HIV AIDS length of stay outliers

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

3 Citations (Scopus)

Abstract

Costs with HIV/AIDS hospitalizations are one of the major financial burdens on healthcare systems worldwide. In Portugal, hospitalizations related to HIV infection are some of the most expensive and the second major diagnosis category, and also accounts for the greatest average length of stay. As a result, it is crucial to understand and identify HIV/AIDS hospital length of stay outliers. The objective of this study is to analyse HIV/AIDS length of stay high outliers during five consecutive years (2009-2013) and to identify its determinants for a specific HIV/AIDS diagnosis related group. To attain these objectives we will use a logistic regression model with random effects. (C) 2015 The Authors. Published by Elsevier B.V.

Original languageEnglish
Title of host publicationCONFERENCE ON ENTERPRISE INFORMATION SYSTEMS/INTERNATIONAL CONFERENCE ON PROJECT MANAGEMENT/CONFERENCE ON HEALTH AND SOCIAL CARE INFORMATION SYSTEMS AND TECHNOLOGIES, CENTERIS/PROJMAN / HCIST 2015
EditorsMM CruzCunha, J Varajao, R Rijo, R Martinho, P Schubert, A Boonstra, R Correia, R Berler
PublisherElsevier Science B.V., Inc
Pages984-992
Number of pages9
DOIs
Publication statusPublished - 2015
EventConference on ENTERprise Information Systems (CENTERIS) / International Conference on Project MANagement (ProjMAN) / International Conference on Health and Social Care Information Systems and Technologies (HCist) - Vilamoura, Portugal
Duration: 7 Oct 20159 Oct 2015

Publication series

NameProcedia Computer Science
PublisherELSEVIER SCIENCE BV
Volume64
ISSN (Print)1877-0509

Conference

ConferenceConference on ENTERprise Information Systems (CENTERIS) / International Conference on Project MANagement (ProjMAN) / International Conference on Health and Social Care Information Systems and Technologies (HCist)
CountryPortugal
CityVilamoura
Period7/10/159/10/15

Keywords

  • Hospital length of stay
  • outliers
  • random effects
  • HIV/AIDS
  • MIXTURE REGRESSION
  • INPATIENT LENGTH
  • PUBLIC-HEALTH

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