Paper Info
Title
A Spatio-Temporal Auto-Regressive Model For Generating Savings Calls To A Health Line
Abstract
Urgency admission is one of the most important factors regarding hospital costs, which can possibly be mitigated by the use of national health lines such as the Portuguese Saude24 line (S24). Aiming future development of decision support indicators in a hospital savings context, based on the economic impact of the use of S24 rather than hospital urgency services, this study investigates spatio-temporal dependencies of the number of S24 calls generating savings in each Portuguese municipality, over the period 2010-2016, under an autoregressive approach. An econometric analysis of the savings obtained by the use of S24 is also carried out considering a savings index.Combining insights from classical spatial econometrics and from the analysis of spatio-temporal data, novel Bayesian Poisson spatio-temporal lag models are presented and applied in this paper. This extends to time the ideas of a Bayesian Poisson spatial lag model, considering both a parametric and a non-parametic structure for time and space-time effects.The results obtained for the savings index reveal that, over the last seven years, there has been a more comprehensive spatial effectiveness of the S24 line in solving the non-urgent emergency situations, that could be handled by primary health care services or in a self care basis.
Year
DOI
Venue
2019
10.1007/978-3-030-24302-9_7
COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2019, PT III: 19TH INTERNATIONAL CONFERENCE, SAINT PETERSBURG, RUSSIA, JULY 1-4, 2019, PROCEEDINGS, PART III
Keywords
DocType
Volume
Bayesian analysis, Spatial econometrics, Autoregressive models, Space-time correlation, Poisson
Conference
11621
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Paula Simões100.34
M. Lucília Carvalho200.34
Sandra M. Aleixo311.98
Sérgio Gomes400.34
Isabel Natário500.34