1.Application of Survival Analysis to Data from Discharge Abstract of Medical Record Department: Focused on Readniission.
Kwisook CHOI ; Joonhyun HONG ; Jeonghwa LEE
Journal of Korean Society of Medical Informatics 2000;6(4):35-43
Abundant data on patients have been accumulated in hospital since the introduction of the computerized system. Now data mining is required for the survival and growth of hospital. Cases of 19,558 patients were analyzed to investigate factors influencing readmission and repeated admissions, and to estimate probability of readmission with considering covariate effects. Techniques of Kaplan-Meier method, Cox proportional hazards model, and WLW method were applied to the analysis. The conclusions are as follows. The severity of disease, congenital defect and chronicity of disease are influencing readmission or repeated admissions of a patient. Patient s characteristics, such as gender, distance from residence and type of discharge are also related to them. The probability of readmission can be estimated for a patient with variety of conditions for certain period of time. It is suggestive that survival analysis is a good methodology for data mining works on computerized data in hospital. If death certificate data are connected with patients' data, we will be able to get a good data source to medical studies.
Congenital Abnormalities
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Information Storage and Retrieval
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Data Mining
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Death Certificates
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Humans
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Medical Records*
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Proportional Hazards Models
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Survival Analysis*
2.A Study on the Factors Related to the Readmission and Ambulatory Visit in an University Hospital: Using Patient Care Information DB.
Joonhyun HONG ; Kuisook CHOI ; Jeonghwa LEE ; Eunmee LEE
Journal of Korean Society of Medical Informatics 2000;6(4):23-33
To identify the factors related to the readmission and ambulatory visit we analyzed the data in discharge abstract DB(DADB) and outpatient database(OPDB) for 19,983 patients discharged in 1990 from an university hospital(S Hospital) in Seoul. The target patients were limited to those who didn' t have previous episode of discharge in that hospital. Readmission data for 10 years(1990-1999) and ambulatory visit data for 5 years(1995-1999) were analyzed by using x2 test and multiple logistic regression analysis. The main results of this study is as follows. 1) As the number of readmission was increased, readmission rate(RR) was also increased while the average length of stay(ALOS) was decreased. 2) RR was higher in male, transferred from other health care facilities, with consultation, biopsy, ICU care episode during hospitalization. 3) In logistic regression, RR of patients living close to S Hospital hospital was higher than the others wh?n other variables were adjusted. 4) RR of the patients with the diagnosis(Dx) of cancer or cancer related condition was the highest(47.6%), and the consistency rate (CR) of principal Dx group with that of previous admission was also the highest in cancer patients. As the number of readmission was increased the CR of Dx group was also increased. 5) 23.4%(4866) of the target patients had episode of visiting outpatient dispensary(OPD) for between 1995-1999 and the average number of visit was 13.6 times. Patients with the Dx of heart disease showed the highest proportion in ambulatory visit.
Biopsy
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Delivery of Health Care
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Episode of Care
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Heart Diseases
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Hospitalization
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Humans
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Logistic Models
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Male
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Outpatients
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Patient Care*
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Seoul
3.Microbial Contamination of Reusable Suction Container and Cost Analysis of Reusable Suction Container and Disposable Suction Container
Eunyong KU ; Gukgeun LEE ; Miyang JEON ; Jeonghwa CHOI ; Youngok LEE
Journal of Korean Biological Nursing Science 2019;21(2):133-140
PURPOSE: The purpose of this study was to check the degree of residual microbial contamination after disinfection of reusable suction containers, used in an intensive care unit (ICU) and present basic data for efficient use through cost analysis in comparison to disposable suction containers. METHODS: This study was conducted on 32 reusable suction containers used in an ICU on a selected specific day. After disinfection and washing, specimens were collected from the used containers and cultured to check for microbial contamination. Additionally, a comparative narrative study analyzes the cost of using reusable suction containers and disposable suction containers. Data were analyzed with the SPSS WIN 20.0 program using real numbers and percentage χ²-test. RESULTS: As a result of the study, microorganisms were found in all samples where in 30 were gram-positive (62.5%) while 13 were gram-negative (27.1%). Based on level of contamination, microorganisms were less than 10CFU/ml in 18 samples (56.3%); 11–99CFU/ml in six samples (18.8%); and more than 100CFU/ml in eight samples (25%). Cost per day for a reusable suction container was 10,655 + α while cost per day for a disposable suction container was 10,666 won. CONCLUSION: This study found that reusable suction containers, even after disinfection, accounted for factors of potential infection as well as microbial contamination. So, disposable suction containers are superior in cost-effectiveness and highly efficient for use with infected patients.
Costs and Cost Analysis
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Disinfection
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Drainage
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Humans
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Intensive Care Units
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Microbial Interactions
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Suction