• Quality Improvement in Health Care
• /
• v.10 no.2
• /
• pp.164-175
• /
• 2003

Objectives: To evaluate the performance of models to predict AMI patients death using severity adjustment measures in Korea. Methods: Medical records of 861 patients treated by AMI in 7 general hospitals during 1996 and 1997 were reviewed by trained nurses. We measured the severity of patients by APACHE III, MedisGroups, CSI and DS. Using each severity method a predictive mortality for each patient was calculated from a logistic regression model including the severity score. The statistical performance of each severity method model was evaluated by using c-statistics and R2. For each hospital, z scores compared actual and expected mortality rates. Results: The overall in-hospital mortality was 14.5%, ranged from 10.0% to 22.2%. The distributions of severity scores for each method was significantly different by hospitals. The four severity-adjusted models to predict AMI patients death varied in their statistical performance for discrimination power of patients death. Order of Severity-adjusted mortality rates and z scores by four severity measures was different. Conclusion: Severity-adjusted mortality rates of AMI patients might be applied as an indicator for hospital performance evaluation in Korea. Because different severity methods frequently produce different impressions about relative hospital performance, more studies has to be done to use it as quality indicator and more attention should be paid to select appropriate severity measures.

• Journal of Preventive Medicine and Public Health
• /
• v.34 no.3
• /
• pp.244-252
• /
• 2001

Objective : Health insurers and policy makers are increasingly examining the hospital mortality rate as an indicator of hospital quality and performance. To be meaningful, a risk-adjustment of the death rates must be implemented. This study reviewed 5 severity measurement methods and applied them to the same data set to determine whether judgments regarding the severity-adjusted hospital mortality rates were sensitive to the specific severity measure. Methods : The medical records of 584 patients who underwent coronary artery bypass graft surgery in 6 general hospitals during 1996 and 1997 were reviewed by trained nurses. The MedisGroups, Disease Staging, Computerized Severity Index, APACHE III and KDRG were used to quantify severity of the patients. The predictive probability of death was calculated for each patient in the sample from a multivariate logistic regression model including the severity score, age and sex to evaluate the hospitals' performance, the ratio of the observed number of deaths to the expected number for each hospital was calculated. Results : The overall in-hospital mortality rate was 7.0%, ranging from 2.7% to 15.7% depending on the particular hospital. After the severity adjustment, the mortality rates for each hospital showed little difference according to the severity measure. The 5 severity measurement methods varied in their statistical performance. All had a higher c statistic and $R^2$ than the model containing only age and sex. There was a little difference in the relative hospital performance evaluation by the severity measure. Conclusion : These results suggest that judgments regarding a hospital's performance based on severity adjusted mortality can be sensitive to the severity measurement method. Although the 5 severity measures regarding hospital performance concurred, more often than would be expected by chance, the assessment of an individual hospital mortality rates varied by the different severity measurement method used.

• Korean Journal of Psychosomatic Medicine
• /
• v.6 no.1
• /
• pp.28-34
• /
• 1998

Objective: This study was designed to evaluate the etiological factors of the PTSD(post traumatic stress disorder) by examining the relationship between severity of physical trauma and subsequent the severity of PTSD symptom in traffic accident related PTSD patients. Method: Subjects were 21 psychiatric inpatients with history of traffic accident related PTSD(DSM-IV criteria), the purpose of evaluation of mental disability and no evidence of organic brain leisons. The severity of physical trauma was assessed by McBride number of nonpsychiatric department and the presence / absence of loss of conciousness. The severity of PTSD symptom was assessed by Hovens' self rating inventory for PTSD. And then we evaluated the correlation between these two factors. And we also evaluated relationship between severity of PTSD symtom and clinical variables. Results : There were no significant relationship between McBride number of nonpsychiatric department severity and symptomatic severity(r= 0.17, p<0.05), the presence / absence of loss of conciousness and symptomatic severity(p>0.05). And significant relationship between symptomatic severity and clinical varibles such as sex, education level, marital status(p<0.05). Conclusions : These data did not support data of previous studies that traumatic severity was correlated with symptom severity but, suggested that other variables affecting the severity of PTSD symptom is more important indirectly. And that the 'trauma' in PTSD is psychological meaning rather than physical meaning is also suggested.

• The Journal of Korean Medicine
• /
• v.38 no.3
• /
• pp.185-196
• /
• 2017

Backgrounds: Inpatient Classification System for Korean Medicine (KDRG-KM) was developed and has been applied for monitoring the costs of KM hospitals. Yet severity of patients' condition is not applied in the KDRG-KM. Objectives: This study aimed to develop the severity classification methods for KDRG-KM and assessed the explanation powers of severity adjusted KDRG-KM. Methods: Clinical experts panel was organized based on the recommendations from 12 clinical societies of Korean Medicine. Two expert panel workshops were held to develop the severity classification options, and the Delphi survey was performed to measure CCL(Complexity and Comorbidity Level) scores. Explanation powers were calculated using the inpatient EDI claim data issued by hospitals and clinics in 2012. Results: Two options for severity classification were deduced based on the severity classification principle in the domestic and foreign DRG systems. The option one is to classify severity groups using CCL and PCCL(Patient Clinical Complexity Level) scores, and the option two is to form a severity group with patients who belonged principal diagnosis-secondary diagnosis combinations which prolonged length of stay. All two options enhanced explanation powers less than 1%. For third option, patients who received certain treatments for severe conditions were grouped into severity group. The treatment expense of the severity group was significantly higher than that of other patients groups. Conclusions: Applying the severity classifications using principal diagnosis and secondary diagnoses can advance the KDRG-KM for genuine KM hospitalization. More practically, including patients with procedures for severe conditions in a severity group needs to be considered.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.1
• /
• pp.197-206
• /
• 2015

Defect severity that is a measure of the impact caused by the defect plays an important role in software quality activities because not all software defects are equal. Earlier studies have concentrated on defining defect severity levels, but there have almost never been trials of measuring module severity. In this paper, first, we define a defect severity metric in the form of an exponential function using the characteristics that defect severity values increase much faster than severity levels. Then we define a new metrics set for software module severity using the number of defects in a module and their defect severity metric values. In order to show the applicability of the proposed metrics, we performed an analytical validation using Weyuker's properties and experimental validation using NASA open data sets. The results show that ms is very useful for measuring the module severity and msd can be used to compare different systems in terms of module severity.

• Fire Science and Engineering
• /
• v.33 no.2
• /
• pp.139-144
• /
• 2019

The increase in the elderly population also increased the damage and deaths of the elderly drivers. However, studies on the severity and severity of the elderly driver are not actively conducted and the factors are unknown. In this study, I tried to find out the factors affecting the damage and severity of the elderly driver in the frontal collision and to utilize them additionally in the severity classification. Collision Deformation Classification (CDC) Code was used to check the extent of damage to the vehicle. Abbreviated Injury Scale (AIS) was used to determine the injury parts and severity of injury, and the Injury Severity Score (ISS) to confirm the severity of the patient. The odds ratios of severe injury patients were found to be 7.381 in the subjects with 5 or more deformation extent and the ${\beta}$ value of the deformation extent was 0.453 in the analysis of the severity by linear regression analysis. Therefore, the degree of deformation extent of 5 or more can be suggested as a criterion that can be used additionally to the severity classification in the elderly driver.

• International Journal of Highway Engineering
• /
• v.17 no.3
• /
• pp.117-124
• /
• 2015

PURPOSES : The purpose of this study is to verify traffic accident injury severity factors for elderly drivers and the relative relationship of these factors. METHODS : To verify the complicated relationship among traffic accident injury severity factors, this study employed a structural equation model (SEM). To develop the SEM structure, only the severity of human injuries was considered; moreover, the observed variables were selected through confirmatory factor analysis (CFA). The number of fatalities, serious injuries, moderate injuries, and minor injuries were selected for observed variables of severity. For latent variables, the accident situation, environment, and vehicle and driver factors were respectively defined. Seven observed variables were selected among the latent variables. RESULTS : This study showed that the vehicle and driver factor was the most influential factor for accident severity among the latent factors. For the observed variable, the type of vehicle, type of accident, and status of day or night for each latent variable were the most relative observed variables for the accident severity factor. To verify the validity of the SEM, several model fitting methods, including ${\chi}^2/df$, GFI, AGFI, CFI, and others, were applied, and the model produced meaningful results. CONCLUSIONS : Based on an analysis of results of traffic accident injury severity for elderly drivers, the vehicle and driver factor was the most influential one for injury severity. Therefore, education tailored to elderly drivers is needed to improve driving behavior of elderly driver.

• The Journal of Korean Medicine
• /
• v.23 no.4
• /
• pp.15-26
• /
• 2002

There is much confusion in the field of atopic dermatitis (AD) regarding how to best measuredisease severity objectively. Therefore, we aimed to establish a new adequate scoring system for AD, that should be based on comparisonand analysis of various scoring systems. We report as follows. Methods: We searched for data relating to severity scoring systems for atopic dermatitis in Entrez PubMed From 1990 to 2001 Results and Conclusions: 1. Properties of severity scoring systems were validity, reliability, sensitivity of change and ease of use. 2. The essential items of severity scoring systems were extent. intensity and subjective symptoms. 3. The surface extent of the lesion was evaluated by the percentage of involvement of each of 10 areas. 4. The criteria of severity were divided into intensity and subjective symptoms. Intensity items are erythema, papulation, lichenification, oozing, dryness, excoriations, and pigmentation. The subjective symptom is pruritus, evaluated according to sleep loss. 5. The significant items of severity scoring system were symptomsrather than areas. As it were, we assumed extent accounted for around 30% of each total score, with intensity and subjective symptoms representing 70%.

• Journal of Korean Academy of Nursing
• /
• v.30 no.5
• /
• pp.1243-1253
• /
• 2000

The purpose of this study was to verify the validity of the Patient Severity Classification Tool by examining the correlations between the APACHE Ⅲ and the Patient Severity Classification Tool and to propose admission criteria to the ICU. The instruments used for this study were the APACHE Ⅲ developed by Knaus and the Patient Severity Classification Tool developed by Korean Clinical Nurses Association. Data was collected from the 156 Medical ICU patients during their first 24 hours of admission at the Seoul National University Hospital by three trained Medical ICU nurses from April 20 to August 31 1999. Data were analyzed using the frequency, $x^2$, Wilcoxon rank sum test, and Spearman rho. There was statistically significant correlations between the scores of the APACHE III and the Patient Severity Classification Tool. Mortality rate was increased as patients classification of severity in both the APACHE III and the Patient Severity Classification Tool scored higher. The Patient Severity Classification Tool was proved to be a valid and reliable tool, and a useful tool as one of the severity predicting factors, ICU admission criteria, information sharing between ICUs, quality evaluations of ICUs, and ICU nurse staffing.

• International Journal of Highway Engineering
• /
• v.18 no.3
• /
• pp.127-134
• /
• 2016

PURPOSES : Low visibility caused by dark surroundings at nighttime affects the likelihood of accidents, and various efforts, such as installing road safety facilities, have been made to reduce accidents at night. Despite these efforts, the nighttime severity index (SI) in Korea was higher than the daytime SI during 2011-2014. This study determined the factors affecting daytime and nighttime accident severity through a discriminant analysis. METHODS : Discriminant analysis. RESULTS : First, drowsiness, lack of attention, and lighting facilities affected both daytime and nighttime accident severity. Accidents were found to be caused by a low ability to recognize the driving conditions and a low obstacle avoidance capability. Second, road conditions and speeding affected only the daytime accident severity. Third, failure to maintain a safe distance significantly affected daytime accident severity and nonsignificantly affected nighttime accident severity. The majority of such accidents were caused by rear-end collisions of vehicles driving in the same direction; given the low relative speed difference in such cases, the shock imparted by the accidents was minimal. CONCLUSIONS : Accidents caused by a failure to maintain a safe distance has lower severity than do accidents caused by other factors.