• 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.

• 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.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.

• Health Policy and Management
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• v.5 no.2
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• pp.18-34
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• 1995

To clarify the relationship between the medical supply(medical persons and goods) and the use of bed, the author has made comparison among OECD 24 countries. Per Capita Bed-days can be divided into Average Length of Stay and Admission Rate, and these three variables were regressed upon both In-patient Care Beds of all medical institutions including acute somatic, psychiatric, special, nursing homes and other long-term care and Share of Total Health Employment in Total Employment. The result of regression analysis shows a statistically significant positive relationship between In-patient Care Beds and Average Length of Stay, and negative relationship between Share of Total Health Employment and Admission Rate. In addition to Ordinary Least Square(OLS) estimation, amended Bounded Influence Estimation(BIE) was also made to adjust the influence of outliers. Japan shows a very large number of In-patient Care Beds and a very low Share of Total Health Employment, and this medical situation is judged to have close relation to her long Average Length of Stay and low Admission Rate.

• 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 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.

• Journal of Preventive Medicine and Public Health
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• v.16 no.1
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• pp.157-162
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• 1983

In order to determine the factors affecting the length of stay by pay status, a total of 961 in-patients medical records with appendectomy. cholecystectomy and Cesarean section discharged from the January 1979 to December 1981 from the University hospital were reviewed. Average length of stay showed no statistically significant difference by year between the insured and the non-insured patients, however multiple diagnoses and surgical complication were significantly different from single diagnosis and non-complicated cases. Surgical complication explained the length of stay mostly, and physician in discharge, multiple diagnoses, and accommodation in order for insured patients. Surgical complication, admission route, physician in charge and age in order explained the length of stay for non-insured patients.

• 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.

• 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.

• Korea Journal of Hospital Management
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• v.15 no.2
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• pp.15-26
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• 2010

Stroke is a high-risk disease. The future of the medical environment is that the proportion of elderly population is increasing, the average life expectancy is being increased, while the fatal rate of stroke will be low. These situation will due to the financial burden on medical insurance. The most important factor that affects on the medical costs of stroke patients is the length of stay. In this study the mean length of hospital for stroke stay was 21.81days(37.97days for intracerebral hemorrhage, 18.89 days for cerebral infarction). The payment per case of stroke was 6.86 million won(12.6 million won for intracerebral hemorrhage, 5.72 million won for cerebral infarction). The payment per case of intracerebral hemorrhage was 2.2 times more than that of cerebral infarction. The payment in the day of hospitalization was the highest and until the second day medical costs was high. After the third day medical costs tended to decline, after that seemed to show an almost constant level. The length of hospital stay was found to be the most important determinant of inpatient charges for stroke. Accordingly rational management of the length of stay will be beneficial to health care consumers, providers, states.