• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.509-512
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• 2010

본 논문에서는 지방환자의 서울진료의 추이와 치료결과를 살펴보기 위해 2005년, 2008년의 퇴원환자 조사 자료를 재원일수를 이용하여 분석하였다. 그 결과 2005년 퇴원환자 333,280명과 2008년 퇴원환자 419,873명의 성별, 연령별, 주진단 분포는 유사한 것으로 나타났으며 치료결과 재원일수는 2005년에 30일 이상이 7.2%, 20~29일이 5.9%인데 비해 2008년은 30일이상이 6.2%, 20~29일 6.0%로 나타나 재원일수는 절감되었다. 전체퇴원환자의 재원일수에 영향을 끼치는 요인에 대해 회귀분석 결과 연도, 성, 보험유형, 의료기관유형, 입원경로, 내원 경유, 주진단, 거주지의 효과를 통제한 후 지방환자의 진료지역에 따른 재원일수를 살펴본 결과 서울이 가장 낮은 것으로 나타났다. 또한 암환자의 재원일수에 영향을 끼치는 요인에 대해서도 연도, 성, 보험유형, 의료기관유형, 입원경로, 내원 경우, 주진단, 거주지의 효과를 통제한 후 지방환자의 진료지역에 따른 재원일수를 살펴본 결과 서울이 가장 낮은 것으로 나타났다. 즉, 지방환가 거주지에서 진료를 받는 것에 비해 서울에서 진료를 받는 것이 치료결과가 짧았다. 이는 타 지역 진료의 간접의료비 영향으로 서울지역에서 조기 퇴원하여 거주지에서 진료하였거나 서울 진료자가 중증도가 낮은 환자가 많아 재원일수가 낮을 수 있다는 것도 배제 할 수 없다. 이에 대한 중증도 보정 후 서울 진료환자의 재원일수가 낮은 요인을 분석하는 추후 연구가 필요하다.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.273-283
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• 2017

This study aims to develop a convergence optimized LOS(Length of Stay) management system that can provide efficient by predicting LOS on outpatient information for inducing the LOS to manage their own activities. web program has been implemented to comput in real-time predicting LOS by using the predicted LOS model of outpatient information. The predict model was derived management targets of long term predicted patient group and intensive care patient group. The optimized LOS(Length of Stay) management system was confirmed efficient for optimizing management of LOS that can provide by the long-term predicting alarm and over LOS alarm service for long term predicted patient group and intensive care patient group. Therefore the trial operating policy alternative on extension of predicted LOS is needed to utilized convergence optimizing system on LOS.

• 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.

• 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.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.314-323
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• 2013

This study analyzed the relationship between the level of hospital caseloads and length of stay for the delivery patients. The differences of hospital caseloads were measured by the Internal Herfindahl Index, which measured the concentration of delivery patient in a hospital. And the structure variables of hospitals such as the number of bed, the number of treatment, and the number of doctors and nurses per 100 beds were included as control variables. And average length of stay of delivery patients was used as the dependent variable. Concentration status of delivery patients was measured in two models: (1) first model represents the concentration level of delivery patient in all hospital patients, (2) second model represents the concentration level of delivery patient in all obstetrics and gynecology patients. In regression analysis, patient concentration index was not statistically significant in explaining the variation of average length of stay in two models. But the number of delivery patients and number of beds were statistically significant. The number of delivery patient variable showed negative regression coefficient with average length of stay and the number of beds showed positive coefficient with average length of stay. This study result indicated that the volume of delivery patients in a hospital will play a significant role in reducing the length of stay of delivery patients. Patient volume could contribute in improving the efficiency of patient care in a hospital.

• The Journal of the Korea Contents Association
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• v.11 no.9
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• pp.372-383
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• 2011

Our study was carried out to develop the severity-adjustment model for length of stay in hospital for percutaneous coronary interventions so that we would analysis the factors on the variation in length of stay(LOS). The subjects were 1,011 percutaneous coronary interventions inpatients of the Korean National Hospital Discharge In-depth Injury Survey 2004-2006 data. The data were analyzed using t-test and ANOVA and the severity-adjustment model was developed using data mining technique. After yielding the standardized value of the difference between crude and expected length of stay, we analysed the variation of length of stay for percutaneous coronary interventions. There was variation of LOS in regional differences, size of sickbed and insurance type. The variation of length of stay controlling the case mix or severity of illness can be explained the factors of provider. This supply factors in LOS variations should be more studied for individual practice style or patient management practices and healthcare resources or environment. We expect that the severity-adjustment model using administrative databases should be more adapted in other diseases in practical.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.380-389
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• 2012

This study aims to argue fundamental issues on factors associated with revenues of hand injury patients to effectively manage hospitals specialized in hand injuries. The study employes 2,461 patients who entered S hospital from 2008 to 2010 with hand injuries. The followings are the results of the study. First, there is significant difference among occurrence of hand injuries with regard to demographics of patients. That is, it is likely to have longer average length of stay(ALOS) of male over female, of the elderly over infants and toddlers, and vice versa on average daily patient revenues. Also, compared to patients with traffic and labor insurance, patients with health insurance is likely to stay longer at lower daily cost. Fifth, demographics and incidence of hand injuries were significantly associated with average length of stay(ALOS) and average daily patient revenues. That is, male over female, age over 60 over any other age categories, patients with traffic and labor insurances over one with health insurance, cases with laceration, avulsion and bone transplantation over any other types of hand injury patients were factors significantly related to ALOS and average daily patient revenues. In sum, it is needed to focus on education and campaign to raise attentions on preventing various hand injuries. Also, managers at hospitals specialized in hand injuries should pay attention on issues such as reducing ALOS to run the organization effectively.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.487-497
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• 2021

The purpose of this study is to identify factors affecting length of stay(LOS) and death in tuberculosis(TB) patients by disease type, patient characteristic, admission and disease characteristic, and hospital characteristic from 2008 to 2017. Survey data was using Korean national hospital discharge in-depth survey data produced by Korea Disease Control and Prevention Agency. Study subjects were 10,634 inpatients with TB(A15, A16, A17, A18, A19, U88.0, U88.1, U84.30, U84.31) and analyzed frequency, chi-square test, Fisher's exact test, and logistic regression by using STATA 13.0. As a study result, the type of TB(extrapulmonary TB, multidrug-resistant TB, extensively drug-resistant TB), sex(woman), age(35-49, 50-64, 65-74, 75 years old or older), admission type(outpatient department), CCI(1-2 point, 3 point over), hospital location(metropolitan city) and bed size(300-499, 500-999, over 1000) were significantly influence LOS. Also, the type of TB(extrapulmonary TB, extensively drug-resistant TB), sex(woman), age(50-64, 65-74, 75 years old or older), residence(small town/rural), admission type(outpatient department), CCI(1-2 point, 3 point over), hospital location(provincial) were significantly influence death. In conclusion, the existing tuberculosis management has been patient management with rapid diagnosis and treatment following early detection. But other studies should be carried out for the system that identifies and supports high-risk groups of the long-term length of stay in hospital or high mortality rates as a result of treatment.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2668-2676
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• 2011

In order to analyze the variation in length of stay(LOS) of injury inpatients, we developed severity-adjusted LOS model using Korean National Discharge In-depth Injury Survey data of Center for Disease Control. Appling this model, we calculated predicted values and, after standardizing LOS using the differences from the actual values, analyzed the variation in LOS. Major factors affecting severity-adjusted LOS of injury inpatients were found to be severity, surgery(or no surgery), age, injury mechanism and channel of hospitalization. Result of analysis of the differences between the actual values and predicted values adjusted by decision tree model suggested that there were statistically significant differences by hospital size(number of beds), type of insurance and location of institution. In order to reduce the variation in LOS, efforts should be exerted in developing nationwide treatment protocol, inducing medical institutions to utilize it, and furthermore systematically evaluating it to reduce the variation continually.