Application of statistical and decision-analytic models for evidence synthesis for decision-making in public health and the healthcare sector

Download statistics - Document (COUNTER):

Treskova, Marina: Application of statistical and decision-analytic models for evidence synthesis for decision-making in public health and the healthcare sector. Hannover : Gottfried Wilhelm Leibniz Universität, Diss., 2020, IV, 399 S. DOI:

Selected time period:


Sum total of downloads: 347

With the awareness that healthcare is a limited resource, decision-makers are challenged to allocate it rationally and efficiently. Health economic methods of evidence synthesis for decision-making are useful to quantify healthcare resource utilisation, critically evaluate different interventions and ensure the implementation of the most effective or cost-effective strategy. The nine studies included in the present cumulative doctoral thesis aim to demonstrate the capability of statistical and decision-analytic modelling techniques to inform and support rational healthcare decision-making in Germany. Five studies apply statistical modelling in analyses of public health and health economic data. They show that thedeveloped models are valuable instruments for examining patterns in the data andgenerating knowledge from observable data which can further be used in devising disease management and care programs as well as economic evaluations.Further, two health economic evaluations, which adopt the decision-analytic-modelling approach, show that decision-analytic modelling is a powerful tool to represent the epidemiology of infectious and non-infectious diseases on a population level, quantify the burden of the diseases, generalise the outcomes of clinical trials, and predict how the interventions can change the impact of the diseases on the health of the population. Additionally, two literature reviews examine the application of decision-analytic modelling in health economic evaluations. The first study reviews and empirically analyses health technology assessments by the German Institute for Medical Documentation and Informationand demonstrates that the application of decision-analytic models improves the evidence produced for policy-making in the healthcare sector in Germany. The second systematic review focuses on methodological choices made in constructing decision-analytic models and explains how critically the structural and parametrical assumptions can influence the final message of the economic evaluations and shows that building a validated, reliable model as well as the transparent reporting is of high priority in facilitating the communication and implementation of the most cost-effective course of action. Overall, the present thesis shows the relevance and advantage of the application of models in synthesising evidence for decision-making. The included studies contribute to the current and future development of the methods used to address the problems of health economic efficiency. Further advances in the computational modelling techniques and data collection, from one side, will ease the decision-making process, but, from another side, will require increasing competence and understanding within the decision-making bodies.
License of this version: Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.
Document Type: doctoralThesis
Publishing status: publishedVersion
Issue Date: 2020
Appears in Collections:Wirtschaftswissenschaftliche Fakultät

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 89 25.65%
2 image of flag of United States United States 68 19.60%
3 image of flag of No geo information available No geo information available 41 11.82%
4 image of flag of Russian Federation Russian Federation 38 10.95%
5 image of flag of Czech Republic Czech Republic 26 7.49%
6 image of flag of China China 12 3.46%
7 image of flag of Romania Romania 8 2.31%
8 image of flag of India India 8 2.31%
9 image of flag of France France 7 2.02%
10 image of flag of United Kingdom United Kingdom 5 1.44%
    other countries 45 12.97%

Further download figures and rankings:


Zur Erhebung der Downloadstatistiken kommen entsprechend dem „COUNTER Code of Practice for e-Resources“ international anerkannte Regeln und Normen zur Anwendung. COUNTER ist eine internationale Non-Profit-Organisation, in der Bibliotheksverbände, Datenbankanbieter und Verlage gemeinsam an Standards zur Erhebung, Speicherung und Verarbeitung von Nutzungsdaten elektronischer Ressourcen arbeiten, welche so Objektivität und Vergleichbarkeit gewährleisten sollen. Es werden hierbei ausschließlich Zugriffe auf die entsprechenden Volltexte ausgewertet, keine Aufrufe der Website an sich.

Search the repository