Thesis title: An Evidence-Based care model to match the population's healthcare needs. A novel algorithm for planning healthcare service delivery in the community houses
This doctoral dissertation examines how healthcare services can be better organized in Italy, using the province of L’Aquila as a case study. The central theme is the application of the Hub and Spoke model, an organizational structure that has already been used in hospitals for emergency care and cancer treatment, but which is now being applied to community and territorial healthcare. The aim of this thesis is not only to describe this model but also to provide a practical tool, based on data analysis and computer algorithms, that can help policymakers decide where to place healthcare facilities and how to allocate staff efficiently.
Italy’s National Health Service (SSN) was established in 1978 to provide universal access to healthcare. At its foundation, the SSN was revolutionary: it was free at the point of use, funded by taxation, and based on the principle of equal access for all citizens. Over time, however, the system has been challenged by profound demographic and social changes. The Italian population is ageing, and older adults are more likely to suffer from multiple chronic diseases that require long-term and continuous care. At the same time, resources are limited, and there are strong differences between regions and even between municipalities in terms of service availability.
The COVID-19 pandemic made these weaknesses visible to everyone. During the emergency, hospitals quickly became overloaded, and many local health districts were unable to support patients effectively at home. Rural areas and mountain communities, such as those found in Abruzzo, suffered in particular because of long distances, poor infrastructure, and difficulties in coordinating services. This confirmed the need for a stronger, more flexible territorial healthcare system capable of guaranteeing proximity, prevention, and continuity of care.
In response, the Italian government introduced reforms supported by the European Union’s Recovery and Resilience Plan. Within this framework, more than fifteen billion euros have been dedicated to healthcare, with the goal of strengthening territorial networks, introducing telemedicine, and modernizing infrastructures. The official framework for these reforms was provided by Ministerial Decree 77/2022, which clearly defined standards for new territorial services and formally adopted the Hub and Spoke model as the guiding organizational principle.
The Hub and Spoke model is based on a simple idea: some services require larger, better-equipped centers, while others can be delivered in smaller facilities closer to where people live. In this model, the Hubs are larger facilities that concentrate resources, staff, and technologies. They are open for longer hours, offer a wider range of services, and are responsible for coordinating the entire network. The Spokes, on the other hand, are smaller and more widespread facilities that provide everyday services such as general practice, nursing, chronic disease monitoring, vaccinations, and health promotion.
The strength of the model lies in its balance: Hubs guarantee quality and efficiency, while Spokes guarantee accessibility and proximity. Digital technologies and telemedicine play a key role by linking the two levels and allowing information and consultations to be shared across the network. In principle, this system can provide both equity and sustainability: people in remote villages can access basic services locally, while more complex needs can be referred to the Hub without unnecessary duplication of resources.
The province of L’Aquila, managed by ASL 1, represents an ideal testing ground for this model. The area covers over 5,000 square kilometers, almost half of Abruzzo’s territory, and includes 108 municipalities. Many of these municipalities are small, scattered, and located in mountainous areas, often above 1,000 meters of altitude. Distances between towns are significant: travelling from one extreme of the province to the other can take several hours. In winter, snow and adverse weather conditions can further isolate communities.
This complex geography creates enormous difficulties for healthcare. Hospitals and larger centers are located in a few towns, while many small communities remain far from them. This makes it hard to guarantee equal access to healthcare for all residents. At the same time, the population is ageing and healthcare needs are growing. For these reasons, ASL 1 is a particularly challenging and significant context in which to apply the Hub and Spoke model.
The methodological approach developed in this dissertation was designed to transform complex demographic and healthcare data into a coherent territorial plan. To achieve this, the research relied on the Python programming language, which offers powerful tools for managing large datasets, performing statistical analysis, and visualizing results. The process began with the careful preparation of data. Demographic information on the population, including age distribution and population density, was combined with geographical data such as distances and travel times between municipalities, taken from official ISTAT sources. These elements were then integrated with healthcare activity data provided by ASL 1, which described the number and type of outpatient services delivered to residents in recent years.
Once the data had been harmonized into a single database, the next step was to define the territorial network of Hubs and Spokes. Each municipality in the province was assigned to a reference center according to objective criteria. Proximity was a decisive factor, measured not only in kilometers but also in travel time, which better reflects the real accessibility of services. At the same time, demographic thresholds were respected: each Hub was set to serve a maximum of 50,000 inhabitants, while each Spoke could serve up to 40,000. This ensured that no facility would be overloaded beyond its capacity. The result was a balanced and rational territorial map, which was subsequently represented through thematic cartography in order to visualize how municipalities were distributed across the network.
The research then turned to the quantification of healthcare services. Outpatient activity was analyzed for the years 2019, 2023, and 2024, with a particular focus on cardiology but also including specialties such as urology, gynecology, dermatology, and geriatrics. Each service type was associated with its average delivery time, so that raw numbers could be translated into an estimate of the total minutes of professional work required. This approach made it possible not only to describe how many services were delivered, but also to evaluate the workload imposed on specialists and facilities.
Finally, the integration of service demand with the territorial assignments made it possible to estimate how many hours of specialist work were required in each Hub and Spoke. A computational procedure then distributed this workload across doctors, taking into account contractual limits of thirty-six hours per week and a maximum of six hours per day. This allowed the model to transform statistical data into practical information about staffing needs, offering a concrete basis for planning the number of specialists required to guarantee adequate coverage across the province.
The model produced a detailed map of the province organized according to the Hub and Spoke model. In the Avezzano area, travel times were relatively short and population density higher, which made service accessibility better. In the L’Aquila area, the larger territorial extension and lower density resulted in longer travel times. The Sulmona area presented intermediate results, but some municipalities, such as Opi, still faced long journeys of around 50 minutes to reach their reference center. Despite these difficulties, almost 90% of municipalities were able to access their Hub or Spoke in less than 30 minutes, which is considered acceptable for territorial healthcare.
When service data were analyzed, cardiology emerged as one of the most requested specialties, reflecting the ageing population and the high prevalence of cardiovascular conditions. The analysis showed that Hubs such as L’Aquila and Sulmona required a larger number of specialists to cope with demand, while Spokes, although smaller, were essential to ensure that care remained close to local communities. The study demonstrated that staff requirements could be estimated realistically and that the distribution of specialists could be optimized to avoid both shortages and inefficiencies.
The implications of this research go beyond the province of L’Aquila. The thesis demonstrates that the Hub and Spoke model, when applied with rigorous data analysis, can create a healthcare system that is at once efficient, equitable, and sustainable. By quantifying service demand and translating it into staff requirements, the model provides policymakers with a tool for evidence-based planning. Instead of relying on intuition or political negotiation, decisions about where to build facilities and how many specialists to hire can be guided by transparent, measurable criteria.
The research also highlights the importance of considering geography and demography in healthcare planning. Territories are not all the same: mountain areas, rural regions, and densely populated urban centers require different solutions. A flexible, adaptive model such as the one proposed here is better equipped to deal with these differences.
The study acknowledges some limitations. The data used covered specific years and may not capture future trends. The estimation of workload was based on average service times, which may not reflect the variability of real-life clinical practice. Moreover, the focus was primarily on cardiology, leaving open the question of how the model could be extended to multiple specialties simultaneously.
Future research could build on this work by integrating quality-of-care indicators, patient satisfaction surveys, and longitudinal data to monitor how service demand evolves over time. It could also test the model in other regions of Italy or apply it to specialties such as oncology, pediatrics, or mental health.
In conclusion, this dissertation provides both a conceptual framework and a practical tool for the reorganization of healthcare services in Italy. By applying the Hub and Spoke model to ASL 1 Avezzano-Sulmona-L’Aquila, it shows that it is possible to reconcile accessibility, efficiency, and sustainability even in complex and challenging territories. The use of data-driven algorithms allows healthcare managers to make informed choices about where to place facilities and how to allocate human resources.
The study ultimately argues that Italy’s healthcare reforms will succeed only if they are accompanied by careful planning and continuous evaluation. The model presented in this thesis offers a concrete contribution in this direction. It demonstrates that universal healthcare, the founding principle of the SSN, can be preserved and even strengthened through innovation, digitalization, and intelligent resource allocation.