• Journal of Digital Convergence
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• v.10 no.3
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• pp.197-205
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• 2012

In this study, we analyzed situation and length of stay(LOS) variations of inpatients with pressure ulcer using patient safety indicators developed by the United States Agency for Healthcare Research and Quality(AHRQ) and proposed management of medical quality and development of policy. The dataset was taken from 1,373 database of the hospital discharge injury survey from 2005 to 2008. Analysis method was used frequency and chi-square test, ANOVA, multiple linear regression analysis. In result, distribution of inpatients with pressure ulcer by sex were 52.5%(male), 47.5%(female), respectively and aged $65{\geqq}years$ was the highest in age group. LOS of inpatients with nervous system principal disease was the longest. Independent variables which were statistically associated with LOS of inpatients with pressure ulcer were year, sex, insurance type, bed size, operation, principal diagnosis. Therefore, hospital should develop the standardized strategy and guidelines to manage pressure ulcer inpatients efficiently and apply it into the medical information system.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.22-32
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• 2016

As the number of aged population rapidly goes up, the cases of stroke and the related medical expenses continuously increase. The purpose of this study is to investigate the mortality of stroke patients based on CCI(Charlson Comorbidity Index) by utilizing the Korea National Hospital Discharge Injury Survey, analyzing the factors associated with the mortality of stroke patients. We analyzed 21,494 cases which are classified as the death of strokes aged over 20 years by using the Korea National Hospital Discharge Injury Survey between the year 2005 and 2010. In order to find out the mortality based on CCI and status of comorbidity, we used the technical statistics. We performed a logistic regression analysis to examine the reasons for the mortality of the strokes. We found that the independent variables for the influence of the mortality of strokes include age, type of insurance, residence urban size, size of hospital beds, the location of hospital, admission route, physical therapy, brain surgery, type of stroke, and CCI. This indicates that the effective monitoring on the age, types of stroke, comorbidity is needed. In addition to this, more medical support toward medicaid patients are needed, too. We believe that these results will be used positively for the evaluation of the stroke patients, providing the basic materials for the further research on the establishment of the health-related policy.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.459-467
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• 2013

The purpose of this study was to identify the differences in medical care utilization by regional economic status using the National Hospital Discharge Patients Injury Survey. In order to determine economic status of each region, 234 cities and counties were categorized 5 quintiles according to their financial self-reliance ratio. The main results are as follows. First, low economic region has high age-standardized admission rate and standardized mortality rate. Second, of 16 major diseases, cerebrovascular and heart diseases, lung cancer, and stomach cancer reported greater changes in standardized mortality rate by regional economic status. Third, the rate of admission via emergency room in low economic region is higher than that of high economic region. Lastly, in the major illnesses, lower economic status led to an increase in average length of stay. Therefore, In order to bridge the gap in health inequality across regions, a regional medical policy tailored for each region and characteristics of the economic status should be established.

• Journal of Digital Convergence
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• v.11 no.6
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• pp.221-233
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• 2013

This study aims to develop the severity-adjusted length of stay(LOS) model for acute stroke patients using data from the hospital discharge survey and propose management of length of stay(LOS) for acute stroke patients and using for Hospital management. The dataset was taken from 23,134 database of the hospital discharge survey from 2004 to 2009. The severity-adjusted LOS model for the acute stroke patients was developed by data mining analysis. From decision making tree model, the main reasons for LOS of acute stroke patients were acute stroke type. The difference between severity-adjusted LOS from the decision making tree model and real LOS was compared and it was confirmed that insurance type and bed number of hospital, location of hospital were statistically associated with LOS. And to conclude, hospitals should manage the LOS of acute stroke patients applying it into the medical information system.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.393-400
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• 2011

In a large scale survey, cluster sampling design in which a set of observation units called clusters are selected is often used to satisfy practical restrictions on time and cost. Especially, a two stage cluster sampling design is preferred when a strong intra-class correlation exists among observation units. The sample Primary Sampling Unit(PSU) and Secondary Sampling Unit(SSU) size for a two stage cluster sample is determined by the survey cost and precision of the estimator calculated. For this study, we derive the optimal sample PSU and SSU size when the population SSU size across the PSU are di erent by extending the result obtained under the assumption that all PSU have the same number of SSU. The results on the sample size are then applied to the $4^{th}$ Korea Hospital Discharge results and is compared to the conventional method. We also propose the optimal sample SSU (discharged patients) size for the $7^{th}$ Korea Hospital Discharge Survey.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.747-754
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• 2012

The purpose of this study was to compare inter-regional accident modes using the National Hospital Discharge Patient Injury Survey. In order to determine economic status of each region, 234 cities and counties were categorized as 5 groups according to their financial self-reliance ratio. The main results are as follows. First, transport accidents had increased by the age group of 25 to 44 but decreased thereafter. Second, the frequency of car accidents was the highest among several types of transport accidents. Most common site of transport accidents was roads and highways. Third, there was significant difference in the modes of transport accident among regions. Fourth, emergency admission rate was quite different according to regional groups but it was no significant difference by economic status. Lastly, there was significant difference in injury patterns by region groups. In regions which were high economic status, there were relatively less serious injury patterns such as sprain, strain, dislocation while regions which were in low economic status had experienced serious injury including fracture, stab wound, and open fracture. We could find the difference in accident modes by regional economic status. Therefore, health authority should consider different accident prevention strategies by regional groups.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.196-205
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• 2016

The purpose of this study is to identify factors influencing treatment result in patients with Tuberculosis by patient characteristic, admission and disease characteristic, and hospital characteristic from 2006 to 2012. Survey data was using Korean national hospital discharge in-depth survey data produced by KCDC(Korea Center for Disease Control and Prevention). Study subjects were 8,305 inpatients with TB(A15.0~A19.9) and analyzed frequency, chi-square test, and logistic regression by using SPSS 20(Statistical Package for the Science). The results of this study show that influencing factors of treatment result were ages (20-39, 40-64, and over 65 years), type of insurance(medical aid), disease code (A16, A17, A18, A19), LOS (31-90, and 91-180 days), beds of hospital (300-499, 500-999, over 1,000 beds) and hospital district (non-metropolitan). These findings implied that it is necessary to support successful prevention and management for high risk TB groups and to build middle and long-term policies as well as short -term policy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2293-2303
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• 2013

Objective: This study aims to determine whether national patient safety indicators (PSIs) can be calculated. Methods: Using PSI criteria from Organization for Economic Co-Operation and Development (OECD) Health Technical Papers 19 based on the Agency for Healthcare Research and Quality (AHRQ), PSIs were identified in the Korean National Hospital Discharge In-depth Injury Survey (KNHDIIS) database for 875,622 inpatient admissions between 2004 and 2008. Logistic regression was used to estimate factors of variations for PSIs. Results: From 2004 to 2008, 3,084 PSI events of 8 PSIs occurred for over 80 thousands discharges. Rates per 1,000 events for decubitus ulcer (PSI3, 4.88), foreign body left during procedure (PSI5, 0.05), postoperative sepsis (PSI13, 1.32), birth trauma-injury to neonate (PSI17, 7.92) and obstetric trauma-vaginal delivery (PSI18, 32.81) are all identified between ranges from maximum to minimum of OECD rates, respectively. However, rates per 1,000 events for selected infections due to medical care (PSI7, 0.22), postoperative pulmonary embolism or deep vein thrombosis (PSI12, 0.90) and accidental puncture or laceration (PSI15, 0.71) are below the minimum of OECD range. 7 PSIs except PSI 18 showed statistically significant relationship with number of secondary diagnoses. When adjusting patient characteristics, there are statistically significant different rates according to bed size or location of hospitals. Conclusion: This is the first empirical study to identify nationally number of adverse events and PSIs using administrative database. While many factors influencing these results such as quality of data, clinical data and so on are remain, the results indicate opportunities for estimate national statistics for patient safety. Furthermore outcome research such as mortality related to adverse events is needed based on results of this study.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.413-422
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• 2012

In this study, we developed the severity-adjusted length of stay (LOS) model for acute myocardial infarction patients using data from the hospital discharge survey and proposed management of medical quality and development of policy. The dataset was taken from 2,309 database of the hospital discharge survey from 2004 to 2006. The severity-adjusted LOS model for the acute myocardial infarction (AMI) patients was developed by data mining analysis. From decision making tree model, the main reasons for LOS of AMI patients were CABG and comorbidity. The difference between severity-adjusted LOS from the ensemble model and real LOS was compared and it was confirmed that insurance type and location of hospital were statistically associated with LOS. And to conclude, hospitals should develop the severity-adjusted LOS model for frequent diseases to manage LOS variations efficiently and apply it into the medical information system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.4910-4918
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• 2013

This study aims to design a Severity-Adjusted LOS(Length of Stay) Model in order to efficiently manage LOS of AMI(Acute Myocardial Infarction) patients. We designed a Severity-Adjusted LOS Model with using data-mining methods(multiple regression analysis, decision trees, and neural network) which covered 6,074 AMI patients who showed the diagnosis of I21 from 2004-2009 Korean National Hospital Discharge in-depth Injury Survey. A decision tree model was chosen for the final model that produced superior results. This study discovered that the execution of CABG, status at discharge(alive or dead), comorbidity index, etc. were major factors affecting a Sevirity-Adjustment of LOS of AMI patients. The difference between real LOS and adjusted LOS resulted from hospital location and bed size. The efficient management of LOS of AMI patients requires that we need to perform various activities after identifying differentiating factors. These factors can be specified by applying each hospital's data into this newly designed Severity-Adjusted LOS Model.