• Korea Journal of Hospital Management
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• v.11 no.3
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• pp.73-93
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• 2006

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.

• Journal of Korean Medicine Rehabilitation
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• v.24 no.1
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• pp.65-76
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• 2014

Objectives The purpose of this study is to investigate the corelation between traffic accident severity and treatment period and cost by traffic accident. Methods Outpatients who visited Jaseng Korean medicine hospital traffic accident clinic were investigated by hospital computer system about period and cost of treatment. And we requested for repair cost of car, a sort of car groups and agreement date with car insurance company to insurance company. Therefore we could analysis statistical correlation of traffic accident severity (repair cost of car) with period of treatment, cost of treatment, number of treatment in same sort of car groups. For statistics, we used SPSS version 18.0 for windows. Results A significant positive correlation was found between traffic accident severity (repair cost of car) with repair cost of car, cost of treatment and number of treatment in semi-midsize car, midsize car group. But, any significant correlation wasn't found between traffic accident severity (repair cost of car) with repair cost of car, cost of treatment and number of treatment in small car, full-sized car group. In SUV (sport utility vehicle) car group some significant correlation was found, but it isn't between traffic accident severity (repair cost of car) with repair cost of car, cost of treatment and number of treatment. Conclusions It was found that traffic accident severity (repair cost of car) had an effect on cost of car, cost of treatment and number of treatment by statistical analysis. But, it was also suggested strongly that other factors like a cost of car and ages had an effect on them.

• Health Policy and Management
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• v.9 no.4
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• pp.1-14
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• 1999

The purpose of this study was to estimate the magnitude of patient's actual cost-sharing for hospital services in the National Health Insurance which has been estimated with only a few hospitals or limited number of patients. Also we aimed at analysis of factors influencing the magnitude. Sources of analyzed data were two databases. 1997 medical benefits record of the National Federation of Medical Insurance and 1997 Statistics for Hospital Management from the Korea Institute of Health Services Management(KIHM). We merged two databases and related records for 224 hospitals. based on the identification details of each hospital. The average percent of patients' cost-sharing was 51.7% of total hospital revenues from the insurance. with 40.3% of revenue in inpatient and 67.4% in outpatient. respectively. The contributing hospital factors to the magnitude of cost-sharing were size of hospitals. teaching status. location. number of employed physicians. etc. Larger and university hospital. urban location. and with more physicians were positively correlated with higher level of cost-sharing. Additionally, the higher the expenses of inpatient's treatment was, the higher the size of patient's cost-sharing was. These findings suggest that present level of patients' cost-sharing is quitely high and it is urgent to reduce the patient's cost-sharing to the reasonable level. It would be necessary to extend the coverage of insurance benefits and to develop policies focusing on larger hospitals and inpatient services.

• Korea Journal of Hospital Management
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• v.12 no.3
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• pp.20-46
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• 2007

Given the pressures to promote the efficient utilization of medical resources, hospitals have developed cost accounting systems in several countries. This study discusses the recent development and problems of hospital cost accounting practices in three countries: UK, US, and Japan. first, we discuss a cost accounting structure and detailed pictures of costing practices. Second, problems of current systems arc reviewed and then possible remedies are discussed. Third, we provide implications for implementing the systems(especially ABC). finally, we assert that infrastructure(hospital information systems, database, etc.) must be established and the target level of costing has to be considered before organization-wide application.

• Environmental and Resource Economics Review
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• v.11 no.4
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• pp.659-687
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• 2002

This study used a discrete choice model to investigate an association between air pollution and hospital visits for acute respiratory symptoms with the national health interview survey conducted in 1998 in South Korea. The results showed that $NO_2$ and TSP were significantly related to hospital visits in a single-pollutant model, but when they were simultaneously considered, only $NO_2$ remained significant. It was estimated as $NO_2$ level increased by 10%(0.0027ppm) from 0.027ppm (the mean $NO_2$ level), hospital visits increase by 0.176%. This study also measured respondent's out-of-pocket expense and the time cost for commuting and waiting for the visit. We found that on the average, out-of-pocket expense is 5,600 won per hospital visit, but the total cost per hospital visit is measured at 33,440 won with time cost of commuting and waiting at 27,840 won. Time cost was over 63.6~83.3% of the total cost per hospital visit.

• Korea Journal of Hospital Management
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• v.19 no.1
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• pp.32-42
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• 2014

It is necessary to calculate prime cost of medical services accurately in order to evaluate the adequacy of medical fee. This paper aims to identify cost analysts' perception on prime cost of medical services and needs in establishing a cost accounting system in hospitals, proposing future directions and guidelines for the calculation of medical fee. A self-administered questionnaire and telephone survey on operation of a hospital cost-accounting system was conducted in November, 2012, among cost analysts currently working in the hospitals and hospital administrators planning to implement the hospital cost-accounting system. Our study shows that most of the cost analysts were aware of the importance of calculating prime cost and responded that collection of the prime cost data from government is necessary although they are less likely to provide the data in the future concerning the risk of data misuse and data security. They also responded that lack of budget allocation and excessive workload were the main reasons for not estimating the prime cost and operating cost management information system. Results show that hospital cost analysts considered the data accuracy is the most critical factor in calculating prime costs of medical services. However, there was no investment budget allocated in some hospitals or limited to less than 100 million, indicating that hospitals are reluctant to invest on implementing the cost accounting system. Respondents stated the organization that collects the prime cost of medical services among hospitals should display strong analytical capabilities, ensure data security, and maintain independence, which is most demanded. There are 57 hospitals that calculated the prime cost of medical services for 2012 by each medical department and 20 hospitals that calculated the prime cost by fee-for-services, aiming to establish a cost accounting system. Our results indicate that hospitals should voluntarily provide the accurate prime cost for medical services in order to properly evaluate the adequacy of medical fee. Consequently, it is critical to establish an independent organization to collect and appraise the data. It is also recommended that government should implement various policies to encourage hospitals to participate in the data collection to achieve the data accuracy and representativeness.

• Korea Journal of Hospital Management
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• v.9 no.1
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• pp.66-94
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• 2004

The objective of this study is to examine how to maximize the efficiency of hospital management by minimizing the unit cost of hospital operation. For this purpose, this paper proposes to develop a model of the profit maximization based on the cost minimization dictum using the statistical tools of arriving at the maximum likelihood values. The preliminary survey data are collected from the annual statistics and their analyses published by Korea Health Industry Development Institute and Korean Hospital Association. The maximum likelihood value statistical analyses are conducted from the information on the cost (function) of each of 36 hospitals selected by the random stratified sampling method according to the size and location (urban or rural) of hospitals. We believe that, although the size of sample is relatively small, because of the sampling method used and the high response rate, the power of estimation of the results of the statistical analyses of the sample hospitals is acceptable. The conceptual framework of analyses is adopted from the various models of the determinants of hospital costs used by the previous studies. According to this framework, the study postulates that the unit cost of hospital operation is determined by the size, scope of service, technology (production function) as measured by capacity utilization, labor capital ratio and labor input-mix variables, and by exogeneous variables. The variables to represent the above cost determinants are selected by using the step-wise regression so that only the statistically significant variables may be utilized in analyzing how these variables impact on the hospital unit cost. The results of the analyses show that the models of hospital cost determinants adopted are well chosen. The various models analyzed have the (goodness of fit) overall determination (R2) which all turned out to be significant, regardless of the variables put in to represent the cost determinants. Specifically, the size and scope of service, no matter how it is measured, i. e., number of admissions per bed, number of ambulatory visits per bed, adjusted inpatient days and adjusted outpatients, have overall effects of reducing the hospital unit costs as measured by the cost per admission, per inpatient day, or office visit implying the existence of the economy of scale in the hospital operation. Thirdly, the technology used in operating a hospital has turned out to have its ramifications on the hospital unit cost similar to those postulated in the static theory of the firm. For example, the capacity utilization as represented by the inpatient days per employee tuned out to have statistically significant negative impacts on the unit cost of hospital operation, while payroll expenses per inpatient cost has a positive effect. The input-mix of hospital operation, as represented by the ratio of the number of doctor, nurse or medical staff per general employee, supports the known thesis that the specialized manpower costs more than the general employees. The labor/capital ratio as represented by the employees per 100 beds is shown to have a positive effect on the cost as expected. As for the exogeneous variable's impacts on the cost, when this variable is represented by the percent of urban 100 population at the location where the hospital is located, the regression analysis shows that the hospitals located in the urban area have a higher cost than those in the rural area. Finally, the case study of the sample hospitals offers a specific information to hospital administrators about how they share in terms of the cost they are incurring in comparison to other hospitals. For example, if his/her hospital is of small size and located in a city, he/she can compare the various costs of his/her hospital operation with those of other similar hospitals. Therefore, he/she may be able to find the reasons why the cost of his/her hospital operation has a higher or lower cost than other similar hospitals in what factors of the hospital cost determinants.

• Korea Journal of Hospital Management
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• v.8 no.1
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• pp.135-164
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• 2003

The operating room is the major facility that costs the highest investment per unit area in a hospital. It requires commitment of hospital resources such as manpower, equipments and material. The quantity of these resources committed actually differs from one type of operation to another. Because of this, it is not an easy task to allocate the operating cost to individual clinical departments that share the operating room. A practical way to do so may be to collect and add the operating costs incurred by each clinical department and charge the net cost to the account of the corresponding clinical department. It has been customary to allocate the cost of the operating room to the account of each individual department on the basis of the ratio of the number of operations of the department or the total revenue by each operating room. In an attempt to set up more rational cost allocation method than the customary method, this study proposes a new cost allocation method that calls for itemizing the operation cost into its constituent expenses in detail and adding them up for the operating cost incurred by each individual department. For comparison of the new method with the conventional method, the operating room in the main building of hospital A near Seoul is chosen as a study object. It is selected because it is the biggest operating room in hospital A and most of operations in this hospital are conducted in this room. For this study the one-month operation record performed in January 2001 in this operating room is analyzed to allocate the per-month operation cost to six clinical departments that used this operating room; the departments of general surgery, orthopedic surgery, neuro-surgery, dental surgery, urology, and obstetrics & gynecology. In the new method(or method 1), each operation cost is categorized into three major expenses; personnel expense, material expense, and overhead expense and is allocated into the account of the clinical department that used the operating room. The method 1 shows that, among the total one-month operating cost of 814,054 thousand wons in this hospital, 163,714 thousand won is allocated to GS, 335,084 thousand won to as, 202,772 thousand won to NS, 42,265 thousand won to uno, 33,423 thousand won to OB/GY, and 36.796 thousand won to DS. The allocation of the operating cost to six departments by the new method is quite different from that by the conventional method. According to one conventional allocation method based on the ratio of the number of operations of a department to the total number of operations in the operating room(method 2 hereafter), 329,692 thousand won are allocated to GS, 262,125 thousand won to as, 87,104 thousand won to NS, 59,426 thousand won to URO, 51.285 thousand won to OB/GY, and 24,422 thousand won to DS. According to the other conventional allocation method based on the ratio of the revenue of a department(method 3 hereafter), 148,158 thousand won are allocated to GS, 272,708 thousand won to as, 268.638 thousand won to NS, 45,587 thousand won to uno, 51.285 thousand won to OB/GY, and 27.678 thousand won to DS. As can be noted from these results, the cost allocation to six departments by method 1 is strikingly different from those by method 2 and method 3. The operating cost allocated to GS by method 2 is about twice by method 1. Method 3 makes allocations of the operating cost to individual departments very similarly as method 1. However, there are still discrepancies between the two methods. In particular the cost allocations to OB/GY by the two methods have roughly 53.4% discrepancy. The conventional methods 2 and 3 fail to take into account properly the fact that the average time spent for the operation is different and dependent on the clinical department, whether or not to use expensive clinical material dictate the operating cost, and there is difference between the official operating cost and the actual operating cost. This is why the conventional methods turn out to be inappropriate as the operating cost allocation methods. In conclusion, the new method here may be laborious and cause a complexity in bookkeeping because it requires detailed bookkeeping of the operation cost by its constituent expenses and also by individual clinical department, treating each department as an independent accounting unit. But the method is worth adopting because it will allow the concerned hospital to estimate the operating cost as accurately as practicable. The cost data used in this study such as personnel expense, material cost, overhead cost may not be correct ones. Therefore, the operating cost estimated in the main text may not be the same as the actual cost. Also, the study is focused on the case of only hospital A, which is hardly claimed to represent the hospitals across the nation. In spite of these deficiencies, this study is noteworthy from the standpoint that it proposes a practical allocation method of the operating cost to each individual clinical department.

• Health Policy and Management
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• v.10 no.4
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• pp.116-143
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• 2000

Considerable attention has been devoted in the accounting literature to identify the factors that cause or drive the costs of overhead activities. This paper extends recent cost driver research to the health care provider. In various case studies, it has been suggested that overhead costs are driven by volume and complexity variables. This paper investigates the significance of these variables in determining hospital overhead costs, how they are structurally related and how the cost impacts of these variables can be estimated in practice. This paper analyzes the determinants of hospital costs using the sample of South Korea hospitals for seven year during the period 1952－1997. The paper focuses on the extent to which hospital overhead costs depend on complexity, efficiency in addition to depending on more conventional volume based measures of hospital activity. The results of regression analysis suggest that volume and complexity factors positively and significantly affect overhead costs in the hospital industry. The results show that the complexity-related cost drivers strongly affected on the overhead costs in tile health care provider industry more than manufacturing industry which is mainly affected by volume-related cost drivers. That means each Industry may have different cost structures. Therefore it Is Important to find their proper cost structures and cost drivers and use them. Futhermore identification of overhead or indirect cost drivers is likely to be particularly useful in heath care. The identification of cost drivers can be of benefit to all health care stakeholders because these facilitates more efficient management of the national resources devoted to health care. While this study has documented that the level of service complexity is a significant determinant of hospital overhead costs, caution should be exercised in interpreting this as supportive of the cost accounting procedures associated with ABC. It is an open question whether even a well-designed ABC system will provide suitable proxies for marginal costs for decision making purposes.

• The Korean Journal of Health Service Management
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• v.5 no.1
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• pp.87-99
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• 2011

The aim of the research is to figure out how the perception and the attitude of hospital staff have effect on cost management behavior, to check the mediation effect in the relationship between cost attitude and cost management behavior, and to provide some basic data of efficient cost management means for hospital staff. The major results of research can be summed up as following. Subordinate factors of cost perception such as conviction, information, and thought were all revealed as meaningful effect ones on cost attitude, but they didn't have meaningful effect on cost management behavior. However, if we check the final results of direct effect, indirect effect, and total effect in its variants, we can understand that cost perception have indirect effect on cost management behavior via cost attitude. Cost attitude was revealed as the greatest variant having direct effect on cost management behavior. As a conclusion, it seems that the correct cost perception can make positive cost attitude, by which desirable cost management behavior can be induced. Therefore, as the correct cost perception can make positive attitude, it is necessary to construct effective system to provide useful cost information for staff at anytime and at any place continually on organization aspect. It is important to get correct cost perception for the positive attitude of staff. Nevertheless, if the positive attitude would not be formed, it is necessary to search for the ways for personal motivation, for the management behavior cannot emerge positively.