Background and aim Costing is a crucial component of health economic evaluations, but there is a wide variation in the approaches of calculating costs in the German health care system. This series of articles aims to propose unified costing methods for the different health care sectors while the current article is addressing overarching problems across all sectors.Methods The working group "Standardized Costing" within the committee "Economic Evaluation" of the German Society of Health Economics (dggo) discussed the current problems in the context of costing for health economic evaluation and developed agreed, unified costing approaches for the different health care sectors. The group consisted of researchers from universities and decision-makers in the German health care system and developed the recommendations at three personal meetings and additional telephone conferences. Preliminary results were presented at the 11th annual meeting of the dggo.Results The current paper presents the recommendations regarding perspective, price-resources framework, study types, cost components, data sources, adjustment of cost data over time or cross-country, and uncertainty in cost calculations. Additionally, the general structure of the four following articles on health care sector-specific costing is presented.

Zusammenfassung Hintergrund und Zielsetzung Kostenberechnungen sind ein wesentlicher Bestandteil gesundheitsökonomischer Evaluationen, weisen jedoch für den deutschen Versorgungskontext teilweise große Unterschiede im methodischen Vorgehen auf. Zielsetzung der vorliegenden Artikelserie ist es, einen konsentierten Vorschlag zu den Vorgehensweisen der Kostenberechnungen in verschiedenen Versorgungssektoren zu präsentieren und mit diesem einführenden Artikel allgemeine, Sektoren-unspezifische Aspekte in der Durchführung von Kostenberechnungen zu beschreiben. Methodik In der Arbeitsgruppe „Standardkosten“ des Ausschusses „Ökonomische Evaluation und Entscheidungsfindung“ haben sich Wissenschaftlerinnen und Wissenschaftler von Universitäten und Entscheidungsträgern im Gesundheitswesen zusammengeschlossen, um die bestehenden Probleme bei Kostenberechnungen im Rahmen gesundheitsökonomischer Forschungen zu diskutieren und ein einheitliches Vorgehen zu erarbeiten. Zur Entwicklung der Empfehlungen fanden drei Arbeitstreffen sowie weitere Telefonkonferenzen statt. Die vorläufigen Ergebnisse wurden auf der 11. Jahrestagung der dggö der Fachöffentlichkeit vorgestellt. Ergebnisse Im vorliegenden ersten Artikel einer zunächst fünf Artikel umfassenden Serie werden grundsätzliche Themen der Perspektivwahl, des Preis-Mengengerüstes, der Studienarten, der Kostenkomponenten, der Datenquellen, der Anpassung von Kostendaten über die Zeit oder über Ländergrenzen hinweg sowie der Umgang mit Unsicherheit behandelt und Empfehlungen zu diesen Themen gegeben. Des Weiteren wird die Gliederung von später folgenden vier Artikeln zu den Berechnungsmethoden in einzelnen Versorgungssektoren beschrieben.

Aim The legal regulations on reimbursement and billing of drugs in Germany are very complex, so that the estimation of drug costs in health economic evaluations is often handled differently. The aim of this paper is to describe a methodological procedure for the determination of drug costs in the context of health economic evaluations in Germany. Method The description was primarily carried out from the perspective of the Statutory Health Insurance and is based on the general steps of cost estimation: identification, quantification and assessment of resources, followed by an aggregation. Aside from particularities in the German context, various data sources have to be considered. Results In order to determine drug costs, the approval and reimbursement status must also be taken into account. To estimate the resource consumption, information on dosage (quantity and frequency) and treatment duration is required. The pharmacy sales prices and, if available, reference prices provide a basis for the assessment of resource consumption. In order to calculate the drug costs, specific statutory regulations on discounts and co-payments must also be considered. Conclusion Despite efforts to achieve a standardisation, there are still limitations regarding the determination of drug costs. Uncertainties arise particularly from the fact that individual discount contracts cannot be taken into account as they are not publicly accessible. This paper, intends to improve the consistency and comparability of drug costs estimations in health economic evaluations, therefore promoting the process of rational decision making.

Zusammenfassung Zielsetzung Die gesetzlichen Regelungen zur Erstattung und Abrechnung von Arzneimitteln sind sehr komplex, sodass die Bestimmung der Arzneimittelkosten im Rahmen von gesundheitsökonomischen Evaluationen oft unterschiedlich gehandhabt wird. Ziel der Arbeit ist es, ein mögliches methodisches Vorgehen zur Kostenbestimmung von Arzneimitteln in Deutschland für gesundheitsökonomische Evaluationen zu beschreiben. Methoden Die Darstellung erfolgt primär aus der Perspektive der gesetzlichen Krankenversicherung und orientiert sich an den allgemeinen Schritten zur Kostenbestimmung: Ressourcenidentifikation, Bestimmung des Mengen- und Preisgerüsts, Aggregation. Dabei sollen neben Besonderheiten im deutschen Kontext auch verschiedene Datenquellen Berücksichtigung finden. Ergebnisse Für die Kostenbestimmung sind insbesondere der Zulassungsstatus und die Erstattungsfähigkeit der Arzneimittel zu berücksichtigen. Zur Erfassung des Ressourcenverbrauchs sind Angaben zur Dosierung (Menge und Häufigkeit) und zur Behandlungsdauer erforderlich. Als eine Grundlage für die Bewertung des Ressourcenverbrauchs gilt der Apothekenabgabepreis und – sofern vorhanden – Festbeträge. Um die Kosten für verschreibungspflichtige Arzneimittel zu berechnen, sind spezifische gesetzliche Regelungen zu Rabatten und Zuzahlungen zu berücksichtigen. Schlussfolgerung Trotz der Bemühungen um eine Standardisierung sind weiterhin Limitationen im Bereich der Kostenermittlung von Arzneimitteln vorhanden. Unsicherheiten ergeben sich insbesondere aufgrund der Nichtberücksichtigung von kassenindividuellen Rabattverträgen, da diese nicht öffentlich zugänglich sind. Auch unter Berücksichtigung der dargelegten Limitationen soll die vorliegende Arbeit einen Beitrag zu einer Verbesserung der Konsistenz der Kostenermittlung und Vergleichbarkeit von Arzneimittelkosten im Rahmen gesundheitsökonomischer Evaluationen leisten und somit den Prozess einer rationalen Entscheidungsfindung befördern.

Objectives Dossiers submitted for early benefit assessments in Germany also provide information on the precise determination of the target population (patients eligible for a drug). The situation is complex for non-small-cell lung cancer (NSCLC) due to highly specific therapeutic indications. Our aim was to compare the different methodological steps applied to determine the target population in dossiers on drugs for NSCLC. Methods We analysed NSCLC dossiers assessed by the German Institute for Quality and Efficiency in Health Care (IQWiG) between 01.01.2011 and 31.12.2017. Methodological details regarding the determination of the target population were extracted and compared. Results We analysed 23 NSCLC dossiers. In all dossiers, the target population was determined using the number of all patients with lung cancer as the basis for calculations. This patient population was further reduced in several successive steps by assuming proportions of patients with a specific characteristic (e.g. disease stage). The most important calculation steps were patients with NSCLC ( n = 23 dossiers), with a specific disease stage ( n = 23), with a specific tumour mutation ( n = 14), with a specific tumour histology ( n = 7), without prior treatment ( n = 15), with pretreatment in second or further treatment lines ( n = 17), and/or with specific pretreatments ( n = 9). The proportions of patients determined within the same calculation step varied considerably between dossiers. Discussion The calculation methods applied and the target population sizes reported in NSCLC dossiers vary considerably. A consensus with regard to the databases and calculation methods used to determine the target population in NSCLC would be helpful to reduce variations.

OBJECTIVES:Since 2011, early benefit assessment of all new drugs launched in Germany is mandatory. The exact determination of the appropriate target population (i. e. patients eligible for a drug) plays an important role for subsequent price negotiations. In type 2 diabetes, the size of the target population varies considerably between company dossiers submitted for assessment. Our aim was to explore whether routine data from all persons insured in German statutory health insurance (SHI) funds can be used to derive information on the size of the target population with type 2 diabetes.METHODS:We explored how the data available at the German Institute of Medical Documentation and Information (DIMDI) can be used to obtain the information required. A data-based concept was chosen and the selection criteria were developed in a multidisciplinary project group. Before finalizing the database query, the criteria were evaluated in a test database and the database query was then repeatedly modified.RESULTS:At the time of the design of our analysis in 2017, the most recent data available at DIMDI were for 2013. The algorithm we developed for identifying patients with type 2 diabetes and classifying them according to their medication, based primarily on the combination of ICD and ATC codes, enabled us to determine the size of target populations for different indications in diabetes mellitus type 2.CONCLUSION:Our methodological approach seems to be suitable to determine target populations in type 2 diabetes.

Since 2015, it has been IQWiG’s legal responsibility to coordinate HTA reports, to provide a methodological framework and reporting structure. The health economic domain includes the assessment of intervention costs as well as, depending on the initial question, a systematic review or a specific analysis of the cost-effectiveness. In autumn of 2017, external experts commenced working on the first topics within the framework of the so-called “ThemenCheck Medizin” (“Topic Check Medicine). First preliminary HTA reports were just published. Our aim was to analyse these HTA reports with a focus on the summarised results of the health economic domain. We retrieved all publicly available preliminary HTA reports from the “ThemenCheck Medizin” homepage (www.themencheck-medizin.iqwig.de). Therefore, we investigated and summarised the author’s results on benefits and harms as well as the results on the cost-effectiveness-ratio of a medical procedure. Since December 2018 until now, 4 preliminary HTA reports were published. In 2 of these 4 reports (topics: music therapy for patients with cancer, interventions in the event of a suicidal crisis) the authors declare a benefit of the intervention. The health economic domain of all preliminary HTA reports contains information on intervention costs. None of the reports, however, contained any information on the cost-effectiveness. Only 1 report (cleft lip and palate: nasoalveolar molding) provided results on health economic aspects: external experts had expanded the methodological framework and reported total costs based on cost analyses. In order to receive more results on health economic aspects within HTA reports, a modification of the methodological framework of the health economic domain is necessary. Widening the health economic focus from cost-effectiveness information to health economic aspects such as cost analyses might achieve this aim.

In a recently published article, Quang et al. evaluate the quality of systematic reviews of health economic evaluations of interventions for hepatitis.1 As the authors of one of the systematic reviews included in the assessment,2 we would like to discuss the methods which were applied and which, in our opinion, seem to be inappropriate.

Background: Estimating input costs for Markov models in health economic evaluations requires health state-specific costing. This is a challenge in mental illnesses such as depression, as interventions are not clearly related to health states. We present a hybrid approach to health state-specific cost estimation for a German health economic evaluation of antidepressants. Methods: Costs were determined from the perspective of the community of persons insured by statutory health insurance ("SHI insuree perspective") and included costs for outpatient care, inpatient care, drugs, and psychotherapy. In an additional step, costs for rehabilitation and productivity losses were calculated from the societal perspective. We collected resource use data in a stepwise hierarchical approach using SHI claims data, where available, followed by data from clinical guidelines and expert surveys. Bottom-up and top-down costing approaches were combined. Results: Depending on the drug strategy and health state, the average input costs varied per patient per 8-week Markov cycle. The highest costs occurred for agomelatine in the health state first-line treatment (FT) ("FT relapse") with €506 from the SHI insuree perspective and €724 from the societal perspective. From both perspectives, the lowest costs (excluding placebo) were €55 for selective serotonin reuptake inhibitors in the health state "FT remission." Conclusion: To estimate costs in health economic evaluations of treatments for depression, it can be necessary to link different data sources and costing approaches systematically to meet the requirements of the decision-analytic model. As this can increase complexity, the corresponding calculations should be presented transparently. The approach presented could provide useful input for future models.

Background and purpose: The German Institute for Quality and Efficiency in Health Care (IQWiG) previously tested two preference elicitation methods in pilot projects and regarded them as generally feasible for prioritizing outcome-specific results of benefit assessment. The present study aimed to investigate the feasibility of completing a discrete choice experiment (DCE) within 3 months and to determine the relative importance of attributes of periodontal disease and its treatment. Patients and methods: This preference elicitation was conducted alongside the IQWiG benefit assessment of systematic treatments of periodontal diseases. Attributes were defined based on the benefit assessment, literature review, and patients' and periodontologists' interviews. The DCE survey was completed by patients with a history of periodontal disease. Preferences were elicited for the attributes "tooth loss within next 10 years", "own costs for treatment, follow-up visits, re-treatment", "complaints and symptoms", and "frequency of follow-up visits". Patients completed a self-administered questionnaire including 12 choice tasks. Data were analyzed using a random parameters logit model. The relative attribute importance was calculated based on level ranges. Results: Within 3 months, survey development, data collection among 267 patients, data analysis, and provision of a study report could be completed. The analysis showed that tooth loss (score 0.73) was the most important attribute in patients' decisions, followed by complaints and symptoms (0.22), frequency of follow-up visits (0.02), and costs (0.03) (relative importance scores summing up to 1). Conclusion: A preference analysis performing a DCE can be generally feasible within 3 months; however, a good research infrastructure and access to patients is required. Outcomes used in benefit assessments might need to be adapted to be used in preference analyses.

Aim Since 2011, an early benefit assessment is required for all new drugs being launched in Germany. Evidence submitted by pharmaceutical companies in dossiers is assessed by the Institute for Quality and Efficiency in Health Care (IQWiG) and subsequently appraised by the German Federal Joint Committee (FJC). The exact determination of the patient target population plays an important role for subsequent price negotiations. In diabetes mellitus type 2 the size of target population varies considerably between dossiers. Our aim was to explore the reasons for these differences.Method We analyzed 20 dossiers with drugs for diabetes mellitus type 2 published between January 2012 and May 2015. Details regarding the estimation of the target population were extracted and compared. Based on the extractions a criteria list was developed to categorize possible reasons for different sizes of the target population.Results The estimations of the target population were mainly based on secondary data analyses of drug prescriptions. The methods and assumptions used to analyze these data varied widely.Important reasons for differences in the estimations are the kind of database, the time frame, the operationalization of diabetes patients, the specification of the target population, the type of contraindications, the consideration of currently undetected patients, the mode of extrapolation to the overall population, and the portion of statutory health insurance patients. We could not identify one reason that could explain most of the deviations in the size of the target population. Several reasons seem to interact and it was not possible to determine the direction or size of the effect.Conclusion There is a strong need for more detailed descriptions of the methods and databases used in the dossiers to estimate the size of the target populations. A harmonization of the methods seems to be helpful to reduce the variation.

The German Institute for Quality and Efficiency in Health Care (IQWiG) uses patient-relevant outcomes to inform decision-makers.

Pharmaceutical companies increasingly use statutory health insurance claims data analyses to quantify the target population in German reimbursement dossiers. We evaluated the analyses submitted by the manufacturers with a focus on reporting quality. The database comprised all dossiers published until May 2017 (n = 257) on the Federal Joint Committee’s homepage (http://www.g-ba.de/). We included all dossiers in which a statutory health insurance claims data analysis commissioned by the manufacturer was applied to determine the number of patients eligible for the drug under assessment. To evaluate the reporting quality, a 27-items checklist specifically developed for the frameworks and requirements of the German health care system – STROSA-2 (STandardized Reporting Of Secondary data Analyses) – was used. Two reviewers assessed all analyses independently; discrepancies were resolved through discussion. 18 claims data analyses used in 18 different benefit assessment procedures were eligible for inclusion. Detail and quality of reporting varied widely between reports. The evaluation with STROSA revealed several shortcomings: in most cases, facts on background and rationale were missing (n = 10). 10 analyses did not provide internal validation. The results section often contained no presentation of the characteristics of the study population (n = 5). Information on age and gender distribution relevant for the evaluation of the representativeness of the sample were frequently missing or incomplete (n = 12). Most analyses did not include a discussion of results (n = 7), internal validity (n = 12), strengths and weaknesses (n = 12) and transferability (n = 12). Claims data analyses may support the quantification of the target population in the early benefit assessment of drugs in Germany. To provide a reliable decision base, however, their reporting quality needs to be improved, in particular concerning the description of methods and the discussion of methods and results.

Bundesweit 40 Betriebe wurden mit dem Ziel erhoben, die Lahmheitssituation in der okologischen Zuchtsauenhaltung in Stallhaltungsverfahren mit Auslauf zu erfassen. Die mittlere Lahmheitspravalenz der tragenden Sauen lag bei 6,9 % (0 – 34,8 %, Median 5,1 %) und somit auf deutlich niedrigerem Niveau als Literaturangaben fur die konventionelle Zuchtsauenhaltung. Auf einzelnen Betrieben konnen Lahmheiten jedoch in erheblichem Umfang auftreten; ihrer Vermeidung sollte aus Tierschutz- und okonomischen Grunden in jedem Fall Beachtung geschenkt werden. Risikofaktoranalysen mittels multivariater logistischer Regression ergaben folgende Einflussfaktoren: In Betrieben, fur die die Wurfzahl der Sauen bekannt war (n=28 Betriebe, 447 Sauen), stieg mit steigender Wurfzahl bzw. mit steigender Anzahl Schwellungen, die das Einzeltier aufwies, das Risiko fur das Vorliegen einer Lahmheit. Bei Berucksichtigung des gesamten Datensatzes (n=40 Betriebe, 1.111 Sauen), aber unter Ausschluss des Faktors Wurfzahl, verblieben zusatzlich zum Faktor Schwellungen die Klauenlange (erhohtes Risiko durch zu lange Klauen), Einschatzung der Lahmheitssituation durch den Betriebsleiter (hoheres Risiko bei deutlicher Abweichung), die „Haltung der Jungsauen mit Auslauf“ (weniger Lahmheiten, wenn Auslauf vorhanden) sowie die Variable „Reinigung Haltungsbereich tragende Sauen“ (hoheres Risiko bei Grundreinigung) im Endmodell. Uber die Haltungsvorgaben in der okologischen Sauenhaltung scheinen wesentliche praventive Aspekte bereits umgesetzt zu sein. Die Ergebnisse der vorliegenden Untersuchung zeigen nichtsdestotrotz, dass das Management Einfluss auf die Lahmheitssituation nimmt. Das diesbezugliche Problembewusstsein sollte daher gefordert werden, z. B. hinsichtlich des Erkennens von Lahmheiten. Erst die Bestimmung des einzelbetrieblichen Status quo auf Grundlage tierbezogener Indikatoren ermoglicht es, Schwachstellen in Haltungsumwelt und Management aufzudecken und somit betriebsindividuelle Optimierungsmasnahmen ableiten zu konnen. Gefordert durch das Bundesministerium fur Ernahrung und Landwirtschaft aufgrund eines Beschlusses des Deutschen Bundestages im Rahmen des Bundesprogramms Okologischer Landbau und andere Formen nachhaltiger Landwirtschaft. Projektleitung: Dr. Friedrich Weismann, Thunen-Institut, Institut fur Okologischen Landbau

International institutions investigate different methods to systematically elicit patient preferences and discuss how these can best be used to inform health care decision making, e.g. approval and reimbursement. The German Institute for Quality and Efficiency in Health Care (IQWiG) conducted two pilot projects using Analytic Hierarchy Process and a Discrete Choice Experiment (DCE). The IQWiG recently initiated a new project to explore whether a preference elicitation using a DCE can be conducted within three months. The objective was to elicit patient preferences for treatment and disease characteristics of periodontal treatment alternatives. Treatment and disease characteristics for the DCE were identified by literature review and a preliminary list of endpoints provided by IQWiG. Endpoints were selected based on patient and periodontist interviews. Tooth loss, symptoms & complaints, costs, and frequency of periodontist visits were included as attributes in the DCE. A Bayesian efficient design was developed. A minimum sample size of 84 participants was estimated for analysis of the main effects model. Preferences were modeled with a random parameters logit model. Relative attribute importance was calculated based on the ranges of level coefficients within an attribute. At three months, 267 patients were included in the survey. Patients considered losing two teeth instead of none, the worst level in the experiment (-5.01, p<0.001). Having “long teeth due to gum recession” was the least preferred type of symptoms and complaints (-1.51, p<0.001). Overall, patients judged differences within the attribute tooth loss most important (0.73 relative weight), followed by symptoms & complaints (0.22), frequency of periodontist visits (0.03), and costs (0.02).CONCLUSIONS: Patients considered prevention of tooth loss most important in their decision. This preference elicitation shows that a DCE can be conducted within 3 months while still complying with standard methodological requirements and reaching a predefined sample size.

Zielsetzung Seit 2011 durchlaufen in Deutschland alle neu zugelassenen Arzneimittel die frühe Nutzenbewertung. Pharmazeutische Unternehmen reichen ein Dossier beim Gemeinsamen Bundesausschuss (G‑BA) ein, der das Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen (IQWiG) mit dessen Bewertung beauftragen kann. Die Angaben im Dossier zur Größe der Zielpopulation, für die das zu bewertende Arzneimittel infrage kommt, spielen u. a. eine Rolle in den nachfolgenden Preisverhandlungen. Bei den neu zugelassenen Arzneimitteln in der Indikation Diabetes mellitus Typ 2 variiert die Größe der Zielpopulation beträchtlich zwischen den Dossiers. Ziel dieser Untersuchung war es, die Ursachen hierfür aufzuspüren. Methodik 20 Dossiers mit Antidiabetika für die Behandlung von Diabetes mellitus Typ 2 wurden analysiert, deren Bewertungsverfahren zwischen Januar 2012 und Mai 2015 publiziert worden sind. Informationen, die sich auf die Größe der Zielpopulation beziehen, wurden extrahiert und verglichen. Basierend auf der Extraktionsliste wurde ein Kriterienkatalog entwickelt, um Gründe für unterschiedlich große Zielpopulationen zu kategorisieren. Ergebnisse Die Abschätzung der Größe der Zielpopulation erfolgte in der Regel auf der Basis einer Sekundärdatenanalyse von Arzneimittelverordnungen. Bei der Analyse dieser Daten zeigten sich große Unterschiede in den Annahmen und bei den Methoden. Wesentliche Gründe für die Unterschiede waren verschiedene Datenbanken, das betrachtete Zeitfenster, die Operationalisierung der Patienten mit Diabetes mellitus Typ 2, die Spezifikation der Zielpopulation, die Kontraindikationen laut Fachinformation, die Berücksichtigung von unentdeckten Patienten mit Diabetes mellitus Typ 2, die Hochrechnung der Stichprobe auf die Gesamtbevölkerung sowie der Anteil der Patienten, die gesetzlich krankenversichert sind. Es ist nicht möglich, den Einfluss einzelner Ursachen zu quantifizieren; vielmehr scheinen verschiedene Faktoren zu interagieren. Schlussfolgerung Es zeigte sich, dass die Annahmen und Methoden der verwendeten Datenbanken, die den Berechnungen in den Dossiers zugrunde liegen, dringend transparenter darzustellen sind. Abweichungen sind nicht vollständig vermeidbar, aber eine Harmonisierung der Methoden kann die Vergleichbarkeit der ermittelten Patientenzahlen erhöhen.

The aim of the study was assessing lameness prevalence in organic sows as well as identifying potential risk factors for lameness. The project focused on sows in organic farms with access to an outdoor run. Sows have been chosen since they are kept for a longer period of time as compared with fattening pigs and therefore influencing factors from the housing environment may have a greater impact on them. Furthermore, leg health is a prerequisite for productivity and longevity. In the preparatory phase, different gait scoring systems were be identified from the literature and tested with regard to reliability and feasibility in the on-farm context. Also, farms which are willing to cooperate (criteria for inclusion: minimum flock size 20 sows, certified since at least two years) were identified. 40 farms have been visited and lameness and leg health was assessed on an individual level. The final analysis is not finished yet, but this contribution shows a first overview over the lameness situation on the visited farms of organic pig breeding in Germany.

BACKGROUND:Results from existing studies indicate that different respondent groups' health state valuations in cost-utility analyses are not equivalent.OBJECTIVES:The objectives in our study were to analyse differences in health state valuations among three respondent groups in the context of medical rehabilitation in Germany.METHODS:Using the time trade-off (TTO) technique, valuations of EQ-5D-3L health states were obtained from patients with musculoskeletal diseases, healthy volunteers and health care professionals. We used linear mixed models to predict TTO utilities and specified and tested interaction effects.RESULTS:We identified statistically significant (p < 0.05) differences among the three groups in six out of 42 health states. On average, patients' TTO values were somewhat higher compared with other respondent groups. Most of these differences occurred in severe health states. Mean differences and mean absolute differences were 0.02 and 0.14 for patients vs healthy volunteers and 0.06 and 0.14 for patients vs health care professionals. Furthermore, significant effects among respondents were observed for seven of the 22 possible interactions describing differences between respondent groups. Coefficients associated with significant interaction effects ranged from 0.08 to 0.18 (absolute values).CONCLUSION:The results of our study suggest that TTO valuations of health states differ depending on the specific respondent group from which valuations are obtained. On average, these differences were small. However, researchers and decision makers should remain aware of these differences when interpreting incremental cost-utility assessments.

Der Herstellung langgereifter Rohwurste dienen kastrierte schwere Schweine zur Sicherstellung der benotigten Fettquantitat und -qualitat. Dazu werden auch im okologischen Landbau vor allem moderne Hybridtiere (Hy) verwendet, bei denen die Fettkriterien oftmals unzureichend ausfallen. Die Nutzung von alten, gefahrdeten Rassen, z.B. von Sattelschweinen (Sa), mit einer hohen de-novo Fettsynthesekapazitat konnte hier eine sinnvolle Alternative darstellen und gleichzeitig einen Beitrag zu deren Erhaltung leisten. Es wurden die Auswirkungen von drei Genotypen (Sa, Pietrain * Sa (PiSa), Hy) und zwei Raufuttervarianten (Kleegrassilage, Stroh) auf Mastleistung (ML), Schlachtkorperqualitat (SQ), Fleischqualitat (FQ), Fettsauremuster (FSM) und Produktqualitat der langgereiften Rohwurst (PQ) uberpruft (Schwalm et al., 2013a und 2013b). ML, SQ, FQ und FSM wurden signifikant durch den Genotyp, jedoch nicht nennenswert durch die Raufuttervariante beeinflusst. Hy zeigte die beste ML und Sa die schlechteste. Bei der FQ bestanden keine nennenswerten genotypischen Unterschiede, wahrend bei der SQ und dem FSM Sa am besten und Hy am wenigsten fur die Rohwurstherstellung geeignet erschien. Bei der PQ schnitt tendenziell Sa besser ab als Hy. Die PiSa-Herkunfte nahmen bei samtlichen Untersuchungskriterien eine mittlere Stellung ein. Es wird geschlussfolgert, dass die Kreuzung eines modernen Endstufenebers mit reinrassigen Sattelschweinsauen am besten geeignet zu sein scheint, alte, bedrohte Rassen mit Hilfe der Wertschopfung in einem Premiumsegment zu erhalten.