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Childbirth and Diagnosis Related Groups (DRGs): patient classification and hospital reimbursement in 11 European countries
European Journal of Obstetrics & Gynecology and Reproductive Biology, 1, 168, pages 12 - 19
The study compares how Diagnosis-Related Group (DRG) based hospital payment systems in eleven European countries (Austria, England, Estonia, Finland, France, Germany, Ireland, Netherlands, Poland, Spain, and Sweden) deal with women giving birth in hospitals. It aims to assist gynaecologists and national authorities in optimizing their DRG systems.
National or regional databases were used to identify childbirth cases. DRG grouping algorithms and indicators of resource consumption were compared for those DRGs which account for at least 1% of all childbirth cases in the respective database. Five standardized case vignettes were defined and quasi prices (i.e. administrative prices or tariffs) of hospital deliveries according to national DRG-based hospital payment systems were ascertained.
European DRG systems classify childbirth cases according to different sets of variables (between one and eight variables) into diverging numbers of DRGs (between three and eight DRGs). The most complex DRG is valued 3.5 times more resource intensive than an index case in Ireland but only 1.1 times more resource intensive than an index case in The Netherlands. Comparisons of quasi prices for the vignettes show that hypothetical payments for the most complex case amount to only €479 in Poland but to €5532 in Ireland.
Differences in the classification of hospital childbirth cases into DRGs raise concerns whether European systems rely on the most appropriate classification variables. Physicians, hospitals and national DRG authorities should consider how other countries’ DRG systems classify cases to optimize their system and to ensure fair and appropriate reimbursement.
Keywords: Childbirth, Delivery, Diagnosis-Related Groups, Europe, Economics, Hospital.
Diagnosis Related Groups (DRGs) are widely used in Europe for a range of different purposes  and : they form the basis of hospital performance comparisons, they are used to facilitate hospital management and in DRG-based hospital payment systems, and they define reimbursement categories or “hospital products”  . DRGs are clinically meaningful groups of patients that have (a) similar clinical characteristics and (b) similar patterns of resource consumption  . Even though some systems do not define DRGs in the strict sense of the word (that is groups are not diagnosis related), this article uses the term DRGs to summarize all groups of patients defined by DRG systems or similar grouping algorithm. When DRGs are insufficiently homogenous in terms of resource consumption, performance comparisons do not adequately control for differences between patients within DRGs and, for a large number of patients, hospital reimbursement is either too high or too low. Therefore, classification variables, such as diagnoses, procedures and patient demographics, ideally take the most important determinants of resource consumption (and ultimately costs) into account  and .
Childbirth is one of the main causes of hospitalization for women, accounting for about 5% of hospital activity in most OECD countries  . Optimal design of DRG systems for childbirth cases is essential in order to assure adequate performance comparisons and fair reimbursement for this very frequent cause of hospitalisation. Comparative analyses of how different countries’ DRG systems classify women giving birth can help obstetricians, paediatricians and midwives to scrutinize national standards of classification against European equivalents and to identify potential scope for improvement. Furthermore, analyses of how the services of specialists in treating different women are valued and reimbursed in other DRG systems may inform and substantiate discussions about the adequacy of cost weights (or other indicators of resource consumption). Yet, detailed comparative analyses of grouping algorithms for childbirth are very scarce, suffer from a very limited scope, and have not assessed the classification of patients using routine inpatient data  . Therefore, the present study aims to assess the grouping algorithms used in eleven European countries to (1) identify classification variables used to classify hospital childbirth cases into DRGs, (2) compare variations in resource consumption intensity of DRGs within countries, and (3) compare variations in hospital price levels between countries. The results were generated as part of the EuroDRG project, Diagnosis-Related Groups in Europe: Towards Efficiency and Quality, which aimed to examine the ability of European DRG systems to define homogenous groups of patients.
2. Materials and methods
2.1. Definition of episode of care
Similar methods have been reported previously for two other episodes of care, i.e. appendectomy breast cancer  , Acute myocardial infarction  , and stroke  . In short, as part of the EuroDRG project, researchers from eleven European countries (Austria, England, Estonia, Finland, France, Germany, Ireland, the Netherlands, Poland, Spain and Sweden) agreed upon a common definition for hospital childbirth. The definition was based on the International Classification of Diseases 10th edition (ICD-10) for diagnoses and ICD-9 Clinical Modification (ICD-9CM) for procedures, or equivalent national procedure codes, and is presented in Box 1 . Depending on national coding guidelines and practices as well as on national diagnosis and procedure coding systems, large discrepancies exist across countries concerning how “childbirths” can be identified in national databases. Therefore, national researchers in the EuroDRG project defined national criteria that would ensure the identification of all live and stillbirths in the respective country's database.
|Defined by||Primary or secondary diagnosis or by procedure or by both|
|Primary diagnosis (ICD-10)||France||Z37.x|
|Estonia||O32, O34, O60, O63, O64, O68 and O80-O84|
|Sweden||O80-O84 and Z37|
|Primary diagnosis national code||Netherlands a||V51|
|Secondary diagnosis (ICD-10)||Germany||Z37.x|
|Procedure (ICD-9CM, or equivalent in national codes)||Austria b||3851, 3852, 3853, 3855, 3856 and 3857|
|Ireland c||72, 73 and 74|
|Spain||72, 73 and 74|
|Poland||72, 73 and 74|
|Primary diagnosis and procedure|
|Primary diagnosis||Finland||O60, O63, O68 and O80-O84|
|Procedure||Finland e||MAC, MAD, MAE, MAF, MAG, MAH and MCA|
a Diagnosis treatment combination.
c ACHI: Australian Classification of Health Interventions.
d OPCS 4.5: Classification of Surgical Operations and Procedures (version 4, 2009–11 (5th revision).
e NCSP: Nomesco Classification of Surgical Procedures.
ICD-10: International Classification of Diseases, 10th edition; ICD-9CM: International Classification of Diseases Clinical Modification.
2.2. Data sources
In each country, researchers identified national or regional hospital databases and obtained access to all information necessary for the purposes of this study, i.e. diagnoses, procedures, and DRGs of anonymous individual patients. Table 1 provides an overview of the databases and data years available for each country. In addition, the Table specifies the DRG system and versions used in the database.
|Country||Database||Data year||Grouping algorithm||Identified childbirth cases in databases|
|Austria||Leistungsorientierte Krankenanstaltenfinanzierung (LKF)-database of the Bundesministerium für Gesundheit (BMG)||2008||LKF version 2008||74,095|
|England||Hospital Episode Statistic (HES)||2007/08||HRG version 4||555,432|
|Estonia||Estonian Health Insurance Fund (EHIF)-database||2008||NordDRG version 2008||15,624|
|Finland||Finnish Hospital Discharge Register||2008||NordDRG version 2008||57,990|
|France||Programme de Médicalisation des Systèmes d’Information en Médecine, Chirurgie, Obstétrique (PMSI MCO)-database||2008||GHM11 version 2009||770,590|
|Germany||DRG-statistic of the Federal Statistical Office (Destatis)||2008||G-DRG version 2008||655,116|
|Ireland||Hospital In-patient Enquirey (HIPE)-database of the Health Services Executive (HSE)||2008||AR-DRG version 5.1||71,742|
|Netherlands||Database of the Diagnosis Treatment Combinations (DBC)-casemix system||2008||DBC version 2008||75,363|
|Poland||Register of episodes of care and reimbursement of the National Health Fund (NHF)||2009||JGP version 2008||395,351|
|Spain||Hospital Minimum Basic Data Set (CMBD) of the Public Hospital Network of Catalonia (XHUP)||2008||AP-DRG version 23||62,250|
|Sweden||National Patient Register (NPR) of the Board of Health and Welfare||2008||NordDRG version 2008||106,111|
Researchers from each country translated the definition into national codes for diagnoses and procedures. The number of childbirth cases and the corresponding DRGs were extracted from the databases. The number of cases varied from about 15,600 in Estonia to almost 770,600 cases in France (see Table 1 ).
2.3. Patient classification variables
Detailed comparative analyses of grouping algorithms and classification variables were performed for the most frequent DRGs, i.e. those DRGs that individually accounted for at least 1% of cases in our databases. Grouping algorithms were mapped graphically to facilitate easy comparison of similarities and differences between DRG systems. In addition, we calculated for each DRG the percentage of included cases out of all childbirth cases identified in the respective database.
2.4. Comparison of variations in resource consumption intensity
Relative resource consumption of each DRG was compared to a country-specific index DRG. The index DRG was specified as that DRG, into which an index case of a 32-year-old woman admitted to the hospital for the normal delivery of one newborn would be classified. Subsequently the index DRG was assumed to have a cost index of one.
The national measure of resource consumption (cost weight/raw tariff/score) of the index DRG was then used as the denominator for calculating a cost index. For each country, the cost weight/raw tariff/score of each DRG was divided through the cost weight/raw tariff/score of the index case in order to calculate a cost index for each DRG. This cost index can then serve as an indicator of the relative resource intensity of different DRGs within one country. In addition, the cost index can be used to compare the ability of different countries’ systems to differentiate between complicated and uncomplicated cases
2.5. Comparison of hospital price levels
In addition to the normal delivery without complications (index case), five standardized case vignettes of women with different combinations of diagnoses, procedures, age, setting and length of stay (LOS) were defined to compare variations in hospital price levels between countries ( Table 2 ). The selection was meant to cover a range of different DRGs in each DRG system. The vignettes represented cases of childbirth by ascending order of complexity, from a day case without complications (vignette 1) to twin birth (vignette 5).
|Primary or secondary diagnosis (ICD-10)||Delivery procedure (ICD-9-CM)||Obstetrical trauma – fourth or third degree perineal laceration during delivery (ICD-10: O70.3)||Age (years)||Setting||LOS (days)|
|Woman 1||Single live birth (Z37.0)||Manually assisted delivery (73.5)||No||29||Day case/short therapy or inpatient||1|
|Woman 2||Single live birth (Z37.0)||Manually assisted delivery with episiotomy (73.5 and 73.6)||No||16||Inpatient||4|
|Woman 3||Single live birth (Z37.0)||Low forceps operation with episiotomy (72.1)||Yes||34||Inpatient||4|
|Woman 4||Single live birth (Z37.0)||Classical caesarean section (74.0)||No||29||Inpatient||5|
|Woman 5||Twins, both live born (Z37.2)||Manually assisted delivery (73.5)||No||31||Inpatient||7|
|Index case||Single live birth (Z37.0)||Manually assisted delivery (73.5)||No||32||Inpatient||4|
National researchers grouped the case vignettes into DRGs and determined whether the national DRG system would consider these cases to be inliers or outliers, i.e. whether the predefined LOS is below or above the DRG system-specific lower or upper LOS threshold. Quasi prices were ascertained for the index case and for each vignette using an approach similar to that of Koechlin et al.  . Quasi prices were supposed to reflect the national average costs of treatment and – if possible – to include the full set of costs, i.e. recurrent and capital costs. Finally, the index DRG was appointed a quasi price index of one. The quasi price index of all remaining DRGs was calculated by dividing the quasi price of each scenario by that of the index DRG.
All prices were reported in 2008 Euros. If necessary, prices were deflated to year 2008 national currency using national GDP  and  and converted to Euros using average currency exchange rates for the year 2008  .
3.1. Patient classification variables
Fig. 1 provides a simplified illustration of the classification variables of grouping algorithms for DRG systems in eleven European countries. The Figure includes classification variables of those DRGs that individually represent at least 1% of childbirth cases in each country (and certain DRGs that are necessary for understanding the grouping logic). The last columns on the right show the percentage out of all childbirth cases covered by each DRG and the cost index. Together, the DRGs included in our study account for 99% or more of all childbirth cases in each of the considered countries. DRGs containing less than 1% of cases in the national database are characterized by shaded boxes in light grey and are not considered in the following analysis. The index DRGs are highlighted in dark grey.
There is great variation in grouping algorithms across Europe. The number of DRGs included in the study ranges from only three in Austria, The Netherlands and Poland, to eight in Germany. In addition, the number and type of classification variables differ between DRG systems. In general, classification variables include: (1) type of diagnosis, (2) surgical partition (i.e. performance of an operating room procedure), (3) type of delivery (4) ‘complicating conditions’ (5) LOS, (6) age, (7) weeks of pregnancy at delivery, and (8) treatment setting. However, while Austria distinguishes only between different types of delivery (vaginal, complicated, c-section), a much higher number of classification variables are used in Germany (spontaneous delivery, other vaginal, c-section, other complicating procedures, complicating diagnoses, multiple complicating diagnoses, intrauterine therapy, week of pregnancy, length of stay, and other complications).
Obviously, the type of delivery is used as a classification variable by each of the countries. With the exception of Poland, all countries differentiate between vaginal delivery and caesarean section. England, Estonia and Germany additionally distinguish between assisted and non-assisted vaginal delivery. Other distinctions concern surgical non-caesarean section delivery in Germany and obstetrical trauma in The Netherlands. Multiple deliveries are classified according to type of delivery in Poland and The Netherlands and according to complicating diagnosis or procedure in Ireland.
Except for The Netherlands, all countries attempt to take into account whether a case is complicated or not, but they differ greatly in their approaches to identifying complicated cases. Austria uses only complicated delivery, while Estonia uses both complicated delivery and complicated caesarean section. England, France and Poland identify complications or comorbidities (CC) on the basis of secondary diagnoses and differentiate between without CC, with CC, and sometimes with major CC (France). In addition, Finland, Spain and Sweden include complicated delivery and complicated caesarean section as classification variables. Germany and Ireland aggregate complicating diagnoses and discharge status into a patient clinical complexity level (PCCL). Another less frequently used classification variable includes intrauterine therapy (IUT; Germany).
Finally, France, Germany and Poland use LOS to identify women with CC who stay in hospitals for a relatively short time, and consequently do not require high reimbursements. Other classification variables concern age (England), weeks of pregnancy at delivery (Germany), and treatment setting (Finland, The Netherlands, and Sweden).
3.2. Comparison of variations in resource consumption intensity
In most countries, the vast majority of childbirth cases are grouped into the black DRG ( Fig. 1 ) containing the index case ( Box 1 ), i.e. between 16% in Ireland and 90% in Poland. The high percentage for Poland might be explained by the fact that Poland is the sole country which does not differentiate between vaginal delivery and caesarean section. Fig. 1 also presents the relative resource consumption intensity of DRGs by means of cost indices. In most countries, the index DRG has the lowest cost index, but in The Netherlands a specific outpatient DRG exists with a tariff that is about 45% below that of the index DRG. In France and Finland, similar DRGs exist but they contain only about 1% of all cases.
Comparisons of cost indices show that an uncomplicated caesarean section is associated with 40% higher payments than an uncomplicated vaginal delivery in Estonia but with 186% higher payments in Ireland. A complicated delivery does not lead to higher payments for vaginal deliveries in Estonia (cost index 1.01) but to 67% higher payments in Spain. In Poland, hospitals receive 40% higher payments for vaginal deliveries with CCs if women stay at least 6 days in hospitals, while hospitals receive 60% higher payments in England and France (in France for major CCs).
As shown in Fig. 1 , the highest cost indexes are valued around three times higher than the index case (England, Germany, and Ireland). In general, the most complex DRG concerns a caesarean section with CC (England, Estonia, Finland, France, Germany, Ireland, Spain, and Sweden). In the German DRG system, where weeks of pregnancy are considered, hospitals receive substantially higher payments for preterm delivery (under 33 weeks and under 26 weeks). In the three countries with only three DRGs for childbirth stays (Austria, The Netherlands and Poland), the highest valued DRG has a cost index below two. Age does not influence the cost index in England.
3.3. Comparison of hospital price levels
Table 3 shows a comparison of DRGs and hospital quasi prices reflecting national average hospital payments for each case vignette and the index case under the assumption that hospital payment would be exclusively based on DRGs.
|Woman 1||Woman 2||Woman 3||Woman 4||Woman 5||Index case|
|DRG||Quasi price (€)||DRG||Quasi price (€)||DRG||Quasi price (€)||DRG||Quasi price (€)||DRG||Quasi price (€)||DRG||Quasi price (€)|
|Austria||Mel13.09A b||1263||Mel13.09A a||2136||Mel13.08A a||2711||Mel13.02A b||3210||Mel13.08A a||2711||Mel13.09A a||2136|
|England||NZ01B a||1474||NZ01D a||1478||NZ01B a||1474||NZ03A a||3239||NZ01A a||2362||NZ01B a||1474|
|Estonia||373 a||756||373 a||756||372 a||764||371 a||1058||373 a||756||373 a||756|
|France||14Z02T a||1092||14Z02A a||2114||14Z02A a||2114||14C02A a||2960||14Z02C a||3332||14Z02A a||2114|
|Germany||O60D b||908||O60D a||1592||O60C a||1828||O01F a||2612||O60B a||2161||O60D a||1592|
|Ireland||O60C a||1931||O60C a||1931||O02A a||4645||O01C a||5532||O60A a||3914||O60C a||1931|
|Sweden||373 a||2047||373 a||2047||372 a||3125||371 a||4192||373 a||2047||373 a||2047|
Large variation in hospital payments exists across countries. In general, quasi prices tend to be lower in countries with a low GDP per capita, i.e. Estonia and Poland, and high in countries with a higher GDP  . Interestingly, however, countries that pay a higher price for one of the vignettes do not necessarily pay a higher price for all kinds of vignettes (woman 1–6). For example, hospitals in England would receive a higher payment than hospitals in France for a classical caesarean section (vignette 4). Conversely, hospitals in France would receive a higher payment than hospitals in England for a twin birth (vignette 5). In some countries, such as Estonia, Finland, Spain and Sweden, a twin birth does not change the tariff compared to a single birth without complications.
Fig. 2 shows the ratio of the quasi price of each DRG compared to a normal delivery without complications (index case) per country (quasi price index = 1). A quasi price index of 2.0 indicates that hospitals would receive twice the price as for a normal delivery in the respective country. The largest within-country variations are found in England, Ireland, Spain and Sweden, where a classical caesarean section (vignette 4) has a quasi price that is more than twice as high as that of the index case. In contrast, only slight variations exist in Estonia, Poland and The Netherlands. Not surprisingly, in half of the countries, payment for a day case without complications (vignette 1) is below that for the index case. Austria and Germany do not have specific DRGs for day cases but apply a LOS-based payment reduction for cases staying shorter than a lower LOS threshold, and this also applies for day cases.
This study presents results of the most comprehensive available comparative analysis of grouping algorithms, classification variables, and prices used for deliveries in the hospital setting in different DRG systems in Europe. It shows great variations across countries in: (1) the number and type of DRGs individually comprising at least 1% of childbirth cases and in the number of considered classification variables, (2) the degree of differentiation between complex and less complex cases, i.e. in the relative resource use intensity of different DRGs, and (3) quasi prices for different types of women (case vignettes).
If DRG systems do not distinguish between less and more complex cases, hospitals and obstetricians that treat a greater share of complicated cases than others are not paid for their higher costs. Therefore, it is important that grouping algorithms define as many DRGs as necessary to assure that performance comparisons and hospital reimbursement are appropriate and reliable  and . Our study showed that Austria, The Netherlands, and Poland classify more than 99% of childbirth cases into only three DRGs, while seven and eight DRGs are used in England and Germany respectively. A complementary statistical analysis, however, showed that countries with higher numbers of DRGs, such as England and Germany, do not necessarily perform better in adjusting for resource use  . The analysis found a contrasting ability of DRG sets to explain resource use for childbirth. DRGs were able to explain 70% of the cost variation in Spain and Estonia, 57% in France and 54% in England, but only 48% in Finland and Germany and 40% in Sweden. Yet, large variations between European DRG systems in the classification of a relatively well defined group of patients may suggest that not all systems consider the most important determinants of resource use as classification variables.
The greatest differences between European DRG systems exist in their approaches towards identifying complicated cases. Interestingly, this is true also when comparing European DRG systems to their equivalents in the United States, most notably the all patient (AP)-DRGs and Medicare Severity-adjusted (MS)-DRGs. On the one hand, as several European DRG systems have their – sometimes remote – roots in DRG systems that were imported from the US  , it is not surprising that classification is often very similar. On the other hand, however, some innovative approaches towards identifying complicated childbirth cases are noteworthy in European DRG systems. Examples are the Patient Clinical Complexity Levels (PCCL) as an aggregate measure of complexity, which was originally imported with the Australian Refined (AR)-DRG system to Ireland and Germany, and differentiation between preterm births through consideration of the week of pregnancy (in Germany). Possibly, countries in Europe and also the United States could improve the homogeneity of DRGs by incorporating these variables.
A previous European study suggested that costs for normal deliveries in the hospital setting were the highest in Germany and France, and LOS the highest in France  . Our study showed that the DRG system in France awards higher payments for patients that stay longer in hospitals. Possibly, this contributes to longer LOS in French hospitals.
Grouping algorithms do not always sufficiently account for increased resource consumption, such as for caesarean sections and/or complicating diagnoses or procedures. With respect to twin births (vignette 5), Estonian, Finnish, Spanish and Swedish hospitals generally receive a lower payment compared to hospitals in other countries, and the same payment as for normal deliveries without complications (index case) in their own countries. Thus, while twin births commonly relate to greater resource consumption compared to single births, this is not at all reflected by the quasi prices in Estonia, Finland, Spain, and Sweden. In the three countries with only three DRGs for childbirth cases (Austria, The Netherlands and Poland), the highest valued DRG has a cost index below two. Therefore, these systems do not take into account more detailed information and reimburse maximum twice the tariff of the index case for the more complex DRG. Indeed, in these cases the more complex DRGs are complicated delivery (Austria), obstetrical trauma (The Netherlands), and multiple delivery/preterm labour (Poland). Furthermore, the funding in different DRG systems might affect the resources that are actually consumed. For example, countries may distribute delivery costs separately to mother and newborn. As our study only referred to the resources consumed by the mother, it is likely that increased funding by means of additional DRGs applies to newborns with complications. A future study could examine whether increased funding leads to increased concentration on particular DRGs.
Our study has several limitations. Firstly, the data used to identify patients, and to assess the relative importance of different DRGs in different countries, originated from routine inpatient databases in eleven countries. As highlighted by the Hospital Data Project  , there are differences in coding practices across countries, and the quality of data is not always comparable. Findings should therefore be interpreted with great caution. Secondly, as we limit part of our comparative analysis to DRGs that account for at least 1% of cases ( Fig. 1 ), we partially neglect how different systems deal with rare outliers, which may, however, be particularly relevant for reimbursement. Thirdly, Table 3 shows quasi prices and not actual hospital payments. This is because different systems account for differences in complexity in different ways. Differences in complexity may be accounted for through adjustments outside the DRG system. In Austria and Finland, for example, hospital payment varies by region and (type of) hospital. Furthermore, differences may be accounted for by the inclusion of different cost categories and/or additional payments. For example, England assigns additional DRGs when certain diagnostic evaluations are performed, while Poland and Austria have additional per-diem based payments for intensive care unit stay  . Additionally, patients in Finland and The Netherlands could have several DRGs per hospital stay, each leading to additional DRG-based payments  . Our findings should therefore be interpreted with great caution. Finally, differences in terms of the health care organization for childbirth may have an impact on the DRG systems and grouping algorithms. For instance, hospitals are increasingly regarded as the safest and most appropriate place to give birth in most Western countries, but the exact proportion of hospital childbirth varies widely between countries, ranging from approximately 71% in the Netherlands  to 98% in France  . Therefore, differences in grouping algorithms between countries may be explained by differences in the health care systems.
In many countries, professional medical associations, specialist experts or consultants formally participate in the process of selection, definition, and update of classification criteria via committees, expert hearings or consultations  and . One example of such involvement is Germany, where the active participation of obstetricians during the yearly updates of the G-DRG system has over time led to the incorporation of classification variables for “weeks of pregnancy” and “intrauterine therapy”  .
Our European comparison can provide a useful new perspective when thinking about how to improve an existing system. For example, obstetricians, paediatricians and midwives in most European countries could ask national DRG authorities to investigate whether homogeneity of patients within DRGs would be increased by introducing classification variables for preterm births (week of pregnancy). In addition, Estonia, Finland, Spain and Sweden could check whether the incorporation of twin births as a classification variable would contribute to more homogenous DRGs. Improving the national DRG system is important because, ultimately, this contributes to assuring adequate performance comparisons and fair hospital reimbursement on the basis of DRGs.
Disclosure of interests
The authors declare that they have no competing interests.
Martine M Bellanger (MMB), Wilm Quentin (WQ) and Siok Swan Tan (SST) have contributed to acquisition of data; MMB drafted the first article and then benefited from SST and WQ for critically revising, in both the interpretation of results and the discussion; all three authors read and approved the final version.
This study was supported by the European Commission within the seventh framework programme (FP7) (Grant Agreement Number 223300).
The results presented in this paper were generated as part of the project ‘Diagnosis-Related Groups in Europe: Towards Efficiency and Quality (EuroDRG)’, which was funded by the European Commission within the Seventh Framework Research Programme (Grant Agreement Number FP7-223300). We are grateful to all our project partners who made this work possible.
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a Ecole des Hautes Etudes en Santé Publique, Rennes Sorbonne Paris Cité, Avenue du Professeur Leon Bernard, 35043, Rennes, France
b European Observatory on Health Systems and Policies, Department of Health Care Management Technische Universität (TU) Berlin, Germany, Straße des 17. Juni 135, 10623 Berlin, Germany
c Institute for Medical Technology Assessment, Erasmus Universiteit Rotterdam, PO Box 1738, 3000 DR Rotterdam, The Netherlands
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