# Machine Learning for Evaluating Hospital Mobility: An Italian Case Study
## 1 Introduction  
Italy's National Health Service is steadfast in providing high-quality medical care to all citizens. However, the regionalized health structure introduces performance disparities across regions, prompting experts to scrutinize and benchmark regional health systems to discern models of excellence, areas needing improvement, and best practices [1]. Our analysis zeroes in on the hospital systems of Apulia and Emilia-Romagna, chosen for their distinct characteristics. Emilia-Romagna, as per the GIMBE Report 2023, is a frontrunrunner in delivering Essential Levels of Assistance (LEA), showcasing its prowproviding essential services. This region's success is partly attributed to the Guarantee System, ensuring quality, appropriateness, and uniformity in health service delivery, a domain where Emilia-Romagna shines (GIMBE Foundation, [[http://www.gimbe.org/](http://www.gimbe.org/)]([http://www.gimbe.org/](http://www.gimbe.org/)) (accessed on 20 March 2024)). Conversely, Apulia, with its unique history, demography, and geography, demonstrates remarkable adaptability and innovation in healthcare, tackling specific challenges head-on. The comparative study between Emilia-Romagna and Apulia aims not to rank their services but to reveal how differing contexts, resources, and strategies influence healthcare service efficiency and effectiveness. Emilia-Romagna leverages its extensive experience to offer proven solutions, whereas Apulia introduces innovative approaches to address unique challenges, potentially applicable in other settings. A pivotal aspect of our research is evaluating hospital efficiency through the lens of resident patient quality perception, considering Apulia and Emilia-Romagna as a unified territory for health mobility analysis. This methodology enables a nuanced assessment of healthcare service efficiency and quality, factoring in patient experiences and preferences in healthcare facility selection. Patient perceptions of hospital service quality are vital for elevating health standards. An analysis of Facebook reviews using machine learning techniques has established a significant correlation between hospital accreditation and online emotional expressions, emphasizing the importance of valuing patient feedback [2]. Additionally, the deployment of a specific conceptual framework has equipped hospital administrators with a robust tool for scrutinizing and enhancing service quality across various hospital settings [3]. These strategies highlight the critical need to integrate patient perspectives in healthcare service optimization, ensuring state-of-the-art, patient-centric care. The analysis of the territorial distribution of healthcare facilities and accessibility offers an interesting perspective on the importance of integrating the healthcare dimension into territorial planning to address inequalities in service access [4]. Furthermore, the study on healthcare inequalities and disparities in disadvantaged areas gathers evidence and field experiences, providing recommendations to tackle inequities and improve access to care [5], thus enriching our understanding of regional healthcare dynamics in Italy with examples and lessons from international contexts. Hospital efficiency is a cornerstone for ensuring quality healthcare in Italy. The Hub & Spoke network model, transient efficiency strategies, prudent management of hospital and intensive care beds, and the adoption of a prospective payment system are instrumental in promoting hospital efficiency, contributing to a more agile and sustainable funding model [6; 7; 8; 9]. These initiatives underscore Italy's commitment to a comprehensive health system renewal, aiming to bolster efficiency and better meet the needs of all citizens. The examination of perceived quality underscores the significance of considering patient hospitalization propensity as an insightful indicator. This propensity, reflecting on hospitalization outcomes and patient mobility, directly impacts the perceived quality of hospital services.