Background and Aim: Liver cirrhosis is characterized by high morbidity and mortality rates. This study was addressed to evaluate the epidemiological and economic impact of cirrhosis on hospitalizations in a large population in Italy. Methods: Epidemiological analysis was performed using hospital discharge sheets of 57,720 hospitalizations due to liver disease from 2006 to 2008, selected from the Veneto regional archive. In a sample of 100 randomly selected hospitalizations, a detailed cost analysis was performed and a comparison was made with sets of patients admitted for heart failure (HF) and chronic obstructive pulmonary disease (COPD). Results: Among patients with cirrhosis, ascites emerged as the most frequent cause of admission, followed by hepatic encephalopathy, hepatocellular carcinoma, and upper gastrointestinal bleeding. Encephalopathy and ascites were the complications with the highest rates of readmission. The detailed cost analysis of hospitalizations revealed that economic expenses in the set of patients admitted for cirrhosis were about 30% higher than those for patients admitted for HF or COPD, mainly due to the longer duration of hospitalization. Conclusions: Cirrhosis has a relevant epidemiological and economic impact on hospitalizations and preventive strategies for its clinical management are warranted.

The rehabilitation scheduling process consists of planning rehabilitation physiotherapy sessions for patients, by assigning proper operators to them in a certain time slot of a given day, taking into account several requirements and optimizations, e.g., patient's preferences and operator's work balancing. Being able to efficiently solve such problem is of upmost importance, in particular after the COVID-19 pandemic that significantly increased rehabilitation's needs.In this paper, we present a solution to rehabilitation scheduling based on Answer Set Programming (ASP), which proved to be an effective tool for solving practical scheduling problems. Results of experiments performed on both synthetic and real benchmarks, the latter provided by ICS Maugeri, show the effectiveness of our solution.

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A core part of the rehabilitation scheduling process consists of planning rehabilitation physiotherapy sessions for patients, by assigning proper operators to them in a certain time slot of a given day, taking into account several legal, medical and ethical requirements and optimizations, e.g., patient's preferences and operator's work balancing. Being able to efficiently solve such problem is of upmost importance, in particular after the COVID-19 pandemic that significantly increased rehabilitation's needs.In this paper, we present a two-phase solution to rehabilitation scheduling based on Answer Set Programming, which proved to be an effective tool for solving practical scheduling problems. We first present a general encoding, and then add domain specific optimizations. Results of experiments performed on both synthetic and real benchmarks, the latter provided by ICS Maugeri, show the effectiveness of our solution as well as the impact of our domain specific optimizations.Under consideration in Theory and Practice of Logic Programming (TPLP).

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