Table 2.

Included survey and case study hospitals in Europe.

Heath Organization	Current Problems and Approach	Vision on Potential Application of AI	Expected Improvement—KPIs
University Hospital of Bern, Department of Obstetrics and Gynecology	Fetal assessment based on Cardiotocography (CTG) or electronic fetal monitoring (EFM) limitations.	Their vision is to develop a medical decision support system, which can assist obstetricians in accurately assessing the fetal state in clinical practice during labor.	Improvement of decision-making can improve fetal outcomes after delivery and avoid unnecessary medical interventions and their health implications for mother and fetus, as well as their economic implications. The KPIs of the AI application are: Fetal outcomes, measured by clinical adaptation (APGAR score) and hypoxia (measured by arterial pH), Invasive interventions for prematurely ending the delivery process, such as instrumental delivery or cesarean section, Economical costs of delivery.
Kuopio University Hospital	Currently, the diagnosis of coronary heart disease has changed towards the non-invasive imaging, which has led to increasing number of patients scheduled to CCTA. Interpretation of CCTA is affected by the image quality, experience of the doctor and by other issues, which can in terms lead to unnecessary repeated or additive diagnostic imaging.	The motivation is to develop an automatic AI-based analysis system for the coronary computed tomography angiography (CCTA): To enhance diagnostic accuracy of CCTA and to guide clinical decision making. Interpretation of CCTA will be systematically guided by the standard AI-based analysis system.	The patients need only one diagnostic method and the workflow of the interpretation of CCTA become more fluent. Relevant KPIs are: Increased number of CCTA imaging in one center, Improved patient convenience, safety and decreased health care costs, Improved effectiveness leads to shorter waiting times and shortened queues.
Hospital of Bozen	Limitations on healthcare resources management and chronic care pathways definition	AI tools to support the definition and scheduling of the different laboratory tests, medical examinations and hospitalization which affect STHA patients, personnel, equipment and resources inside and outside the hospital and located in multiple areas of the geographical territory of its responsibility	Ease the management of healthcare resources with a particular focus on rheumatological diseases and diabetes as chronic diseases. Relevant KPIs are: Decrease waiting time to access to scheduled medical examinations and labor tests, Average cost to provide the healthcare services to the chronic care population, Quality of the medical treatment, e.g., percentage of re-hospitalized patients.
La Fe University Hospital	Chronic diseases (CDs) represent the major cost of morbidity and mortality and lead to 86% of all deaths. In Europe, these account for more than 75% of the healthcare burden with a cost for the economy of €700 billion per year.	AI will help to: Improve the management of chronic conditions and multimorbidity in the face of aging population and its implication on public health; Contain the impact and global burden of chronic conditions, multimorbidity and frailty on individual quality of life and on healthcare systems; Strength the clinical management of complex chronic conditions and multimorbidity having a better understanding of the individual prognosis and disease evolution, and targeting personalized interventions.	Optimization of resources and the clinical flow of chronic patients at Hospital. Relevant KPIs are: Efficiency on the allocation and consumption of resources, Right assignment of chronic patient to care pathway, Decrease in turnaround time, Selection of right pathway, Avoidable episodes of care inadequate use.
Federico II University of Naples	Today CVD is the leading cause of death in Europe; presently 47% of all deaths in Europe and 40% of all deaths in the European Union (EU) are attributable to CVD. This means that across Europe as a whole 4 million deaths per year currently occur due to CVD, of which 1.9 million are in the European Union	Use of AI may help clinicians in problem solving and patient’s management. AI process may be used to improve process of health care management with specific regards to resource allocation, patient management.	Rapid assessment of correct management strategy. Relevant KPIs are: Improvement of timeliness in critical event treatment, Reduction of ambulatorial visits, Forecasting of avoidable critical conditions.
Odense University Hospital	Maintain high quality treatment for our patients in a demographic development scenario and increasing chronic conditions	Need to rely on AI and robots to ensure quality level and improve security in repetitive tasks, while alleviating staffing challenges.	Optimize handling of transports and logistics. Relevant KIPs are: Improve timing for transportation of patients or samples. Release of staffing resources to other tasks/areas. As well as an improved working environment for staff.