Abstract
The Portuguese National Health Line, S24, is an initiative of the Portuguese Health Ministry which seeks to improve accessibility to health care and to rationalize the use of existing resources by directing users to the most appropriate institutions of the national public health services. This study describes and analyses the use of S24. For S24 data, the location attribute is an important source of information to describe its use. Consequently, this study analyses the number of calls received, at a municipal level, under two different spatial econometric approaches. This analysis is important for future development of decision support indicators in a hospital context, based on the economic impact of the use of this health line. Considering the discrete nature of data, the number of calls to S24 in each municipality is better modelled by a Poisson model, considering covariate information: demographic and socioeconomic information, characteristics of the Portuguese health system, and development indicators. In order to explain model spatial variability, the data autocorrelation can be explained in a Bayesian setting through different hierarchical log-Poisson regression models. A different approach uses an autoregressive methodology also for count data through a log-Poisson model with a spatial lag autocorrelation component, better framed under a Bayesian paradigm. With this empirical study, we find strong evidence of a spatial structure in data and obtain similar conclusions with both perspectives of analysis. This supports the view that the addition of a spatial structure to the model improves estimation, even in the case where some relevant covariates have been included. This chapter is a revised and expanded version of the paper: Simões, P., Carvalho, M.L., Aleixo, S., Gomes, S., Natário, I., A Spatial Econometric Analysis of the Calls to The Portuguese National Health Line, Econometrics, 5, 24, MDPI journals, 2017.
Original language | English |
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Title of host publication | Geospatial Technology for Human Well-Being and Health |
Editors | Fazlay S. Faruque |
Place of Publication | Cham |
Publisher | Springer |
Pages | 91-118 |
Number of pages | 28 |
ISBN (Electronic) | 978-3-030-71377-5 |
ISBN (Print) | 978-3-030-71376-8 |
DOIs | |
Publication status | Published - Mar 2022 |
Keywords
- Autoregressive model
- Bayesian inference
- Geographic variations
- Hierarchical model
- Spatial autocorrelation
- Spatial dependence
- Spatial econometrics
- Spatial statistics