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Background Value-based healthcare (VBHC) is a conceptual framework to improve the value of healthcare by health, care-process and economic outcomes. Benchmarking should provide useful information to identify best practices and therefore a good instrument to improve quality across healthcare organizations. This paper aims to provide a proof-of-concept of the feasibility of an international VBHC benchmarking in breast cancer, with the ultimate aim of being used to share best practices with a data-driven approach among healthcare organizations from different health systems. Methods In the VOICE community—a European healthcare centre cluster intending to address VBHC from theory to practice—information on patient-reported, clinical-related, care-process-related and economic-related outcomes were collected. Patient archetypes were identified using clustering techniques and an indicator set following a modified Delphi was defined. Benchmarking was performed using regression models controlling for patient archetypes and socio-demographic characteristics. Results Six hundred and ninety patients from six healthcare centres were included. A set of 50 health, care-process and economic indicators was distilled for benchmarking. Statistically significant differences across sites have been found in most health outcomes, half of the care-process indicators, and all economic indicators, allowing for identifying the best and worst performers. Conclusions To the best of our knowledge, this is the first international experience providing evidence to be used with VBHC benchmarking intention. Differences in indicators across healthcare centres should be used to identify best practices and improve healthcare quality following further research. Applied methods might help to move forward with VBHC benchmarking in other medical conditions. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic has brought great financial problems to the whole world. The football industry also felt the negative effects. A two-month break from not playing football matches affected all football factors. The clubs lost income from various sources, among which they were most financially affected by the lack of fees for TV rights and the loss of earnings from the game itself. The Covid-19 pandemic caused problems even after the return of football competitions, among other things due to the ban on spectators coming to the stadiums. There was no income from nonfootball sources, such as concerts and other events held at football stadiums. Due to the firm connection between the media, the economy and football, the aim of this paper is to present, from an economic and media point of view, the situation in which the football industry in Europe finds itself under the influence of the Covid-19 pandemic. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive network fuzzy inference system (ANFIS) based decision support system that can provide European policy makers with systematic guidance in allocating and prioritizing scant public resources, whilst accomplishing the best growth performance at a regional level. We do so by taking the stance of the Smart Specialization Strategies, which aim at consolidating the regional strengths and make effective and efficient use of public investment in R&D. By applying the ANFIS method, we were able to understand how—and to what extent—the competitiveness drivers promoted technological development and how the latter contributes to the economic growth of European regions. We used socio–economic, spatial, and patent-based data to train, test, and validate the models. What emerges is that an increase of R&D investments enhances the regional employment rate and the number of patents per capita; in turn, by taking into account the several combinations of specialization and diversification indicators, this leads to an increase of the regional gross domestic product (GDP). [ABSTRACT FROM AUTHOR]