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The deductions from reimbursement rates due to short stay are not calculated based on cost accounting data [ 44 , 45 ]. Therefore, other countries such as England do not use lower trim points [ 46 ]. Upper trim points were introduced to lower the risk of the hospital in complicated cases; however, they also suffer from their normative derivation. A non-normative costing-based calculation as in the U. Otherwise, supererogation can lead to a reduced effective reimbursement rate [ 44 ].

The G-DRG system had an average of Inadequate trim point calculation opens up the discussion of a greater DRG differentiation, implying unintended single case reimbursement and less practicability in the grade of differentiation [ 13 ]. That a higher grade of differentiation might not improve welfare has already been shown in econometric models [ 50 ].

Still, consistent outliers can be a sign of the need for further DRG differentiation. Expanding additive components in the DRG calculation, as currently exercised, or outlier-calculation based on costs might partly resolve this issue and increase economic homogeneity [ 32 ]. As the generation of outliers is a necessity to reduce the risk for providers and to create medically and economically homogeneous groups R 2 is about 0. Further, the explained part of the variance is much higher when referring to costs compared with LOS normative derivation [ 34 ].

By using the different modules in the InEK matrix in combination with the date of cost occurrence for outlier calculation, the less accurate normative derivation could be replaced. Thus, the current system has high transparency through normative derivation, but serious flaws concerning the efficiency of the calculation. There is no adjustment in the reimbursement for geographical variations in case-costs — an obvious disadvantage for high-cost regions. Besides, owing to the different composition of DRG costs e. Although a unique base rate calculation and few regional adaptations support competition, they might contradict the care mandate of every German hospital and undermine the security of full health care supply in every region.

Further, case weights are always 2 years old when published. The out-of-date issue affects only relative cost-data case-mix , as base rates are negotiated for every year in every state. But the quality of tariff calculation suffers from out-of-date relative cost-data and especially from insufficient regional cost adaptation. For internal management decisions the base rate can then be adapted to the question that has to be answered.

In the most favorable case, their motivation to take part is image, the fee for every calculated case, or the wish to compare themselves with a nationwide benchmark, and thus the use of the calculation for internal management decisions. In the worst case, the hospital already uses the InEK cost accounting scheme or equivalent systems for internal strategic management decisions and decides on whether the participation might affect its own future reimbursement positively or negatively.

This incentive is especially strong when a hospital knows that it delivers a high percentage of overall cases for the calculation of a DRG, or for hospital chains, where the calculation of one hospital affects the reimbursement of others. Hospitals that are already very efficient have a low incentive to reduce their future reimbursement by delivering beneficial cases.

They have the overall vicious circle nature of the system in mind when deciding about participation. There is an overrepresentation of medium and large hospitals, as small hospitals are possibly not able to achieve the costly, IT and accounting standards required. Concerning ownership, a biased sample can further affect costs, as the incentive to be efficient depends on ownership structure private for-profit, private non-profit, public.

Most of the literature concludes that private for-profit and private non-profit hospitals are less cost efficient than publicly owned hospitals [ 52 — 54 ]. However, the fraction of actual calculation hospitals ca. Although the fraction of publicly owned calculation hospitals has stayed the same since the introduction of the G-DRG system, the private non-profit fraction has increased by ca.

Background

Hospitals that have an incentive to improve efficiency also have an incentive to participate in G-DRG calculation, as this is the only generalized system to support management with cost accounting. As a result, the calculated costs tend to be higher than the true German mean. To compare the profitability of calculating hospitals and non-calculating hospitals in further research might verify the impact of DRG calculation on management quality and system dynamics best, although the mentioned limitations concerning incentives, structure, ownership, and size have to be borne in mind and rethought by policymakers.

Limitations in representativeness and non-adjustment affect benchmarking and strategic reactions on reimbursement rates concerning the elective case-mix. They increase the insecurity of hospital management on published DRG costs. Hospitals react to changes in the case fees catalog by changing their elective case-mix [ 48 ] — a regionally shaped DRG supply situation can develop, and a vicious circle is initiated concerning the motivation for participation.

In contrast, the U. The adoption of adjustment mechanisms as in the PbR system or the U. Assessing the G-DRG cost accounting scheme. Inclusion of all DRG-relevant costs. Increasing participation by a lower costing standard parallel to the currentstandard, to reduce participation bias. This paper assesses the major cost accounting steps in their impact on the goals of G-DRG introduction: improving transparency and efficiency.

Based on the highly differentiated cost module and patient-based calculating structure, the InEK calculation scheme for DRG costs has become a de facto standard for benchmarking in inpatient cost accounting and management, and seems to be developing dynamically. The empirical approach has quantified improvements in G-DRG tariff calculation. The system offers most of the tools necessary to improve efficiency. Transparency and efficiency are reached in the calculations at hospital level, with few improvements possible at an advanced patient-based level, such as time-driven activity-based costing or a consistent full-cost approach.


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However, problematic incentives for participation in the calculation can bias the calculated costs; the G-DRG tariff calculation has a representativeness problem. Although having advanced plausibility checks, tariff calculation methods incorporate the actual cost situation better in other countries. Advancing tariff calculation in hospital financing reforms is a necessity to improve efficiency and transparency in health care management in the long run.

The InEK was able to increase the sample of calculating hospitals, supporting high calculation standards concerning resource allocation at hospital level, but facing methodological problems concerning tariff calculation at national level, such as comparability or inlier calculation issues. As tailored to suit market needs, the standardized cost accounting in the G-DRG system leads to more efficient resource use, more efficient provision of capacity, more transparent and efficient cost-and activity control, and greater competition [ 13 , 60 ].

This combination causes problems in actual hospital financing, although resource allocation in the costing scheme is advanced. Still, the G-DRG costing scheme is the best starting-point for management decisions and for the implementation of further patient-level costing.

With the mentioned limitations, especially concerning tariff calculation at national level, the current G-DRG costing scheme can be considered to be efficient and transparent.

Grundlagen einer Begleitforschung zur Einführung der DRGs aus ethischer Sicht

Coefficient of homogeneity. Diagnosis related groups. German diagnosis related groups. Institute for the Hospital Remuneration System. Length of stay. Payment by results. Patient level information and costing system. Time-driven activity-based costing. Reduction in variance. This article is published under license to BioMed Central Ltd. Review Open Access.

Assessing DRG cost accounting with respect to resource allocation and tariff calculation: the case of Germany. Health Economics Review 2 Abstract The purpose of this paper is to analyze the German diagnosis related groups G-DRG cost accounting scheme by assessing its resource allocation at hospital level and its tariff calculation at national level.

Hospital reimbursement Hospital costs Accounting Resource allocation Prospective payment system Diagnosis related groups. An executive summary is given of the InEK cost accounting scheme at hospital level and on the determination of reimbursement rates at national level, to show the course of action in calculating German inpatient relative prices. To measure improvements since its introduction, and to enable an objective international comparison and classification, an empirical approach is used, measuring cost homogeneity within DRGs.

The three steps of resource allocation at hospital level and the three steps of tariff calculation at national level are assessed, with reference to the two main goals of DRG introduction: improving efficiency and improving transparency [ 14 ]. First, the paper reviews and assesses the three steps in G-DRG resource allocation scheme at hospital level: 1 the groundwork; 2 cost-center accounting; and 3 patient-level costing. The groundwork This section demonstrates the course of action in the G-DRG cost accounting system to allow a detailed assessment of the ability of the scheme to accommodate differentiated resource allocation and precise cost assessment.

Only DRG-relevant costs necessary for DRG-related utilization: medical treatment, care, drugs, cures, therapeutic appliance, and board and lodging remain in the calculation. Non-DRG-relevant cost categories and cost-centers have to be eliminated from the calculation or, in the case of partial relevance, split according to cost-center-specific, DRG-relevant resource utilization.

Thus, an exclusion of costs at the highest possible level of aggregation is claimed full cost approach based on DRG-relevance. The most important non-DRG-relevant costs arise for ambulatory care, research and teaching, psychiatric care, extraordinary expenses, and expenses not relating to the calculation period.

Non DRG relevant cost categories are accruals except for holidays and overtime , most amortizations, private physician liquidation, capital costs, tax, insurance, interest, etc. All cost-centers have to be classified to primary cost-centers service to patient or indirect cost-centers medical and non-medical infrastructure. Figures 2 and 3 explain the groundwork and the subsequent cost-center and patient-level costing. Figure 3 The cost-matrix for every case, Source [ 15 ]. Plausibility checks After case-cost calculation at hospital level, tariff calculation at national level is the second step on the way to understanding the development of G-DRG reimbursement rates and hospital management decisions.

Case costs in cost modules have to relate to case activity, given default band widths. And the relative costs of cost-modules also have to be in default band widths to each other. Participants are informed about errors or possible errors, and have to revise or explain in several rounds. Through this process, the quality of the case costs should be enhanced.

All these checks are performed at single patient-level. Case costs of accepted cases from the hospital are used for calculation if unaccepted cases do not exceed a certain percentage, and if the hospital passes overall conformity checks, analyzing whether the requested calculation methods and processes are met.

Plausibility and conformity checks have become more severe in recent years. This has included shrinking the acceptable band-width in cost modules, more queries that result in more detected calculation errors, and the introduction of the mandatory delivery of additional service data, such as requests for very detailed operating room statistics. The overall percentage of cases with calculation errors allowed decreased.

As a matter of course, the changes in hospital funding affected health care supplies and the different fields of medicine in an unequal manner. Dermatology, in particular, had to deal with the unique situation that the existing in-patient treatment standards did not primarily fit into an Anglo—American-tailored patient classification system.

In central Europe and in Germany, respectively, dermatology has a long tradition as an individual and broad-spectrum field in medicine which has a main focus on in-patient care. Therefore, evaluation studies have been conducted which brought recommendations for a DRG adjustment that partly had been adopted in the further development of the G-DRG system. International experiences give reason to believe that introduction of DRG will probably lead to drifts and shifts in lengths of hospital stay, extent of service providing and quality of care. To report first data-based experiences since the introduction of the G-DRG system, a quantitative analysis including recent in-patient data are shown and discussed in regard to care-related impacts.

Cases were assigned to one of 25 organ-related major diagnostic categories MDC by their principal diagnoses. Nearly two-thirds of in-patient dermatology is represented by MDC 09 skin, subcutaneous tissue and breast. The remaining third is predominantly represented by MDC 23 factors influencing health status and other contacts with health services that covers most of in-patient allergic treatments, MDC 17 haemic and solid neoplasms comprising lymphoma of the skin, MDC 05 circulatory system that contains arterial and venous diseases including therapy of varicose veins and ulcers and MDC 08 musculoskeletal system and connective tissue that covers connective tissue diseases and systemic vasculitis.

PCCL is a measure of the cumulative effect of a patient's complications and comorbidities and it is calculated by arithmetic operations during the grouping process. From up to now, a number of newly recognized factors, such as complex procedures e. The German coding guidelines are legally obliged instructions to ensure appropriate coding and DRG assignment. In the early years, these guidelines have been adapted in accordance with the Hospital Payment Institute to increase DRG homogeneity.

In , for example, coding of systemic cancer therapy was generally modified. In this study, these changes have been appropriately taken into account on algorithms defining clinical patient groups. Data were collected from in-patients regularly admitted during a time period of 4 years —06 and retrieved from the patient data management system. The patient population of each hospital represents a random sample of hospital admissions in national departments of dermatology.

Each data set consists of a patient data block e. Clinical data were coded by attending physicians in compliance with the current national coding standards. Accuracy of coding was ensured by daily checks of physicians specially qualified in coding procedures. Surgical and medical procedures were coded by default according to the national classification of surgeries and procedures OPS , namely version 2. The data sets were retrieved from each department via a standardized data format imported into a specially developed program checking completeness and plausibility.

After processing and checking accuracy, data were regarded as providing high coding quality. In several cases, code mapping was required. The resulting matrix of patient, clinical and G-DRG data were then analysed regarding cost weight tables and case-mix results and several other G-DRG-related parameters on a standard computer system.

However, in addition, the term case-mix may also be taken to refer to both the number and types of patients treated, and the mix of bundles of treatments, procedures and so on provided to patients. Usually the average cost across all G-DRGs is chosen as the reference value, and given a weight of 1.

Case-mix divided by the number of cases will indicate the average severity of a defined group of patients described as the case-mix index CMI. In this study, cost weights were processed from the official national cost weight tables of the annual calculation rounds.

The effective CMI was taken into account including additional per diem payments and discounts for outlier cases in terms of length of hospital stay. We analysed care-related aspects regarding hospital admissions and their underlying diagnoses over time as well as evolutions in LOS, average age and number of cases treated in in-patient settings described above. To evaluate specific aspects of data in more detail, a previously developed clinical model was applied that clusters data into particular treatment groups based on principal diagnosis.

Statistical analysis was conducted using SPSS, release The Mann—Whitney U-test was used to compare differences between both annual time intervals January —December with January —December and initial-end-point time intervals January —March with October —December We analysed data focussing on economic impacts on the G-DRG system level in terms of case-mix index. Care-related aspects were analysed considering frequencies and shifts in dermatological in-patient admissions. Surgical and medical procedures of in-patient care and variables such as LOS in hospital, number of cases and average age have been investigated.

The percentage changes over the years and the distribution of cases in total and by hospital are shown in figure 1. A more detailed analysis at hospital level is provided in figure 2. Results of statistical testing are displayed in table 1. Trends of care-related variables. Data plotted monthly from to Case-mix and CMI are dependent on the results of the nationwide calculation rounds considering present hospital costs.

The present database shows that CMI values tend to increase from the beginning of the year , but subsequently declining on the initial level, however, with inter-hospital differences figures 1 a and 2 a. High-volume groups annual Top DRGs and their relative rates per year concerning number of cases and proportion of case-mix are presented in table 2. Analysis of average age indicates a small increase over time [average age; Patients in Freiburg are 5.

Both the evolutions of LOS and the number of dermatological cases admitted to hospital were analysed over time figures 1 a, 2 c and d. The LOS of a patient is calculated by subtracting the date the patient is admitted from the date of discharge. The number of cases per month was determined via the date of discharge. It is shown that average LOS has been continually reduced hospitalization days; 8. Non-parametric significance testing was not possible for absolute number of cases. These same day cases are being currently not reimbursed by DRG.

Furthermore, over the years, proportions of in-patient same day cases remained relatively stable DRG J68, table 2. A further point of interest is the ratio of surgical versus medical treatments in an in-patient setting. According to the hierarchically organized grouping process for the G-DRG, the coding of a surgical procedure operating room procedure classifies for the surgical partition. Hence, lack of such a procedure classifies for the medical partition. If a special intervention was done, e.

The latter one is actually not relevant for a common dermatological hospital admission. The ratio of surgical versus medical case groups indicates the extent of surgical care in a dermatological in-patient setting. Data in figure 1 a show that the proportion of surgical treatment is rather low mean: Notably, non-operative treatments are dominant mean: Together, the results indicate an initial decline of surgical in-patient activities and increasing medical treatments, however, no long-term changes due to DRG introduction are observable.

To obtain a more detailed view on care-related developments we utilized a clinical model system. The whole data were broken down into 11 case groups figure 1 b. Interestingly, the results show that the number of admitted patients with infectious diseases I , vascular and ulcer diseases VIII and secondary neoplasms declined with high statistical significance for group I. These findings argue that over the observed time period dermatological oncology and some of the conservative dermatological treatments become more and more important in an in-patient setting, whereas some other treatment standards of allergy-related disorders, wound care and infectious diseases appear to be placed in an out-patient setting.

Germany is one of the last countries to adopt a DRG-based per case payment for in-patient care. Still, a high percentage of cost distribution is based on LOS, and especially for medical DRGs conservative therapy , the fraction of directly case-related costs is low compared with operative DRGs. The use of key cost drivers based on old and imprecise point systems, originally developed for physician reimbursement, results in imprecise capacity and resource planning e. Economically sound decisions become limited. The use of the G-DRG system based on InEK calculation as a pricing system and not only as a budgeting instrument is critical against this background [ 8 ].

This allocation method defines nearly all costs as variable and includes time as a key cost driver in a more detailed implementation, such as duration of clinician visits as an example of direct costs or the duration of laboratory tests as an example of indirect costs. The more detailed the calculations are, the more precisely and efficiently management can act; and management decisions become transparent.

Overall, transparency and efficiency in cost accounting have improved since the introduction of the InEK costing scheme. The calculation manual for the calculation of case costs is in its third version now and has increased costing standards greatly since its introduction. Its implementation is enforced by improved and more rigorous plausibility checks. At the hospital level, the learning effect, paired with developing cost accounting software and documentation requirements, has kept up with increased calculation requirements.

After an adaptation phase, the coding of diagnoses and operations and procedures has remained relatively stable [ 13 ]. Hospitals try to adapt treatments to the DRG-system reimbursement by implementing clinical pathways, also oriented on the InEK calculation scheme [ 40 ], promising higher efficiency [ 41 ] and increased transparency through better documentation of the course of action.

The claimed advanced cost accounting methods at hospital level contain risks for tariff calculation. The control for tight band-width in cost modules and further plausibility checks can lead to the exclusion of cases from the calculation, even if costs are calculated correctly. If the costs of a case in a single cost module are not in a target corridor based on previous years, the case might be excluded [ 6 ]. As these corridors are not published, the actual influence and control mechanism of band-widths cannot be defined. Future research is needed to analyze bias caused by band-width control.

Too closely meshed plausibility checks might lead not only to data quality improvements, but also to an undesirable trimming of the calculation on InEK plausibility checks. To achieve high data quality, plausibility checks are both a blessing and a curse. On the one hand, they enforce improved cost accounting, resulting in improved data quality. The efficiency goal of DRG introduction is therefore slightly transgressed, although plausibility checks contribute to efficiency overall.

Transparency is improved, as calculation errors are reported on a patient basis in every round. However, the background on band-width calculation should be reported better and the kind of calculation errors should be made public e. That the calculation of length of stay LOS thresholds is highly important concerning incentives for providers has been shown in detail [ 42 ], also implying that coding issues can be reactions to inlier calculation [ 43 ].

Still, normatively derived upper and lower LOS thresholds imply systematic failures and possibly underfinancing [ 44 , 45 ]. The deductions from reimbursement rates due to short stay are not calculated based on cost accounting data [ 44 , 45 ]. Therefore, other countries such as England do not use lower trim points [ 46 ]. Upper trim points were introduced to lower the risk of the hospital in complicated cases; however, they also suffer from their normative derivation. A non-normative costing-based calculation as in the U.

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Otherwise, supererogation can lead to a reduced effective reimbursement rate [ 44 ]. The G-DRG system had an average of Inadequate trim point calculation opens up the discussion of a greater DRG differentiation, implying unintended single case reimbursement and less practicability in the grade of differentiation [ 13 ]. That a higher grade of differentiation might not improve welfare has already been shown in econometric models [ 50 ].

Still, consistent outliers can be a sign of the need for further DRG differentiation. Expanding additive components in the DRG calculation, as currently exercised, or outlier-calculation based on costs might partly resolve this issue and increase economic homogeneity [ 32 ]. As the generation of outliers is a necessity to reduce the risk for providers and to create medically and economically homogeneous groups R 2 is about 0.

Further, the explained part of the variance is much higher when referring to costs compared with LOS normative derivation [ 34 ]. By using the different modules in the InEK matrix in combination with the date of cost occurrence for outlier calculation, the less accurate normative derivation could be replaced. Thus, the current system has high transparency through normative derivation, but serious flaws concerning the efficiency of the calculation. There is no adjustment in the reimbursement for geographical variations in case-costs — an obvious disadvantage for high-cost regions. Besides, owing to the different composition of DRG costs e.

Although a unique base rate calculation and few regional adaptations support competition, they might contradict the care mandate of every German hospital and undermine the security of full health care supply in every region. Further, case weights are always 2 years old when published. The out-of-date issue affects only relative cost-data case-mix , as base rates are negotiated for every year in every state. But the quality of tariff calculation suffers from out-of-date relative cost-data and especially from insufficient regional cost adaptation.

For internal management decisions the base rate can then be adapted to the question that has to be answered. In the most favorable case, their motivation to take part is image, the fee for every calculated case, or the wish to compare themselves with a nationwide benchmark, and thus the use of the calculation for internal management decisions.

In the worst case, the hospital already uses the InEK cost accounting scheme or equivalent systems for internal strategic management decisions and decides on whether the participation might affect its own future reimbursement positively or negatively. This incentive is especially strong when a hospital knows that it delivers a high percentage of overall cases for the calculation of a DRG, or for hospital chains, where the calculation of one hospital affects the reimbursement of others.

Hospitals that are already very efficient have a low incentive to reduce their future reimbursement by delivering beneficial cases. They have the overall vicious circle nature of the system in mind when deciding about participation. There is an overrepresentation of medium and large hospitals, as small hospitals are possibly not able to achieve the costly, IT and accounting standards required. Concerning ownership, a biased sample can further affect costs, as the incentive to be efficient depends on ownership structure private for-profit, private non-profit, public.

Most of the literature concludes that private for-profit and private non-profit hospitals are less cost efficient than publicly owned hospitals [ 52 - 54 ]. However, the fraction of actual calculation hospitals ca. Although the fraction of publicly owned calculation hospitals has stayed the same since the introduction of the G-DRG system, the private non-profit fraction has increased by ca.

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Hospitals that have an incentive to improve efficiency also have an incentive to participate in G-DRG calculation, as this is the only generalized system to support management with cost accounting. As a result, the calculated costs tend to be higher than the true German mean. To compare the profitability of calculating hospitals and non-calculating hospitals in further research might verify the impact of DRG calculation on management quality and system dynamics best, although the mentioned limitations concerning incentives, structure, ownership, and size have to be borne in mind and rethought by policymakers.

Limitations in representativeness and non-adjustment affect benchmarking and strategic reactions on reimbursement rates concerning the elective case-mix. They increase the insecurity of hospital management on published DRG costs. Hospitals react to changes in the case fees catalog by changing their elective case-mix [ 48 ] — a regionally shaped DRG supply situation can develop, and a vicious circle is initiated concerning the motivation for participation. In contrast, the U. The adoption of adjustment mechanisms as in the PbR system or the U.

The comparability and reproducibility resulting from a standardized G-DRG tariff calculation scheme are of great interest. Transparency and efficiency of tariff calculation are seriously transgressed by the non-representative calculation sample and the motivation to participate. One option to adjust for non-representativeness in the long run is to make the participation of hospitals in InEK cost accounting compulsory. Without reducing the quality of cost accounting by forcing hospitals with less advanced costing abilities to participate, the most important step is to introduce a score that is assigned to the cost modules in the matrix, representing the quality of the allocation methodology for that cost module.

The English patient-level information and costing system PLICS uses such scores to allow for a high participation rate [ 59 ]. To motivate hospitals to reach a high score, the current case fees for cases calculated correctly could depend on score size. Hospitals with less advanced methods can also use key cost driver statistics from hospitals using advanced calculations official relative value units to distribute their costs on cases.

This paper assesses the major cost accounting steps in their impact on the goals of G-DRG introduction: improving transparency and efficiency. Based on the highly differentiated cost module and patient-based calculating structure, the InEK calculation scheme for DRG costs has become a de facto standard for benchmarking in inpatient cost accounting and management, and seems to be developing dynamically.

The empirical approach has quantified improvements in G-DRG tariff calculation. The system offers most of the tools necessary to improve efficiency. Transparency and efficiency are reached in the calculations at hospital level, with few improvements possible at an advanced patient-based level, such as time-driven activity-based costing or a consistent full-cost approach.

However, problematic incentives for participation in the calculation can bias the calculated costs; the G-DRG tariff calculation has a representativeness problem.


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Although having advanced plausibility checks, tariff calculation methods incorporate the actual cost situation better in other countries. Advancing tariff calculation in hospital financing reforms is a necessity to improve efficiency and transparency in health care management in the long run. The InEK was able to increase the sample of calculating hospitals, supporting high calculation standards concerning resource allocation at hospital level, but facing methodological problems concerning tariff calculation at national level, such as comparability or inlier calculation issues.

As tailored to suit market needs, the standardized cost accounting in the G-DRG system leads to more efficient resource use, more efficient provision of capacity, more transparent and efficient cost-and activity control, and greater competition [ 13 , 60 ]. This combination causes problems in actual hospital financing, although resource allocation in the costing scheme is advanced.

Still, the G-DRG costing scheme is the best starting-point for management decisions and for the implementation of further patient-level costing. With the mentioned limitations, especially concerning tariff calculation at national level, the current G-DRG costing scheme can be considered to be efficient and transparent.

National Center for Biotechnology Information , U. Journal List Health Econ Rev v. Health Econ Rev. Published online Aug Matthias Vogl 1, 2. Author information Article notes Copyright and License information Disclaimer. Corresponding author. Matthias Vogl: ed. Received Mar 19; Accepted Aug This article has been cited by other articles in PMC. Abstract The purpose of this paper is to analyze the German diagnosis related groups G-DRG cost accounting scheme by assessing its resource allocation at hospital level and its tariff calculation at national level.

Keywords: Hospital reimbursement, Hospital costs, Accounting, Resource allocation, Prospective payment system, Diagnosis related groups. Methods An executive summary is given of the InEK cost accounting scheme at hospital level and on the determination of reimbursement rates at national level, to show the course of action in calculating German inpatient relative prices.

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Figure 1. Resource allocation at hospital level The groundwork This section demonstrates the course of action in the G-DRG cost accounting system to allow a detailed assessment of the ability of the scheme to accommodate differentiated resource allocation and precise cost assessment. Figure 2.