The healthcare scenario in developed countries is changing deeply: patients, who are frequently affected by multi-pathological chronic conditions, have risen their expectations. Simultaneously, there exist dramatic financial pressures which require healthcare organizations to provide more and better services with equal (or decreasing) resources. In response to these challenges, hospitals are facing radical transformations by bridging, redesigning and engaging their organization and staff. This study has the ambitious aim to shed light and clearly label the trends of change hospitals are enhancing in developed economies, in order to fully understand the presence of common trends and which organizational models and features are inspiring the most innovative organizations. The purpose is to make stock of what is known in the field of hospital organization about how hospitals are changing, as well as of how such change may be implemented effectively through managerial tools. To do so the methodology adopted integrates a systematic literature review to a wider engaged research approach. Evidence suggests that the three main pillars of change of the system are given by the progressive patient care model, the patient-centered approach and the lean approach. However, there emerge a number of gaps in what is known about how to exploit drivers of change and their effects. This study confirms that efforts in literature are concentrated in analyzing circumscribed experiences in the implementation of new models and approaches, failing therefore to extend the analysis at the organizational and inter-organizational level in order to legitimately draw consequences to be generalized. There seem to be a number of “gaps” in what is known about how to exploit drivers of change and their effects, suggesting that the research approach privileged till now fails in providing a clear guidance to policy makers and to organizations’ management on how to concretely and effectively implement new organizational models.

Objectives: Artificial intelligence (AI)-based health technologies (AIHTs) have already been applied in clinical practice. However, there is currently no standardized framework for evaluating them based on the principles of health technology assessment (HTA). Methods: A two-round Delphi survey was distributed to a panel of experts to determine the significance of incorporating topics outlined in the EUnetHTA Core Model and twenty additional ones identified through literature reviews. Each panelist assigned scores to each topic. Topics were categorized as critical to include (scores 7–9), important but not critical (scores 4–6), and not important (scores 1–3). A 70 percent cutoff was used to determine high agreement. Results: Our panel of 46 experts indicated that 48 out of the 65 proposed topics are critical and should be included in an HTA framework for AIHTs. Among the ten most crucial topics, the following emerged: accuracy of the AI model (97.78 percent), patient safety (95.65 percent), benefit–harm balance evaluated from an ethical standpoint (95.56 percent), and bias in data (91.30 percent). Importantly, our findings highlight that the Core Model is insufficient in capturing all relevant topics for AI-based technologies, as 14 out of the additional 20 topics were identified as crucial. Conclusion: It is imperative to determine the level of agreement on AI-relevant HTA topics to establish a robust assessment framework. This framework will play a foundational role in evaluating AI tools for the early diagnosis of dementia, which is the focus of the European project AI-Mind currently being developed.

Background: Multiple sclerosis imposes a heavy burden on the person who suffers from it and on the relatives, due to the caregiving load involved. The objective was to analyse whether the inclusion of social costs in economic evaluations of multiple sclerosis-related interventions changed results and/or conclusions. Methods: A systematic review was launched using Medline and the Cost-Effectiveness Analysis Registry of Tufts University (2000–2019). Included studies should: (1) be an original study published in a scientific journal, (2) be an economic evaluation of any multiple sclerosis-related intervention, (3) include productivity losses and/or informal care costs (social costs), (4) be written in English, (5) use quality-adjusted life years as outcome, and (6) separate the results according to the perspective applied. Results: Twenty-nine articles were selected, resulting in 67 economic evaluation estimations. Social costs were included in 47% of the studies. Productivity losses were assessed in 90% of the estimations (the human capital approach was the most frequently used method), whereas informal care costs were included in nearly two-thirds of the estimations (applying the opportunity and the replacement-cost methods equally). The inclusion of social costs modified the figures for incremental costs in 15 estimations, leading to a change in the conclusions in 10 estimations, 6 of them changing from not recommended from the healthcare perspective to implemented from the societal perspective. The inclusion of social costs also altered the results from cost-effective to dominant in five additional estimations. Conclusions: The inclusion of social costs affected the results/conclusions in multiple sclerosis-related interventions, helping to identify the most appropriate interventions for reducing its economic burden from a broader perspective.

The progressive ageing of the working population and the increase in related chronic diseases tend to affect working capacity. The aim of this study was to evaluate a Workplace Disability Management Program (WDMP) within a pediatric hospital. Absenteeism due to healthcare workers’ (HCWs) pre- and post- WDMP and the related costs were used for the program evaluation. The Return on Investment (ROI), the Break-Even Analysis (BEA) and the value of the average annual productivity of HCWs who took advantage of the Disability Management (DM) interventions to assess the economic impact of the program, were also used. The HCWs enrolled in the program were 131 (approximately 4% of hospital staff), of which 89.7% females and with an average age of 50.4 years (SD ± 8.99). Sick leave days of the HCWs involved decreased by 66.6% in the year following the end of WDMP compared to the previous one (p < 0.001). The total estimated cost reduction of absenteeism is 427,896€ over a year. ROI was equal to 27.66€. BEA indicated that the break-even point was reached by implementing the program on 3.27 HCWs. The program evaluation demonstrated the particular effectiveness of the implemented WDMP model, acting positively on the variables that affect productivity and the limitation to work.