Dans un système de santé avec budget limité, l’efficience des différentes options thérapeutiques doit être comparée afin d’assurer une allocation optimale des ressources. À cette fin, l’analyse coût-utilité (ACU) est privilégiée par les agences d’évaluation des technologies de la santé et requiert des données pharmacoéconomiques telles que les coûts et les scores d’utilité. Toutefois, les données pharmacoéconomiques ne sont pas systématiquement collectées lors des essais contrôlés randomisés (ECR). Lorsqu’elles le sont, elles sont soumises aux limites des ECR affectant ainsi la validité externe des résultats. Cela a mené à l’émergence des études en pratique réelle (real-world evidence studies) comme évidence complémentaire aux ECR aux fins de remboursement. Les données en pratique réelle peuvent être des données primaires (recueillies spécifiquement pour répondre à un objectif particulier) ou des données secondaires (données déjà collectées pour répondre à d’autres objectifs). D’importantes données pharmacoéconomiques, telles que l’utilité, la perte de productivité et les coûts non médicaux, étant généralement manquantes dans les banques de données traditionnelles, les chercheurs en pharmacoéconomie doivent parfois générer leurs propres données. Néanmoins, il n’existe pas de lignes directrices spécifiques pour guider les chercheurs désirant générer des données pharmacoéconomiques en pratique réelle. Le but de cette thèse était d’étudier et contribuer à l’amélioration des pratiques méthodologiques pour la génération de données pharmacoéconomiques en pratique réelle. Précisément, l’objectif du volet 1 était donc de caractériser les pratiques méthodologiques des études collectant des données de pharmacoéconomie et d’évaluer la qualité des résultats obtenus. Une revue systématique de la littérature a permis de confirmer certaines craintes face aux études de pratique réelle, c’est-à-dire le manque de transparence et de crédibilité. Le volet 1 a mis de l’avant le besoin d’améliorer les méthodologies actuelles qui ne produisent pas toujours des résultats robustes, pouvant ainsi affecter la validité et la pertinence des évaluations économiques. Un cadre de recherche spécifique à la collecte de données pharmacoéconomiques en pratique réelle pourrait augmenter la qualité des résultats générés. L’objectif du volet 2 était donc d’identifier les lignes directrices spécifiques à la génération de données d’utilité. Ensuite, d’incorporer les bonnes pratiques méthodologiques dans une boîte à outils destinée spécifiquement aux investigateurs cherchant à générer des valeurs d’utilité en pratique réelle. Bien que cette thèse englobe plus largement l’ensemble des données pharmacoéconomiques, telles que les coûts et l’utilité, la boîte à outils se concentre sur les scores d’utilité uniquement. Il s’agit d’un premier pas vers des lignes directrices officielles fournissant des bonnes pratiques méthodologiques pour la conception et conduite d’études en pharmacoéconomie. Pour ce qui est du volet 3, l’objectif était de mettre en pratique la boîte à outils en rédigeant un protocole de recherche de qualité, pertinent et applicable à la réalité des chercheurs en pratique réelle. Précisément, d’utiliser les recommandations de la boîte à outils afin de mettre en place un devis d’étude et des procédures d’étude qui limitent le risque de biais. Cette thèse contribue à l’avancement des bonnes pratiques et sensibilise la communauté de chercheurs à viser un niveau hiérarchique d’évidence plus élevé. La standardisation des méthodologies pour générer des données pharmacoéconomiques en pratique réelle est un besoin qui demeure non comblé. / In a resource-constrained healthcare system, the effectiveness of various therapeutic interventions must be compared by the means of economic evaluations to ensure optimal resource allocation. The cost-utility analysis (CUA) is favored by health technology assessment (HTA) agencies, and requires health economics and outcomes research (HEOR) data such as costs and utilities. Although they have gained prominence, HEOR data are not systematically collected in randomized controlled trials (RCTs). Even if they were, RCTs are well-known to have inherent limitations leading to a low external validity. Consequently, real-world evidence (RWE) studies have been used as complementary evidence in reimbursement decision-making. Real-world data can be primary data (specifically collected to achieve a certain objective) or secondary data (data that have already been collected for other purposes). However, important HEOR data, such as utility scores, productivity and non-medical costs, are not routinely collected in traditional databases. Therefore, HEOR investigators may need to generate their own pharmacoeconomic data. Nevertheless, there is no single guideline for investigators seeking guidance on methodological steps to estimate HEOR data in a real-world setting. The goal of this thesis was to study and improve good practices for HEOR data generation in a real-world setting. Specifically, the objective of the first article was to characterize methodological practices for collecting HEOR data as well as critically appraise the quality of the results. The systematic literature review confirmed concerns about RWE studies, namely the lack of transparency and credibility. The first article highlighted the need for good practices as current methodologies may not generate robust estimates, thereby affecting the validity and relevance of economic evaluations. A research framework specifically designed for HEOR data collection in a real-world setting could help improve the quality of results. Thus, the objective of the second article was to review current recommendations for health state utility (HSU) generation, and incorporate methodological standards into a single toolbox intended for investigators seeking to collect HSU in a real-world setting. Although this thesis broadly encompasses HEOR data, such as costs and utilities, the toolbox focuses on utility scores only. This is a first step toward official guidelines providing good practice recommendations for designing and conducting HEOR studies. As for the third article, the objective was to use the toolbox to develop a study protocol that is relevant, realistic and of good methodological quality. The recommendations of the toolbox were followed to design the study and limit bias. This thesis provides good practices to help generate high quality HEOR estimates, and motivate investigators to improve the level of evidence to be generated. Standardization of RWE studies collecting HSU has yet to come.

Tesis por compendio / [ES] ¿Cómo es la atribución en un entorno de omnicanal? Se puede determinar una distinción importante en contraste con la atribución en un entorno multicanal. Además de proporcionar el proceso de análisis de marketing, una especificación del proceso estándar intersectorial para la minería de datos (CRISP¿DM), se utiliza un enfoque de método mixto secuencial para analizar la cuestión principal de la investigación. En el primer paso de esta investigación se analizan las características y los requisitos de atribución eficiente en un entorno omnicanal. A partir de entrevistas semiestructuradas con expertos y de un proceso de investigación bibliográfica holística estructurada, se identifica claramente la falta de un enfoque de atribución omnicanal. Los enfoques de atribución existentes se identifican mediante la realización de un proceso estructurado de revisión de la literatura. Estos enfoques identificados se evalúan aplicando los resultados de las entrevistas semiestructuradas con expertos, es decir, los requisitos y características de una atribución omnicanal eficiente. Ninguno de los enfoques de atribución identificados cumple con la mayoría de los requisitos de omnicanal analizados. Al tener la brecha de investigación ¿ la falta de un enfoque de atribución de omnicanales ¿ claramente identificada, se desarrolla un enfoque de atribución de omnicanales en la segunda parte de esta investigación presentada. Utilizando la metodología MAP, la principal laguna de investigación se llena proporcionando el Holistic Customer Journey (HCJ): una base de datos lista para el omni¿canal y un enfoque de atribución de omni¿canal correspondiente. Entre otras cosas, el enfoque de atribución desarrollado consiste en una clasificación de aprendizaje automático. Esta investigación presentada es la primera en utilizar información de casi 240.000.000 de conjuntos de datos de interacción, que contienen información entre dispositivos y entre plataformas. Todas las fuentes de datos subyacentes son proporcionadas por una de las plataformas inmobiliarias más grandes de Alemania. / [CA] Com és l'atribució en un entorn de omnicanal? Es pot determinar una distinció important en contrast amb l'atribució en un entorn multicanal. A més de proporcionar el procés d'anàlisi de màrqueting, una especificació del procés estàndard intersectorial per a la mineria de dades (CRISP¿DM), s'utilitza un enfocament de mètode mixt seqüencial per analitzar la qüestió principal de la investigació. En el primer pas d'aquesta investigació s'analitzen les característiques i els requisits d'atribució eficient en un entorn omnicanal. A partir d'entrevistes semiestructurades amb experts i d'un procés de recerca bibliogràfica holística estructurada, s'identifica clarament la falta d'un enfocament d'atribució omnicanal. Els enfocaments d'atribució existents s'identifiquen mitjançant la realització d'un procés estructurat de revisió de la literatura. Aquests enfocaments identificats s'avaluen aplicant els resultats de les entrevistes semiestructurades amb experts, és a dir, els requisits i característiques d'una atribució omnicanal eficient. Cap dels enfocaments d'atribució identificats compleix amb la majoria dels requisits de omnicanal analitzats. En tenir la bretxa de recerca ¿ la manca d'un enfocament d'atribució de omnicanales ¿ clarament identificada, es desenvolupa un enfocament d'atribució de omnicanales a la segona part d'aquesta investigació presentada. Utilitzant la metodologia MAP, la principal llacuna de recerca s'omple proporcionant el Holistic Customer Journey (HCJ): una base de dades a punt per al omni¿canal i un enfocament d'atribució de omni¿canal corresponent. Entre altres coses, l'enfocament d'atribució desenvolupat consisteix en una classificació d'aprenentatge automàtic. Aquesta investigació presentada és la primera a utilitzar informació de gairebé 240.000.000 de conjunts de dades d'interacció, que contenen informació entre dispositius i entre plataformes. Totes les fonts de dades subjacents són proporcionades per una de les plataformes immobiliàries més grans d'Alemanya. / [EN] What does attribution in an omni¿channel environment look like? A major distinction can be determined in contrast to attribution in a multi¿channel environment. Besides providing the Marketing Analytics Process, a specification of the Cross¿industry standard process for data mining (CRISP¿DM), a sequential mixed method approach is utilized to analyze the main research question. Within the first step of this presented research characteristics, and requirements of efficient attribution in an omni¿channel environment are analyzed. Based on semi¿structured expert interviews and a holistic structured literature research process, the lack of an omni¿channel attribution approach is clearly identified. Existing attribution approaches are identified by conducting the structured literature review process. Those identified approaches are evaluated by applying the results of the semi¿structured expert interviews - the requirements and characteristics of efficient omni¿channel attribution. None of the identified attribution approaches fulfill a majority of the analyzed omni¿channel requirements. By having the research gap - the lack of an omni¿channel attribution approach - clearly identifed, an omni¿channel attribution approach is developed in the second part of this presented research. Utilizing the MAP methodology, the main research gap is filled by providing the Holistic Customer Journey (HCJ): an omni¿channel ready data foundation and a corresponding omni¿channel attribution approach. Among other things the developed attribution approach consists of a machine learning classification. This presented research is the first to utilize information from almost 240.000.000 interaction data sets, containing crossdevice and cross¿platform information. All underlying data sources are provided by one of Germany's largest real¿estate platforms. / Nass, O. (2019). Optimizing Online Marketing Efficiency By Analyzing the Mutual Influence of Online Marketing Channels with Respect to Different Devices [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/122296 / Compendio

The central thesis of this dissertation is that by combining classical scheduling methodologies with those of inventory management and queueing theory we can better model, understand and solve complex real-world scheduling problems. In part II of this dissertation, we provide models of a realistic supply chain scheduling problem that capture both its combinatorial nature and its dependence on inventory availability. We present an extensive empirical evaluation of how well implementations of these models in commercially available software solve the problem. We are therefore able to address, within a specific problem, the need for scheduling to take into account related decision-making processes. In order to simultaneously deal with combinatorial and dynamic properties of real scheduling problems, in part III we propose to integrate queueing theory and deterministic scheduling. Firstly, by reviewing the queueing theory literature that deals with dynamic resource allocation and sequencing and outlining numerous future work directions, we build a strong foundation for the investigation of the integration of queueing theory and scheduling. Subsequently, we demonstrate that integration can take place on three levels: conceptual, theoretical and algorithmic. At the conceptual level, we combine concepts, ideas and problem settings from the two areas, showing that such combinations provide insights into the trade-off between long-run and short-run objectives. Next, we show that theoretical integration of queueing and scheduling can lead to long-run performance guarantees for scheduling algorithms that have previously been proved only for queueing policies. In particular, we are the first to prove, in two flow shop environments, the stability of a scheduling method that is based on the traditional scheduling literature and utilizes processing time information to make sequencing decisions. Finally, to address the algorithmic level of integration, we present, in an extensive future work chapter, one general approach for creating hybrid queueing/scheduling algorithms. To our knowledge, this dissertation is the first work that builds a framework for integrating queueing theory and scheduling. Motivated by characteristics of real problems, this dissertation takes a step toward extending scheduling research beyond traditional assumptions and addressing more realistic scheduling problems.

The central thesis of this dissertation is that by combining classical scheduling methodologies with those of inventory management and queueing theory we can better model, understand and solve complex real-world scheduling problems. In part II of this dissertation, we provide models of a realistic supply chain scheduling problem that capture both its combinatorial nature and its dependence on inventory availability. We present an extensive empirical evaluation of how well implementations of these models in commercially available software solve the problem. We are therefore able to address, within a specific problem, the need for scheduling to take into account related decision-making processes. In order to simultaneously deal with combinatorial and dynamic properties of real scheduling problems, in part III we propose to integrate queueing theory and deterministic scheduling. Firstly, by reviewing the queueing theory literature that deals with dynamic resource allocation and sequencing and outlining numerous future work directions, we build a strong foundation for the investigation of the integration of queueing theory and scheduling. Subsequently, we demonstrate that integration can take place on three levels: conceptual, theoretical and algorithmic. At the conceptual level, we combine concepts, ideas and problem settings from the two areas, showing that such combinations provide insights into the trade-off between long-run and short-run objectives. Next, we show that theoretical integration of queueing and scheduling can lead to long-run performance guarantees for scheduling algorithms that have previously been proved only for queueing policies. In particular, we are the first to prove, in two flow shop environments, the stability of a scheduling method that is based on the traditional scheduling literature and utilizes processing time information to make sequencing decisions. Finally, to address the algorithmic level of integration, we present, in an extensive future work chapter, one general approach for creating hybrid queueing/scheduling algorithms. To our knowledge, this dissertation is the first work that builds a framework for integrating queueing theory and scheduling. Motivated by characteristics of real problems, this dissertation takes a step toward extending scheduling research beyond traditional assumptions and addressing more realistic scheduling problems.

SLOVENE NATIONAL THEATRE IN LJUBLJANA Author Report Of The Diploma Work Author: Bc. Petr Hýl Supervisor: doc. ing. arch. Zdeněk Makovský