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Predictive Models for Hospital Bed Management Using Data Mining Techniques

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Abstract

It is clear that the failures found in hospital management are usually related to the lack of information and insufficient resources management. The use of Data Mining (DM) can contribute to overcome these limitations in order to identify relevant data on patient’s management and providing important information for managers to support their decisions.

Throughout this study, were induced DM models capable to make predictions in a real environment using real data. For this, was adopted the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology. Three distinct techniques were considered: Decision Trees (DT), Naïve Bayes (NB) and Support Vector Machine (SVM) to perform classification tasks. This work explored the possibility to predict the number of patient discharges using only the number of discharges veirifed in the past. The models developed are able to predict the number of patient discharges per week with acuity values ranging from ≈82.69% to ≈94.23%. The use of these models can improve the efficiency of the administration of hospital beds. An accurate forecasting of discharges allows a better estimate of the beds available for the coming weeks.

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References

  1. Santos, M., Azevedo, C.: Data Mining Descoberta do conhecimento em base de dados. FCA - Editora de Informática, Lda (2005)

    Google Scholar 

  2. Santos, M., Boa, M., Portela, F., Silva, Á., Rua, F.: Real-time prediction of organ failure and outcome in intensive medicine. In: 2010 5th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1–6 (2010)

    Google Scholar 

  3. Koh, H., Tan, G.: Data mining applications in healthcare. J. Healthc Inf. Manag. 19(2), 64–72 (2005)

    Google Scholar 

  4. WHO, Expert Committee on Health Statistics, 261 (1963)

    Google Scholar 

  5. Santos, I., Arruda, J.: Análise do Perfil Profissional dos Gestores dos Hospitais Particulares da Cidade de Aracaju- SE. Revista Eletronica da Faculdade José Augusto Vieira Na-77 (2012)

    Google Scholar 

  6. Proença, J., Vaz, A., Escoval, A., Candoso, F., Ferro, D., Carapeto, C., Costa, R., Roeslin, V.: O Hospital Português. Vida Económica-Conferforum (2000)

    Google Scholar 

  7. Neves, M.: Os Médicos vão ter de ser os motores da reforma do sistema. Revista Portuguesa de Gestão & Saúde (5) (2011)

    Google Scholar 

  8. Yang, G., Sun, L., Lin, X.: Six-stage Hospital Beds Arrangement Management System. presented at the Management and Service Science (2010)

    Google Scholar 

  9. Dwivedi, A., Bali, R., Naguib, R.: Building New Healthcare Management Paradigms: A Case for Healthcare Knowledge Management. presented at the Healthcare Knowledge Management Issues, Advances, and Successes (2006)

    Google Scholar 

  10. Bose, R.: Knowledge management-enabled health care management systems: capabilities, infrastructure, and decision-support. Expert Systems with Applications 24(1), 59–71 (2003)

    Article  Google Scholar 

  11. Tsumoto, S., Hirano, S.: Data mining in hospital information system for hospital management. presented at the ICME International Conference on Complex Medical Engineering, CME 2009, pp. 1–5 (2009)

    Google Scholar 

  12. Tsumoto, S., Hirano, S.: Towards Data-Oriented Hospital Services: Data Mining-based Hospital Mangement. In: presented at the The 10th IEEE International Conference on Data Mining Workshops, Sydney, Australia (2011)

    Google Scholar 

  13. Teow, K., Darzi, E., Foo, E., Jin, X., Sim, J.: Intelligent Analysis of Acute Bed Overflow in a Tertiary Hospital in Singapore. Springer US (2012)

    Google Scholar 

  14. Turban, E., Sharda, R., Delen, D.: Decision Support and Business Intelligence Systems, 9a Edição. Prentice Hall (2011)

    Google Scholar 

  15. Maimon, O., Rokach, L.: Introduction to Knowledge Discovery and Data Mining. In: Data Mining and Knowledge Discovery Handbook, 2a Edição. Springer (2010)

    Google Scholar 

  16. Torgo, L.: Data Mining with R: Learning with Case Studies. CRC Press - Taylor & Francis Group (2011)

    Google Scholar 

  17. Meyer, D., Dimitriadou, E., Hornik, K., Weingessel, A., Leisch, F.: Misc Functions of the Department of Statistics (e1071) (2012)

    Google Scholar 

  18. Cortez, P.: Simpler use of data mining methods (e.g. NN and SVM) in classification and regression (2013)

    Google Scholar 

  19. Reis, E.: Estatística Descritiva, 7a ed. Edição Sílabo (2008)

    Google Scholar 

  20. Witten, I., Frank, E., Hall, M.: Data Mining Pratical Machine Learning Tools and Techniques, 3a Edição. Morgan Kaufmann (2011)

    Google Scholar 

  21. Refaeilzadeh, P., Tang, L., Liu, H.: Cross-Validation, Encyclopedia of Database Systems, vol. 5. Springer (2009)

    Google Scholar 

  22. Kantardzic, M.: Data Mining Concepts, Models, Methods, and Algorithms, 2a Edição. Wiley - IEEE Press (2011)

    Google Scholar 

  23. Ben-Hur, A., Weston, J.: A User’s Guide to Support Vector Machines. In: Carugo, O., Eisenhaber, F. (eds.) Data Mining Techniques for the Life Sciences. Humana Press (2010)

    Google Scholar 

  24. Han, J., Kamber, M., Pei, J.: Data Mining Concepts and Techniques, 3a Edição. Morgan Kaufmann (2012)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Algoritmi Centre, University of Minho, Guimarães, Portugal

    Sérgio Oliveira, Filipe Portela & Manuel F. Santos

  2. CCTC, University of Minho, Braga, Portugal

    José Machado & António Abelha

Authors
  1. Sérgio Oliveira

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  2. Filipe Portela

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  3. Manuel F. Santos

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  4. José Machado

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  5. António Abelha

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Corresponding author

Correspondence toSérgio Oliveira.

Editor information

Editors and Affiliations

  1. Universidade de Coimbra & LIACC, Rio Tinto, Portugal

    Álvaro Rocha

  2. Universidade Nova de Lisboa, Instituto Superior de Estatística e Gestão de Informação, Lisboa, Portugal

    Ana Maria Correia

  3. Department of Business Information Systems, Auckland University of Technology, Auckland, New Zealand

    Felix . B Tan

  4. Empirica GmbH, Bonn, Germany

    Karl . A Stroetmann

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© 2014 Springer International Publishing Switzerland

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Oliveira, S., Portela, F., Santos, M.F., Machado, J., Abelha, A. (2014). Predictive Models for Hospital Bed Management Using Data Mining Techniques. In: Rocha, Á., Correia, A., Tan, F., Stroetmann, K. (eds) New Perspectives in Information Systems and Technologies, Volume 2. Advances in Intelligent Systems and Computing, vol 276. Springer, Cham. https://doi.org/10.1007/978-3-319-05948-8_39

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Chapter
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eBook
JPY 22879
Price includes VAT (Japan)
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Softcover Book
JPY 28599
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  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
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Purchases are for personal use only

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