Purpose. For more effective hospital management, it analyzes the trend through general characteristics, balance sheet, income statement, and financial ratio analysis, grasps the causes of the problems, and analyzes management of the hospital in order to use the result as baseline data for development of the hospital in the future. Methods. The collected data of 3 years from 2011 to 2013 about 3 tertiary hospitals in metropolitan cities from Alio (provider of public institution information; www.alio.go.kr), Health Insurance Review & Assessment Service (www.hira.or.kr), and the website of the Ministry of Health and Welfare (www.mw.go.kr) were analyzed and general characteristics, balance sheet, income statement, and financial ratio, analysis are used as data. Results & Conclusions. From the result of data analysis from 2011 to 2013, general characteristics, balance sheet, income statement, financial ratio analysis, and pie charts could lead to conclusions as follows. In the result of comprehensive analysis, the 3 tertiary hospitals showed increase of fixed expense due to extension of the buildings and so did the scale of fund and asset. Although medical revenue increased, the margin of increase for medical expense was greater than that of medical revenue, which consequently led to loss. In prediction for the 3 tertiary hospitals based on characteristics so far, it is expected to see improved revenue structure after building extension is completed, but it is necessary to exert management effort to maintain its optimal level by enhancement in stability of management and inventory turnover through management of inventories.
Some of the large sized companies have taken parts in a hospital business with a view or justification to improve medical care regadless of the disadvantageous fee-for-service medical insurance reimbursement system controlled by authorities related. This gradually brought about the financial difficulties to university hospitals as well as general hospitals that were less competitive. In this circumstance the hospital administrators are called for preparing and implementing proper financial strategies by analyzing external circumstances and internal abilities of their hospitals. In this aspect, an effective cost-analysis system in the hospital has been needed for years. K-University hospital developed the practical cost-analysis system and applied it to the hospital management. The effects of cost analysis system are as belows: first, the trend of the monthly revenue per medical specialist from March to July in 1996 showed increasing pattern which is different from that in past years. second, it turned out that the department of functional laboratory in relation to medical treatment enlarged the medical revenue very sharply. third, the intensive care units were being operated at the state of deficit, while other general wards were lucrative.
This study examines the statistical relationship between medical specialists and managerial performance, using regression analysis with the number of medical specialists per 100 beds as the independent variable and the managerial performance index as the dependent variable. Managerial performance index incorporated the number of out-patients per specialist, the number of in-patients per specialist, the volume of revenue per specialist, the number of beds per specialist, and the average length of stay. To compare different groups of hospitals, dummy variable was applied to five groups of hospitals according to size: 100-299 beds, 300-599 beds, 600-899 beds, 900-1199 beds, and more than 1200 beds. The data consisted of 181 general hospitals with more than 100 beds, which included 28 public hospitals, 73 corporate hospitals, 64 university hospitals and 16 private hospitals. Of those, 87 hospitals were located in big cities and 94 hospitals in medium to small cities. This study used hospitals from the Korean Hospital Association, and data published in 2004. The collected data sample was analyzed using the SPSSWIN 12.0 version, and the study hypothesis was tested using regression analysis. The findings of this study are summarized as follows: Hypothesis 1 predicting a negative effect of the number of medical specialists on the number of out-patients per specialist was supported with statistical significance. The analysis of dummy variable showed causality in all the hospital groups larger than the group of 100-299 beds. Hypothesis 2 predicting a negative effect of the number of medical specialists on the number of in-patients per specialist was supported with statistical significance. The analysis of dummy variable showed causality in the hospital group of 300-599 beds when compared to the group of 100-299 beds. Hypothesis 3 predicting a negative effect of the number of medical specialists on the volume of revenue per specialist was not supported. However, the analysis of dummy variable showed that the volume of revenue per specialist increased in the hospital groups of 600-899 beds, 900-1199 beds, and over 1200 beds, when compared to the group of 100-299 beds. Hypothesis 4 predicting a negative effect of the number of medical specialists on the average length of stay was supported with statistical significance. The analysis of dummy variable showed causality in the hospital group of 300-599 beds, when compared to the group of 100-299 beds. Results of this study show that the number of the medical specialists per 100 beds is an important factor in hospital managerial performance. Most hospitals have tried to retain as many medical specialists as possible to keep the number of patients stable, to ensure adequate revenue, and to maintain efficient managerial performance. Especially, the big hospitals with greater number of beds and medical specialists have shown greater revenue per medical specialist despite the smaller number of patients per medical specialist. Findings of this study explains why hospitals in Korea are getting bigger.
Financial stability is the foremost prerequisite for the continuous growth and development of hospitals. The present study aimed at developing a deterministic model using the factors which affect the hospitals profitability and at discovering which factor affected the hospital profitability. The study conducted questionnaire surveys on all general hospitals, with the exception of special hospitals, with over eighty hospital beds. Of the 274 subject hospitals, 136 of them, consituting 49.6% of the whole, were used in the study. The results are as follows. 1. In the deterministic model, outpatient revenue was affected more by the number of physician visits than by outpatient service intensity. Inpatient revenue was found to be affected more by the number of discharged patients than by inpatient service intensity. However, the increase rate of the service intensity not only contributed in stepping up the operating margin by $4{\sim}8%$ in outpatient and $3{\sim}6%$ in inpatient, but it was statistically significant. 2. Among the factors which determined the operating cost within the deterministic model, the number of patients had a greater impact on the operating cost than the resource consumption per patient. 3. The resource consumption per patient were proved to have the greatest effect on the profitability within the probabilistic model. The management cost per adjusted patient, in particular, was proven to have a statistically significant effect on the profitability in all hospitals.
Financial ratios are key indicators of an organization's financial and business conditions. Among various financial indicators, profitability, financial structure, financial activity and liquidity ratios are frequently used and analyzed. Using the structural equation modeling(SEM) technique, this study examines the structural causal relationships among key financial indicators. Data for this study are taken from complete financial statements from 142 hospitals that passed the standardization audit undertaken by the Korean Hospital Association from 1998 to 2001 for the purpose of accrediting teaching hospitals. In order to improve comparability, ratio values are standardized using the Blom's normal distribution. The final model of the SEM has four latent constructs: financial activity(total asset turnover, fixed asset turnover), liquidity(current ratio, quick ratio, collection period), financial structure(total debt to equity, long-term debt to equity, fixed assets to fund balance), and profitability(return on assets, normal profit to total assets, operating margin to gross revenue, normal profit to gross revenue). While examining several model fit indices(Chi-square (df) = 178.661 (40), likelihood ratio=4.467, RMR=.11, GFI=.849, RMSEA=.157), the final SEM we employed shows a relatively good fit. After examining the path coefficient of the constructs, the financial structure of the hospital affects the hospital's profitability in a statistically significant way. A hospital which utilizes its liabilities, more specifically fixed liabilities, and makes a stable investment decision for fixed assets was found to have a higher profitability than other hospitals. Then, the standard path coefficients were examined to directly compare the influence of variables. It was found that there were no statistically significant path coefficients among constructs. When it comes to variables, however, statistically significant relationships were found. between. financial activity and. fixed. asset turnover, and between profitability and normal profit to gross revenue. These results show that the observed variables of fixed asset turnover and normal profit to gross revenue can be used as indicators representing financial activity and profitability.
Purposes: The purposes of this study is analysis of business performance in national university hospitals in Korea. Methodology: Data from 2010 to 2019 were collected from balance sheet, income statement, and annual reports in 11 national university hospitals. The dependant variables are business performance which are operating margin to total assets, operating margin to gross revenue, and net income to gross revenue. The independent variables are the number of bed, hospital location, opening, liquidity, stability, and activity. Findings: In recent years, activity has been shown to have a lot of influence on management performance. National university hospitals increase profitability by using resources as efficiently as possible. The short-term debt and fixed assets have been increased rapidly in recent years. It was found that management performance has been increased through active investment using financial leverage. Practical Implications: Based on these results, this study will be the basic data for efficient management of national university hospitals.
This study is to grasp a trend of profitability classified by characteristics of hospitals and to analyze related factors. Subjects are 145 hospitals which have gotten the standardization audit by Korean Hospital Association during 1998-200l. Profitability was measured in the aspect of operation profit rate with operating margin to gross revenue as proxy variables. Independent variables were classified by general factors (ownership, number of beds, period of establishment, competition), financial factors (liabilities to total assets, current ratio, fixed ratio, total asset turnover, inventories turnover), and factors related to patient treatment (average length of stay, bed occupancy rate, new outpatient ratio, admission ratio of outpatients, number of patients per specialist, personnel costs per adjusted inpatient, administrative costs per adjusted inpatient). Hierarchical multiple regression analysis model was used in this study. As a result of hierarchical multiple regression analyzation of operating margin to gross revenue, adjustive $R^2$ of general factors was relatively more powerful. The factors had significant effect on operating margin to gross revenue were ownership(+), number of beds(+), competition(+), current ratio(+), fixed ratio(+), total asset turnover(+), personnel costs per adjusted inpatient(-).
This study aims at providing necessary informations for management decision-making to the hospital manager, such as ratios of fixed and variable cost to total operating expense, and variable cost ratio to operating revenues, and determinant factors affecting cost behavior. A study model and related hypotheses were established, data were collected from 41 private university hospitals for the 6years from 1998 to 2003, and regression analyses were performed to test the hypotheses. The results of the analyses and conclusions are as follows; First, labor cost and administration cost within the same number of beds have not only fixed quality of the cost, but variable quality of that. Also, the ratio of the variable costs to operating revenue of the metropolitan was estimated 76.9% and that of other area hospitals was 80.1%. Second, the major factors affecting the increase rate of the operating expense were the increase rates of the number of inpatients, the number of employee, and the number of hospital operating bed. This result implies that maintaining a optimal hospital bed size and efficient operation of the beds are important strategic factors of hospital management.
This study was purposed to find out the difference of the accounting of practical cost between the ABC system and the traditional costing system applied in a hospital, to verified general effect of ABC. Methods: This case study deals with the method of calculation, the cost information that is produced at K hospital in Busan. To examine ABC system and traditional costing system, applying them to the clinical pathology, radiology, physics in K hospital. Results: As a result of costing analysis, it is showed maximum difference of 50% between ABC and traditional cost. compared in revenue center, it occurs the difference of 15% of them. considering the result, it is confirmed that ABC could be used as a means to offer more precise information. therefore, ABC makes possible to produce precise costing information and grasp the driver of cost, and it is possible to reduce cost effectively. Conclusion: ABC provide six benefits: (1) more accurate of service delivered (2) inproved pricing and contracting strategies (3) improved management decision making capability (4) greater ease of determining relevant costs (5) reduced nonvalue added costs.
This study provides an evidence on the determinants of the profitability of university hospital by analyzing university hospital-level data set of hospital performance during the year 2007 (32 university hospitals in total). For the study, a multiple regression model is employed in which profitability index obtained from the DEA computations, operating margin to total asset and gross revenue are used as the dependent variables, and a number of hospital operating characteristics are chosen as the independent variables such as ownership type, location, bed size, period of establishment, bed occupancy rate, admission ratio of outpatients, patients per medical specialist, personnel cost per patient, liabilities to total assets, current ratio, fixed ratio, total asset turnover, medical assistance rate and public indicator. First, the results indicate that the bed occupancy rate and liabilities to total assets are positively and significantly associated with operating margin to total asset. Second, number of beds, the bed occupancy rate and number of patients per medical specialist are positively and significantly associated with operating margin to gross revenue. Third, the bed occupancy rate, number of patients per medical specialist, liabilities to total assets, total asset turnover are positively and significantly associated with profitability index revealed from DEA.
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