (ICSD). In this study, we aimed to investigate the changes in polysomnographic sleep variables according to PLMI and to determine the relevance of the diagnostic criterion for PLMD. Methods: Out of 4195 subjects who underwent standard polysomnography, we selected 666 subjects (370 males and 296 females, aged $47.1{\pm}14.8$) who were older than 17 years and were not diagnosed with primary insomnia, sleep apnea, narcolepsy, or REM sleep behavior disorder. Subjects were divided into three groups according to PLMI severity: group 1 ($PLMI{\leq}5$), group 2 (5 < $PLMI{\leq}15$), and group 3 (PLMI > 15). Demographic and polysomnographic sleep variables and Epworth sleepiness scale (ESS) were compared among the three groups. Results: There were significant differences among the three groups in age and gender. Sleep efficiency (SE) and stage 3 sleep percentage in group 1 were significantly higher than those in groups 2 and 3. The wake after sleep onset (WASO) score in group 1 was significantly lower than those in groups 2 and 3. However, there were no significant differences in SE, stage 3 sleep percentage, or WASO between groups 2 and 3. Sleep latency (SL) in group 1 was significantly lower than that in group 3, but there was no difference in SL between group 2 and group 3. ESS score in group 1 was significantly higher than that in group 3, but there was no difference between group 2 and group 3. Partial correlation analysis adjusted by age showed that PLMI was significantly related to SE and WASO. Conclusion: This study suggests that PLMI influences polysomnographic sleep variables. In addition, we found the individuals who did not have PLMD but had PLMI > 5 were not different in polysomnographic sleep variables from the individuals who had PLMD according to the current criterion. These results raise questions about the relevance of the current diagnostic criterion of PLMD.

• Journal of dental hygiene science
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• v.17 no.6
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• pp.487-494
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• 2017

There is little evidence on the effects of environmental tobacco smoke (ETS) on prevalence of periodontal disease. The aims of this study were to explore the trends of prevalence of periodontal disease and types of exposure to smoke, including ETS according to the survey year, identify factors affecting periodontal disease, and compare the effect size of periodontal disease between active smokers and secondhand smokers. Data on 11,643 individuals were obtained from the fourth and fifth Korean National Health and Nutritional Examination Surveys. Information on exposure to ETS at home and work was self-reported. Severity of periodontal disease was evaluated using the community periodontal index. A multivariate logistic regression analysis was performed to model periodontal disease using types of smoking and the survey year. Overall, the prevalence of periodontal disease was 26.0% (n=3,029) and about 9% of the study population were secondhand smokers. The prevalence of periodontal disease among smokers was significantly increased according to smoking types by year. Active smokers showed a statistically significant adjusted odds ratio (aOR) for having periodontal disease except in the year 2007, whereas secondhand smokers had significant associations only in 2010 (aOR, 1.68; 95% confidence interval, 1.05 to 2.70) compared to non-smokers. For secondhand smokers, the statistical relationship of predicting periodontal disease was weaker than that of active smokers. However, ETS should separately be considered as an important risk factor for periodontal disease. This study suggested the need for further investigation of the impact of ETS on prevalence of periodontal disease using in-depth research designs and objective measurements for assessing periodontal disease and ETS.

• Education of Primary School Mathematics
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• v.16 no.3
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• pp.229-250
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• 2013

The purpose of this study is analyzing 'observation and recommendation letter by teacher', which is being submitted to screen and enhance the utilization of gifted students in accordance with recently introduced gifted students observation, recommendation and screening system. For the purpose, this study will provide with objective securing plan of 'observation and recommendation letter by teacher' by developing an optimum evaluation model. The research findings were as follows: First, the result of analysis on the mathematically gifted students behavior characteristic as appeared in 'observation and recommendation letter by teacher' suggested that the recommending teachers have the tendency of giving superficial statement instead of giving concrete case description. When it was analyzed for frequency by the 'observation and recommendation letter by teacher' analysis framework devised by the author, the teachers showed the tendency of concentrating on specific questions. Meanwhile, there was a tendency that teachers concentrate on specific gifted behavior characteristic or area for which concrete case had been suggested. The reason is believed that such part is easy to observe and state while others are not, or, teachers did not judge the other part as the characteristic of gifted students. Second, the gifted students behavior characteristics as appeared in 'observation and recommendation letter by teacher' were made into scores by Rubric model. When the interrater reliability was analyzed based on these scores, the correlation coefficient of 1st scoring was .641. After a discussion session was taken and 2nd scoring was done 3 weeks later, the correlation coefficient of 2nd scoring increased to .732. The reason is believed that; i) the severity among scorers was adjusted by the discussion session after the 1st scoring, ii) the scorers established detail judgment standard on various situations which can appear because of the descriptive nature, and, (iii) they found a consensus on scoring for a new situation appeared. It implies that thorough understanding and application of scorers on evaluation model is as important as the development of optimum model for the differentiation of mathematically gifted elementary students.

• Sleep Medicine and Psychophysiology
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• v.26 no.1
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• pp.33-43
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• 2019

Objectives: Bipolar disorder is characterized by repetitive relapses that result in psychosocial dysfunctions. The functioning of bipolar disorder patients is related to the severity of symptoms, quality of sleep, drug compliance, and social support. The purpose of this study was to investigate the association between sociodemographic and clinical factors and functional status in bipolar disorder patients. Methods: A total of 52 bipolar disorder patients participated in the study. The following scales were utilized: Korean version of personal and social performance scale (K-PSP), Korean version of Hamilton rating scale for depression (K-HDRS), Korean version of young mania rating scale (K-YMRS), Korean version of pittsburgh sleep quality index (PSQI-K), Korean version of drug attitude inventory (K-DAI), mood disorders insight scale (MDIS), and multidimensional scale of perceived social support (MSPSS). Results: The K-PSP score showed a negative relationship with K-HDRS score (r = -0.387, p = 0.005), but not with K-YMRS score (r = -0.205, p = 0.145). The K-PSP score showed a negative relationship with global PSQI-K score (r = -0.378, p = 0.005) and overall sleep quality (r = -0.353, p = 0.010). The K-PSP scores were positively associated with the KDAI score (r = 0.409, p = 0.003) and MSPSS score (r = 0.334, p = 0.015). The predictive factors for K-PSP were overall sleep quality and social support from family. Conclusion: Our study showed that depressive symptoms were related to overall function in bipolar disorder. Also, our study suggested that improving sleep quality is important in maintaining functional status. Appropriate social support and positive perception toward the drug may lead to the higher level of functioning. This study is meaningful in that the functional status of bipolar disorder patients is analyzed in a multivariate manner in relation to various variables in psychosocial aspects.

• Korean Journal of Psychosomatic Medicine
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• v.29 no.1
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• pp.67-76
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• 2021

Objectives : The aim of this study was to compare activities of daily living (ADLs) according to degenerative changes in brain [i.e., medial temporal lobe atrophy (MTA), white matter hyperintensities] and to examine the association between neurocognitive functions and ADLs in Korean patients with dementia due to Alzheimer's disease (AD) and mild cognitive impairment (MCI). Methods : Participants were 111 elderly subjects diagnosed with AD or MCI in this cross-sectional study. MTA in brain MRI was rated with standardized visual rating scales (Scheltens scale) and the subjects were divided into two groups according to Scheltens scale. ADLs was evaluated with the Korean version of Blessed Dementia Scale-Activity of daily living (BDS-ADL). Neurocognitive function was evaluated with the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease assessment packet (CERAD-K). Independent t-test was performed to compare ADLs with the degree of MTA. Pearson correlation and hierarchical multiple regression analyses were performed to analyze the relationship between ADLs and neurocognitive functions. Results : The group with high severity of the MTA showed significantly higher BDS-ADL scores (p<0.05). The BDS-ADL score showed the strongest correlation with the word list recognition test among sub-items of the CERAD-K test (r=-0.568). Findings from the hierarchical multiple regression analysis revealed that the scores of MMSE-K and word list recognition test were factors that predict ADLs (F=44.611, p<0.001). Conclusions : ADLs of AD and MCI patients had significant association with MTA. Our study, which identifies factors correlated with ADLs can provide useful information in clinical settings. Further evaluation is needed to confirm the association between certain brain structures and ADLs.

• Sleep Medicine and Psychophysiology
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• v.19 no.2
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• pp.68-76
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• 2012

Objectives: Sleep disorders cause changes of autonomic nervous system (ANS) which affect cardiovascular system. Primary insomnia (PI) makes acceleration of sympathetic nervous system (SNS) tone by sleep deficiency and arousal. Obstructive sleep apnea syndrome (OSAS) sets off SNS by frequent arousals and hypoxemias during sleep. We aimed to compare the changes of heart rate variability (HRV) indices induced by insomnia or sleep apnea to analyze for ANS how much to be affected by PI or OSAS. Methods: Total 315 subjects carried out nocturnal polysomnography (NPSG) were categorized into 4 groups - PI, mild, moderate and severe OSAS. Severity of OSAS was determined by apnea-hypopnea index (AHI). Then we selected 110 subjects considering age, sex and valance of each group's size [Group 1 : PI (mean age=$41.50{\pm}13.16$ yrs, AHI <5, n=20), Group 2 : mild OSAS (mean age=$43.67{\pm}12.11$ yrs, AHI 5-15, n=30), Group 3 : moderate OSAS (mean age $44.93{\pm}12.38$ yrs, AHI 16-30, n=30), Group 4 : severe OSAS (mean age=$45.87{\pm}12.44$ yrs, AHI >30, n=30)]. Comparison of HRV indices among the four groups was performed with ANCOVA (adjusted for age and body mass index) and Sidak post-hoc test. Results: We found statistically significant differences in HRV indices between severe OSAS group and the other groups (PI, mild OSAS and moderate OSAS). And there were no significant differences in HRV indices among PI, mild and moderate OSAS group. In HRV indices of PI and severe OSAS group showing the most prominent difference in the group comparisons, average RR interval were $991.1{\pm}27.1$ and $875.8{\pm}22.0$ ms (p=0.016), standard deviation of NN interval (SDNN) was $85.4{\pm}6.6$ and $112.8{\pm}5.4$ ms (p=0.022), SDNN index was $57.5{\pm}5.2$ and $87.6{\pm}4.2$ (p<0.001), total power was $11,893.5{\pm}1,359.9$ and $18,097.0{\pm}1,107.2ms^2$(p=0.008), very low frequency (VLF) was $7,534.8{\pm}1,120.1$ and $11,883.8{\pm}912.0ms^2$ (p=0.035), low frequency (LF) was $2,724.2{\pm}327.8$ and $4,351.6{\pm}266.9ms^2$(p=0.003). Conclusions: VLF and LF which were correlated with SNS tone showed more increased differences between severe OSAS group and PI group than other group comparisons. We could suggest that severe OSAS group was more influential to increased SNS activity than PI group.