• Health Policy and Management
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• v.28 no.2
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• pp.178-185
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• 2018

Background: We investigated association between introduction of the diagnosis-related groups (DRG) system for anal operation and length of stay. Also, we investigated how it is different among hospitals with longer length of stay and among hospitals with shorter length of stay before introduction of the DRG system. Methods: We used data from Health Insurance Review and Assessment which were national health insurance claim data. Total 13,111 cases of anal surgery cases were included which were claimed by hospitals since July 2012 to June 2014. Two-level multivariable regression was conducted to analysis the association between length of stay and characteristics of hospital and patient. Results: Before introducing DRGs, the average length of stay was 5.41 days. After introducing DRGs, average length of stay was decreased to 3.92 days. After introducing DRGs, length of stay has decreased (${\beta}=-1.0450$, p<0.0001) and it was statistically significant. Among hospitals which had short length of stay (shorter than mean of length of stay) before introducing DRGs, effect of introducing DRGs was smaller (${\beta}=-0.4282$, p<0.0001). On contrary, among hospitals which had long length of stay (longer than mean of length of stay) before introducing DRGs, effect of introducing DRGs was bigger (${\beta}=-1.8280$, p<0.0001). Conclusion: Introducing DRGs was more effective to hospitals which had long length of stay before introducing DRGs.

• Clinical and Experimental Pediatrics
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• v.63 no.9
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• pp.361-367
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• 2020

Background: Length of stay is a significant indicator of care effectiveness and hospital performance. Owing to the limited number of healthcare centers and facilities, it is important to optimize length of stay and associated factors. Purpose: The present study aimed to investigate factors associated with neonatal length of stay in the neonatal intensive care unit (NICU) using parametric and semiparametric models and compare model fitness according to Akaike information criterion (AIC) between 2016 and 2018. Methods: This retrospective cohort study reviewed 600 medical records of infants admitted to the NICU of Bandar Abbas Hospital. Samples were identified using census sampling. Factors associated with NICU length of stay were investigated based on semiparametric Cox model and 4 parametric models including Weibull, exponential, log-logistic, and log-normal to determine the best fitted model. The data analysis was conducted using R software. The significance level was set at 0.05. Results: The study findings suggest that breastfeeding, phototherapy, acute renal failure, presence of mechanical ventilation, and availability of central venous catheter were commonly identified as factors associated with NICU length of stay in all 5 models (P<0.05). Parametric models showed better fitness than the Cox model in this study. Conclusion: Breastfeeding and availability of central venous catheter had protective effects against length of stay, whereas phototherapy, acute renal failure, and mechanical ventilation increased length of stay in NICU. Therefore, the identification of factors associated with NICU length of stay can help establish effective interventions aimed at decreasing the length of stay among infants.

• The Journal of Korean Society for School & Community Health Education
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• v.20 no.2
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• pp.69-80
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• 2019

Objectives: In this study, we tried to analyze the factors affecting Length Of Stay for serious patients in Republic of Korea. Methods: The study included 139,172 serious patients in the 2012-2016 discharge details. Using the SPSS 23.0 program, we conducted a rank regression analysis with social and social demographic characteristics as control variables, medical institution characteristics and medical use characteristics as independent variables, and Average Length Of Stay as a dependent variable. Results: Average Length Of Stay for participants was found to be 9.92days. And the location and bed size of medical institutions were not statistically significant, the hospitalization path was more urgent(B=0.43) than the outpatient (p<0.001), and there was no secondary diagnosis(B=0.35). However, Average Length Of Stay was higher (p<0.001) than there was no main surgery(B=0.80). After discharge, Average Length Of Stay for funding(B=0.43) and death(B=0.72) was long (p<0.001). Average Length Of Stay for participants was found to be 9.92days. And the location and the bed size of the medical institution were not statistically significant, and the hospitalization pass had longer Length Of Stay for emergency patients(B=0.43) than for outpatients(p<0.001). There was a longer Length Of Stay(B=0.35) than none was diagnosed. There were longer Length Of Stay(p<0.001) than there was no major surgery(B=0.80). After discharge, the outpatients had longer Average Length Of Stay(B=0.43) and deaths(B=0.72) than those who returned home(p<0.001). Conclusion: As a result of analyzing the factors affecting Average Length Of Stay of the participants, it was confirmed that regardless of the location and bed size of medical institutions, hospitalization route, department diagnosis, main surgery, and whereabouts after discharge. Therefore, appropriate interventions and necessary support must be provided so that efficient Length Of Stay can be managed according to the medical use characteristics of serious patient.

• Health Policy and Management
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• v.19 no.3
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• pp.27-44
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• 2009

The length of stay in emergency departments has been used as a quality indicator to reflect the overall efficiency of emergency care. Identifying characteristics associated with length of stay is critical to monitor overcrowding and improve efficient throughput function of emergency departments. This study examined the level of waiting time for initial assessment by physician and length of stay in emergency departments. Furthermore, we investigated the characteristics of patients' attendance associated with length of stay. An observational study was performed for a sample of 1,526 patients visiting ten nation-wide emergency departments. A structured form was designed to collect information about patients' demographics, route of admission, time and mode of arrival, triage level, cause of attendance, initial assessment time by physician, departure time, and disposition. Multiple regression analysis was performed to determine factors associated with length of stay. The average length of stay was 209.4 minutes (95% confidence interval [CI]=197.1-221.7), with a mean waiting time for initial assessment of 5.9 minutes (95% CI=5.1-6.7). After controlling for emergency department characteristics, increasing age, longer waiting times, attendance due to diseases, higher acuity, multiple diagnoses($\geq$2) and requiring admission or transfer to other health care facilities were positively associated with length of stay in emergency departments. The findings suggest that both patients' characteristics and the flow between emergency departments and parent hospitals should be taken into account in predicting length of stay in emergency departments.

• Quality Improvement in Health Care
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• v.1 no.2
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• pp.34-43
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• 1994

Background: The average hospital stay in most Korean teaching hospitals is longer than that of hospitals in developed countries. The investigation of average hospital stay of teaching hospitals is considered as an important measure to evaluate the effectiveness of hospital management. In this article authors analyzed the relationship of several variables (hospital ownership, number of beds, location of hospitals, number of physician) to length of hospital stay in each clinical department. Methods: The average hospital stay of each clinical department of 184 teaching hospitals was investigated. Authors reviewed the papers of teaching hospitals, that was reported to the Korean Association of Hospitals. Results: The means of hospital stay day of hospitals were not significantly different according to the number of hospital beds and location of hospitals. Only the difference of hospital stay according to ownerships was significant. The length of stay was the highest in public hospitals and the lowest in juridical hospitals. Conclusions: The number of beds and location of hospitals were not associated with the average hospital stay. But ownerships affected the average hospital stay. The national or public hospitals had the longest length of hospital stay. Number of specialists and number of all physicians were closely related to the average hospital stay.

• Health Policy and Management
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• v.31 no.2
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• pp.173-179
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• 2021

Background: In Korea, the length of stay and medical expenses incurred by medical aid patients are increasing at a rate faster than the national health insurance. Therefore, there is a need to create a management strategy for each type of hospitalization to manage the length of stay of medical aid patients. Methods: The study used data from the 2019 National Health Insurance Claims. We analyzed the factors that affect the length of stay for 186,576 medical aid patients who were hospitalized for more than 31 days, with a focus on the type of hospitalization in long-term care hospitals. Results: The study found a significant correlation between gender, age, medical aid type, chronic disease ratio, long-term care hospital patient classification, and hospitalization type variables as factors that affect the length of hospital stay. The analysis of the differences in the length of stay for each type of hospitalization showed that the average length of stay is 291.4 days for type 1, 192.9 days for type 2, and 157.0 days for type 3, and that the difference is significant (p<0.0001). When type 3 was 0, type 1 significantly increased by 99.4 days, and type 2 by 36.6 days (p<0.0001). Conclusion: A model that can comprehensively view factors, such as provider factors and institutional factors, needs to be designed. In addition, to reduce long stays for medical aid patients, a mechanism to establish an early discharge plan should be prepared and concerns about underutilization should be simultaneously addressed.

• Journal of Trauma and Injury
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• v.24 no.2
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• pp.75-81
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• 2011

Purpose: The aim of this study was to analyze the influence of a trauma team's management. Methods: A total of 181 patients with severe trauma were retrospectively divided into two groups. Of these 181 patients, 81 patients without a trauma team admitted between April and October 2008 were assigned to Group 1, and 100 patients with a Trauma team admitted between April and October 2009 were assigned to Group II. We compared general characteristics, the length of stay in the emergency department (ED) and treatment outcomes (24-h packed RBC transfusion, length of intensive care unit (ICU) stay, length of hospital stay, in-hospital mortality, 24-h mortality) between these two groups. Results: The length of stay in the ED was significantly reduced in Group II compared to Group I ($p$=0.025). No significant differences were found in mean arterial pressure, Glasgow Coma Scale, Revised Trauma Score, Injury Severity Score, in-hospital mortality and 24-h mortality between the two groups. However, Group II had a lower amount of 24-h packed RBC transfusion and a shorter length of ICU and hospital stay than Group I, although these differences were not statistically significant. Conclusion: Through the establishment of a trauma team, the length of stay in the ED can be reduced remarkably. Furthermore, the need for 24-h packed RBC transfusions and the length of stay in the ICU and hospital were found to be decreased in patients managed by a trauma team.

• Journal of Trauma and Injury
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• v.30 no.4
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• pp.173-178
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• 2017

Purpose: Most patients with acute low back pain visit emergency room (ER). They mostly need beds, and if their length of stay is longer, it can become difficult to accommodate new patients at the ER. We analyzed the treatment process of patients with back pain and tried to find method for shortening of the length of stay at the ER. Methods: We retrospectively analyzed the medical records of patients with back pain who visited at our ER for one year. Patients were divided into two groups according to their length of stay at ER and were compared the charateristcs of between two groups. Results: A total of 274 patients were included in the study. Eigthy-nine patients (32.5%) were in the group with less than 3 hours and 185 patients (67.5%) were in the other group. In the comparison of the two groups according to the medical departments, the number of patients who were in group with more than 3 hours were 25 (14.0%) in the emergency department, 94 (50.5%) in neurosurgery, 66 (35.5%) in orthopedic surgery. Length of stay was significantly increased in orthopedic surgery and neurosurgery (p=0.014). In addition, the length of stay was longer when computed tomography and magnetic resonance imaging examinations were performed (p=0.000). Regardless of the type of analgesic agent, the median time to the analgesic treatment was shorter in the group with less than 3 hours (p=0.034). Conclusions: In patients with back pain who visit the ER, the emergency medicine doctor will early control the pain and do not unnecessary image examination to reduce a length of stay at the ER.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.1
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• pp.97-101
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• 2012

Objective: With the background of aging population in China and advances in clinical medicine, the amount of operations on old patients increases correspondingly, which imposes increasing challenges to critical care medicine and geriatrics. The study was designed to describe information on the length of ICU stay from a single institution experience of old critically ill gastric cancer patients after surgery and the framework of incorporating data-mining techniques into the prediction. Methods: A retrospective design was adopted to collect the consecutive data about patients aged 60 or over with a gastric cancer diagnosis after surgery in an adult intensive care unit in a medical university hospital in Shenyang, China, from January 2010 to March 2011. Characteristics of patients and the length their ICU stay were gathered for analysis by univariate and multivariate Cox regression to examine the relationship with potential candidate factors. A regression tree was constructed to predict the length of ICU stay and explore the important indicators. Results: Multivariate Cox analysis found that shock and nutrition support need were statistically significant risk factors for prolonged length of ICU stay. Altogether, eight variables entered the regression model, including age, APACHE II score, SOFA score, shock, respiratory system dysfunction, circulation system dysfunction, diabetes and nutrition support need. The regression tree indicated comorbidity of two or more kinds of shock as the most important factor for prolonged length of ICU stay in the studied sample. Conclusions: Comorbidity of two or more kinds of shock is the most important factor of length of ICU stay in the studied sample. Since there are differences of ICU patient characteristics between wards and hospitals, consideration of the data-mining technique should be given by the intensivists as a length of ICU stay prediction tool.

• The Korean Journal of Health Service Management
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• v.8 no.4
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• pp.13-24
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• 2014

This study analyzes the effects of hospital caseload on medical charges and length of stay for inpatients. Hospital caseload, representing the level of concentration of patients, was measured with the Internal Herfindal Index for three diagnosis related group (DRG) codes (appendectomy, operations on anus, and operations on uterus and adnexa). Ordinary least squares regression was used for analysis. Results showed that medical charges per inpatient and average length of stay significantly differed with respect to hospital concentration indices, and that hospital caseload was inversely related to operational performance for appendectomy and operations on uterus and adnexa. The significant negative relationship between concentration index and length of stay may decrease the total medical charges. The results imply that the expansion of the DRG payment system to hospitals will have a negative influence on their gross sales.