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Detection of Adverse Events Through Hospital Administrative Data

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Recent Advances in Information Systems and Technologies (WorldCIST 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 570))

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Abstract

This study aims to estimate and describe the incidence of adverse events (AE) registered in Portuguese public hospitals and consequently to determine the feasibility of using hospital administrative data as a tool for AE surveillance. A retrospective observational study using hospital administrative data was performed to detect the incidence of AE based on a selection of ICD-9-CM codes (diagnoses and external causes). All episodes in public hospitals in the period 2000–2010 were included. AE were divided in three main categories: complications of surgical or medical procedures, misadventures of surgical and medical care, and adverse drug events (ADE). The ADE subgroup was further subdivided in: poisoning, late effect, and adverse drug reaction. Over the studied period, the algorithm was able to detect 543,242 episodes with AE events (3.7% of all episodes), with an in-hospital mortality rate of 6.3%, and a median length-of-stay of 8 days. In a scenario of underreporting of AE, this administrative data approach in an important complement to the other existing surveillance techniques.

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Acknowledgments

The authors would like to thank the support given by the Project “NORTE-01-0145-FEDER-000016” (NanoSTIMA), financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF). The authors wish also to thank the Portuguese Ministry of Health’s Authority for Health Services (Administração Central do Sistema de Saúde I. P. – ACSS) for providing access to national hospitalizations data.

Author information

Authors and Affiliations

  1. Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS), Faculty of Medicine of the University of Porto (FMUP), Porto, Portugal

    Bernardo Marques, Bernardo Sousa-Pinto, Tiago Silva-Costa, Fernando Lopes & Alberto Freitas

  2. CINTESIS - Center for Health Technology and Services Research, Porto, Portugal

    Bernardo Marques, Bernardo Sousa-Pinto, Tiago Silva-Costa, Fernando Lopes & Alberto Freitas

Authors
  1. Bernardo Marques
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  2. Bernardo Sousa-Pinto
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  3. Tiago Silva-Costa
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  4. Fernando Lopes
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  5. Alberto Freitas
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Corresponding author

Correspondence to Alberto Freitas .

Editor information

Editors and Affiliations

  1. DEI/FCT, Universidade de Coimbra, Coimbra, Baixo Mondego, Portugal

    Álvaro Rocha

  2. Nova IMS, Universidade Nova de Lisboa, Lisboa, Portugal

    Ana Maria Correia

  3. College of Engineering, The Ohio State University, Columbus, Ohio, USA

    Hojjat Adeli

  4. DSI/EEUM, Universidade do Minho, Guimarães, Portugal

    Luís Paulo Reis

  5. DIMES, Università della Calabria, Arcavacata di Rende, Italy

    Sandra Costanzo

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Marques, B., Sousa-Pinto, B., Silva-Costa, T., Lopes, F., Freitas, A. (2017). Detection of Adverse Events Through Hospital Administrative Data. In: Rocha, Á., Correia, A., Adeli, H., Reis, L., Costanzo, S. (eds) Recent Advances in Information Systems and Technologies. WorldCIST 2017. Advances in Intelligent Systems and Computing, vol 570. Springer, Cham. https://doi.org/10.1007/978-3-319-56538-5_83

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  • DOI: https://doi.org/10.1007/978-3-319-56538-5_83

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56537-8

  • Online ISBN: 978-3-319-56538-5

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