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Using individual-level administrative data, we investigate the spatial patterns of unexplained shares of health care expenditures (HCE) at the municipality level. The focus is on the elderly population in the Italian Region Friuli-Venezia Giulia observed over the period 2017-2019. The empirical analysis comprises two steps. First, random-effects two-part models are estimated to analyze the effect of age, morbidity, and death on the probability and amount of positive individual total HCE and its components. Second, the unexplained shares of HCE at the municipality level are examined to identify areas with under- or over-spending and substitution among services. Results confirm the existing findings on the determinants of HCE and reveal geographic patterns in the unexplained shares of expenditures. We identify clusters of municipalities with observed HCE higher than predicted for each type of service and clusters with substitution between home care and all other services. These findings are associated with the degree of urbanization of these areas and, consequently, with the ease of access to health care. This is crucial from a policy perspective, as it indicates specific policy targets for public health intervention.

As the burden of acute care on government budgets is mounting in many countries, documenting the evolution of health costs following patients’ hospital admission is essential for assessing overall hospital-related costs. In this paper, we investigate the short- and long-term effects of hospitalization on different types of health care expenditures. We specify and estimate a dynamic DID model using register data of the entire population of individuals aged 50–70 residing in Milan, Italy, over the period 2008–2017. We find evidence of a large and persistent effect of hospitalization on total health care expenditures, with future medical expenses mostly accounted for by inpatient care. Considering all health treatments, the overall effect is sizable and is about twice the cost of a single hospital admission. We show that chronically ill and disabled individuals require greater post-discharge medical assistance, especially for inpatient care, and that cardiovascular and oncological diseases together account for more than half of expenditures on future hospitalizations. Alternative out-of-hospital management practices are discussed as a post-admission cost-containment measure.

As the burden of acute care on government budgets is mounting in many countries, documenting the evolution of health costs following patients' hospital admission is essential for assessing overall hospital-related costs. In this paper, we investigate the short- and long-term effects of hospitalization on different types of health care expenditures. We specify and estimate a dynamic DID model using register data of the entire population of individuals aged 50-70 residing in Milan, Italy, over the period 2008-2017. We find evidence of a large and persistent effect of hospitalization on total health care expenditures, with future medical expenses mostly accounted for by inpatient care. Considering all health treatments, the overall effect is sizable and is about twice the cost of a single hospital admission. We show that chronically ill and disabled individuals require greater post-discharge medical assistance, especially for inpatient care, and that cardiovascular and oncological diseases together account for more than half of expenditures on future hospitalizations. Alternative out-of-hospital management practices are discussed as a post-admission cost-containment measure.

In questa tesi modelliamo l'evoluzione nel ciclo di vita delle spese sanitarie individuali (HCE), espresse in funzione del processo di invecchiamento, degli shock e delle condizioni di salute e della distanza dalla morte. Tutte le analisi sono condotte utilizzando un unico dataset, che permette di analizzare diversi tipi di servizi sanitari e diversi sottocampioni di individui. La popolazione di interesse è costituita da individui di età compresa tra i 50 e i 70 anni, la finestra di età in cui si verificano i primi eventi sanitari avversi. Nel primo capitolo, usiamo un two-way fixed effects model per esaminare l'effetto dell'età, della morbilità e della distanza al decesso (TTD) sulle spese sanitarie individuali. La stima viene effettuata includendo diversi controlli, compresi gli effetti fissi individuali e del medico di medicina generale. Indaghiamo anche in che misura le caratteristiche dei pazienti e dei medici di base contribuiscono alla variabilità complessiva delle spese tra gli individui. I nostri risultati principali mostrano che l'età, la morbilità e TTD sono tutti importanti determinanti della spesa e sono tra gli elementi che contribuiscono maggiormente alla variabilità della stessa tra gli individui. La spesa totale aumenta con l'età, e quest'ultima risulta essere correlata negativamente con il tempo alla morte, un risultato in contrasto con la “red herring” hypothesis. Tale aumento con l'età delle spese complessive è principalmente guidato dalle spese per i servizi extra-ospedalieri; al contrario, non si osserva alcuna differenza nei costi ospedalieri durante la durata l’arco di vita considerato, una volta presi in considerazione gli altri fattori. D'altra parte, le spese ospedaliere guidano principalmente i profili di morbilità e di fine vita della spesa totale. Per quanto riguarda l'analisi di eterogeneità, gli individui cronici e disabili con shock sanitari che richiedono l'ospedalizzazione sono quelli che gravano maggiormente sui cost, In this thesis, we model the life-cycle evolution of individual healthcare expenditures, expressed as a function of the aging process, health shocks and conditions, and distance to death. All the analyses are carried out by using a unique dataset, which allows us to focus on different types of healthcare services and different subsamples of individuals. The population of interest consists of individuals aged 50-70, the age window where the first adverse health events are expected to arise. In the first chapter, we use a two-way fixed effects model to examine the effect of age, morbidity, and time to death (TTD) on individual healthcare expenditures (HCE). The estimation is carried out by controlling for several confounding factors, including individual and General Practitioner (GP) fixed effects. We also investigate to what extent patients’ and GP’ characteristics contribute to the overall variability in expenditures among individuals. Our main results show that age, morbidity, and TTD are all important determinants of HCE and are among the elements that contribute most to the variability in HCE among individuals. Total HCE is increasing in age, with the latter found to be negatively correlated with the time to death, a result in contrast with the ‘red herring’ hypothesis. Such an increase with age of overall expenditures is mainly driven by expenses for out-of-hospital services; in contrast, no difference in hospital costs is observed over the considered lifespan once the other factors are taken into account. On the other hand, inpatient expenditures mainly drive the morbidity and end-of-life profiles of total HCE. Concerning heterogeneous analysis, we find that chronic and disabled individuals with health shocks requiring hospitalization are those who place the greatest burden on the costs borne by the Italian healthcare system. It suggests that the enhancement of preventive approaches before the onset of such shocks is a priority goal to reduce the incidence of l