The Italian Health care System provides universal coverage for comprehensive health services and is mainly financed through general taxation. Since the early 1990s, a strong decentralization policy has been adopted in Italy and the state has gradually ceded its jurisdiction to regional governments, of which there are twenty. These regions now have political, administrative, fiscal and organizational responsibility for the provision of health care. This paper examines the different governance models that the regions have adopted and investigates the performance evaluation systems (PESs) associated with them, focusing on the experience of a network of ten regional governments that share the same PES. The article draws on the wide range of governance models and PESs in order to design a natural experiment. Through an analysis of 14 indicators measured in 2007 and in 2012 for all the regions, the study examines how different performance evaluation models are associated with different health care performances and whether the network-shared PES has made any difference to the results achieved by the regions involved. The initial results support the idea that systematic benchmarking and public disclosure of data are powerful tools to guarantee the balanced and sustained improvement of the health care systems, but only if they are integrated with the regional governance mechanisms.

Since 80's the introduction of New Public Management principles has promoted the use of performance measurement to drive a more efficient, effective and accountable public sector. The adoption of a sophisticated and comprehensive multidimensional performance measurement system, which looks beyond traditional financial measures, based on organization strategies, such as the balanced scorecard, has thus been suggested. This revolution in the public management came together with the devolution processes that involved most European public health systems. Set within this context, in the last decade, each of the twenty Italian regions developed its own management tools. Among others, the Tuscan performance evaluation system (PES) has been valued as a particularly innovative and comprehensive system. This paper reports the novel experience of the Tuscan PES; in particular, it measures PES effectiveness and discusses the critical factors that could have led to the PES success. Five are the critical success factors identified by researchers: the visual reporting system, the linkage between PES and CEO's reward system, the public disclosure of data, the high level of employees and managers involvement into the entire process and the strong political commitment. All those factors run together to achieve better results; however, the process of development of the system plays a pivotal role. Scholars suggest the use of a constructive approach in order to gain effective changes in human organization. According to this stream of literature, this paper contributes by the novel experience of the Tuscan PES in addressing as a further fruitful application of the constructivist approach in healthcare.

Background: The use of Patient Reported Experience Measures (PREMs) has great potential in healthcare service improvement, but a limited use. This paper presents an empirical case of PREMs innovation in Italy, to foster patient data use up to the ward level, by keeping strengths and addressing weaknesses of previous PREMs survey experiences. The paper reports key lessons learned in this ongoing experience of action research, directly involving practitioners. Methods: The aim of this paper is to present the results of an ongoing action research, encompassing the innovation of PREMs collection, reporting and use, currently adopted by 21 hospitals of two Italian regions. The continuous and systematic PREMs collection has been implemented between 2017 and 2019 and includes: a continuous web-based administration, using web-services; an augmented and positive questionnaire matching standard closed-ended questions with narrative sections; the inclusion and benchmarking of patient data within a shared performance evaluation system; public disclosure of aggregated anonymized data; a multi-level and real-time web-platform for reporting PREMs to professionals. The action research was carried out with practitioners in a real-life and complex context. The authors used multiple data sources and methods: observations, feedback of practitioners, collected during several workshops and meetings, and analysis of preliminary data on the survey implementation. Results: A continuous and systematic PREMs observatory was developed and adopted in two Italian regions. PREMs participation and response rates tend to increase over time, reaching stable percentages after the first months. Narrative feedback provide a 'positive narration' of episodes and behaviours that made the difference to patients and can inform quality improvement actions. Real-time reporting of quantitative and qualitative data is enabling a gratifying process of service improvement and people management at all the hospitals' levels. Conclusions: The PREMs presented in this paper has been recognized by healthcare professionals and managers as a strategic and positive tool for improving an actual use of PREMs at system and ward levels, by measuring and highlighting positive deviances, such as compassionate behaviours.

The impact of digitalization of health services has been profound and is expected to be even more profound in the future. It is important to evaluate whether digital health services contribute to health system goals in an optimal way. This should be done at the level of the service, not the ‘digital transformation’. Decisions to adopt new digital health services, at different levels of the health care system, are ideally based on evidence regarding their performance in light of health system goals. In order to evaluate this, a broad perspective should be taken in evaluations of digital health services. Attainment of the broad health system goals, including quality, efficiency and equity, are objectives against which to judge new digital health services. These goals in a broad sense are unaltered by the process of digitalization. Governance should be designed and tailored in such a way to capture all relevant changes in an adequate way. When evaluating digital health services many specific aspects need to be considered. Like for other innovations and (new) technologies, such promises may or may not materialize and potential benefits may also be accompanied by unintended and/or negative (side) effects in the short or long term. Hence, the introduction, implementation, use and funding of digital health technologies should be carefully evaluated and monitored. Governments should play a more active role in the further optimization both of the process of decision making (both at the central and decentral level) and the related outcomes. They need to find a balance between centralized and decentralized activity. Moreover, the broader preparation of the health care system to be able to deal with digitalization, from education, through financial and regulatory preconditions, to implementation of monitoring systems to monitor its effects on health system performance remains important.

Background: The COVID-19 pandemic is a complex global public health crisis presenting clinical, organisational and system-wide challenges. Different research perspectives on health are needed in order to manage and monitor this crisis. Performance intelligence is an approach that emphasises the need for different research perspectives in supporting health systems' decision-makers to determine policies based on well-informed choices. In this paper, we present the viewpoint of the Innovative Training Network for Healthcare Performance Intelligence Professionals (HealthPros) on how performance intelligence can be used during and after the COVID-19 pandemic. Discussion: A lack of standardised information, paired with limited discussion and alignment between countries contribute to uncertainty in decision-making in all countries. Consequently, a plethora of different non-data-driven and uncoordinated approaches to address the outbreak are noted worldwide. Comparative health system research is needed to help countries shape their response models in social care, public health, primary care, hospital care and long-term care through the different phases of the pandemic. There is a need in each phase to compare context-specific bundles of measures where the impact on health outcomes can be modelled using targeted data and advanced statistical methods. Performance intelligence can be pursued to compare data, construct indicators and identify optimal strategies. Embracing a system perspective will allow countries to take coordinated strategic decisions while mitigating the risk of system collapse.A framework for the development and implementation of performance intelligence has been outlined by the HealthPros Network and is of pertinence. Health systems need better and more timely data to govern through a pandemic-induced transition period where tensions between care needs, demand and capacity are exceptionally high worldwide. Health systems are challenged to ensure essential levels of healthcare towards all patients, including those who need routine assistance.