A Spatio-Temporal Auto-regressive Model for Generating Savings Calls to a Health Line

Paula Simões, M. Lucília Carvalho, Sandra Aleixo, Sérgio Gomes, Isabel Natário

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 Saúde24 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.

Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings
EditorsOsvaldo Gervasi, Bernady O. Apduhan, Beniamino Murgante, David Taniar, Carmelo Torre, Eufemia Tarantino, Ana Maria A.C. Rocha, Elena Stankova, Vladimir Korkhov, Sanjay Misra
PublisherSpringer Verlag
Pages81-96
Number of pages16
ISBN (Print)9783030243012
DOIs
Publication statusPublished - 1 Jan 2019
Event19th International Conference on Computational Science and Its Applications, ICCSA 2019 - Saint Petersburg, Russian Federation
Duration: 1 Jul 20194 Jul 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Volume11621 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Computational Science and Its Applications, ICCSA 2019
CountryRussian Federation
CitySaint Petersburg
Period1/07/194/07/19

Fingerprint

Spatio-temporal Model
Autoregressive Model
Health
Line
Health care
Econometrics
Siméon Denis Poisson
Economics
Spatio-temporal Data
Decision Support
Costs
Emergency
Healthcare
Space-time
Model

Keywords

  • Autoregressive models
  • Bayesian analysis
  • Poisson
  • Space-time correlation
  • Spatial econometrics

Cite this

Simões, P., Carvalho, M. L., Aleixo, S., Gomes, S., & Natário, I. (2019). A Spatio-Temporal Auto-regressive Model for Generating Savings Calls to a Health Line. In O. Gervasi, B. O. Apduhan, B. Murgante, D. Taniar, C. Torre, E. Tarantino, A. M. A. C. Rocha, E. Stankova, V. Korkhov, ... S. Misra (Eds.), Computational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings (pp. 81-96). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11621 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-24302-9_7
Simões, Paula ; Carvalho, M. Lucília ; Aleixo, Sandra ; Gomes, Sérgio ; Natário, Isabel. / A Spatio-Temporal Auto-regressive Model for Generating Savings Calls to a Health Line. Computational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings. editor / Osvaldo Gervasi ; Bernady O. Apduhan ; Beniamino Murgante ; David Taniar ; Carmelo Torre ; Eufemia Tarantino ; Ana Maria A.C. Rocha ; Elena Stankova ; Vladimir Korkhov ; Sanjay Misra. Springer Verlag, 2019. pp. 81-96 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Simões, P, Carvalho, ML, Aleixo, S, Gomes, S & Natário, I 2019, A Spatio-Temporal Auto-regressive Model for Generating Savings Calls to a Health Line. in O Gervasi, BO Apduhan, B Murgante, D Taniar, C Torre, E Tarantino, AMAC Rocha, E Stankova, V Korkhov & S Misra (eds), Computational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11621 LNCS, Springer Verlag, pp. 81-96, 19th International Conference on Computational Science and Its Applications, ICCSA 2019, Saint Petersburg, Russian Federation, 1/07/19. https://doi.org/10.1007/978-3-030-24302-9_7

A Spatio-Temporal Auto-regressive Model for Generating Savings Calls to a Health Line. / Simões, Paula; Carvalho, M. Lucília; Aleixo, Sandra; Gomes, Sérgio; Natário, Isabel.

Computational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings. ed. / Osvaldo Gervasi; Bernady O. Apduhan; Beniamino Murgante; David Taniar; Carmelo Torre; Eufemia Tarantino; Ana Maria A.C. Rocha; Elena Stankova; Vladimir Korkhov; Sanjay Misra. Springer Verlag, 2019. p. 81-96 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11621 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Aleixo, Sandra

AU - Gomes, Sérgio

AU - Natário, Isabel

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AB - 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 Saúde24 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.

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Simões P, Carvalho ML, Aleixo S, Gomes S, Natário I. A Spatio-Temporal Auto-regressive Model for Generating Savings Calls to a Health Line. In Gervasi O, Apduhan BO, Murgante B, Taniar D, Torre C, Tarantino E, Rocha AMAC, Stankova E, Korkhov V, Misra S, editors, Computational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings. Springer Verlag. 2019. p. 81-96. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-24302-9_7