# Delving into public-expenditure elasticity: Evidence from a National Health Service acute-care hospital network

## TL;DR

This study examines how hospital spending in Spain's healthcare system responds to different factors based on hospital type, aiming to improve financial sustainability.

## Contribution

The study introduces a dynamic analysis of hospital expenditure elasticity across different hospital clusters using SARIMAX models and nationwide data.

## Key findings

- Hospitals treating severe cases are most sensitive to quasi-price factors like bed numbers.
- Smaller hospitals show higher elasticity to quantity factors, with expenditure increasing more than proportionally.
- Hospital clusters differ in expenditure responsiveness, suggesting tailored strategies for optimizing spending.

## Abstract

The sustainability of public hospital financing in Spain is a recurring issue, given its representativeness in annual public healthcare budgets which must adapt to the macroeconomic challenges that influence the evolution of spending. Knowing whether the responsiveness of hospital expenditure to its determinants (need, utilisation, and quasi-prices) varies according to the type of hospital could help better design strategies aimed at optimising performance.

Using SARIMAX models, we dynamically assess unique nationwide monthly activity data over a 14-year period from 274 acute-care hospitals in the Spanish National Health Service network, clustering these providers according to the average severity of the episodes treated.

All groups showed seasonal patterns and increasing trends in the evolution of expenditure. The fourth quartile of hospitals, treating the most severe episodes and accounting for more than 50% of expenditure, is the most sensitive to quasi-price factors, particularly the number of beds per hospital. Meanwhile, the first quartile of hospitals, which treat the least severe episodes and account for 10% of expenditure, is most sensitive to quantity factors, for which expenditure showed an elasticity above one, while factors of production were not affected.

Belonging to one or another cluster of hospitals means that the determinants of expenditure have a different impact and intensity. The system should focus on these differences in order to optimally modulate expenditure not only according to the needs of the population, but also according to the macroeconomic situation, while leaving hospitals room for manoeuvre in case of unforeseen events. The findings suggest strengthening a network of smaller hospitals (Group 1)–closer to their reference population, focused on managing and responding to chronicity and stabilising acute events–prior to transfer to tertiary hospitals (Group 4)–larger but appropriately sized, specialising in solving acute and complex health problems–when needed.