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The hospital emigration to another region in the light of the environmental, social and governance model in Italy during the period 2004-2021.
- Source :
-
BMC Public Health . 7/15/2024, Vol. 24 Issue 1, p1-34. 34p. - Publication Year :
- 2024
-
Abstract
- The following article presents an analysis of the impact of the Environmental, Social and Governance-ESG determinants on Hospital Emigration to Another Region-HEAR in the Italian regions in the period 2004-2021. The data are analysed using Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled Ordinary Least Squares-OLS, Weighted Least Squares-WLS, and Dynamic Panel at 1 Stage. Furthermore, to control endogeneity we also created instrumental variable models for each component of the ESG model. Results show that HEAR is negatively associated to the E, S and G component within the ESG model. The data were subjected to clustering with a k-Means algorithm optimized with the Silhouette coefficient. The optimal clustering with k=2 is compared to the sub-optimal cluster with k=3. The results suggest a negative relationship between the resident population and hospital emigration at regional level. Finally, a prediction is proposed with machine learning algorithms classified based on statistical performance. The results show that the Artificial Neural Network-ANN algorithm is the best predictor. The ANN predictions are critically analyzed in light of health economic policy directions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14712458
- Volume :
- 24
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- BMC Public Health
- Publication Type :
- Academic Journal
- Accession number :
- 178463496
- Full Text :
- https://doi.org/10.1186/s12889-024-19369-x