Advertisement

Entropy Measures: An Health Care Study

  • Enrico CiavolinoEmail author
  • Corrado Crocetta
  • Amjad D. Al-Nasser
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 274)

Abstract

In medical emergency situations, the triage process allows patients in potentially life-threatening condition to receive the fastest and most appropriate medical treatment. Triage consists in an evaluation of patients’ medical condition on a colour-based scale, reflecting from major to minor urgency. Shannon’s entropy measures are applied to such process in order to evaluate concordance, overestimation and underestimation of triage codes assigned to patients in two different moments and by different health-care professionals: during the acceptance phase, by nurses (variable X), and by physicians after deepened diagnostic evaluation (variable Y). Entropy indexes were also used to compare the years 2016 and 2015, showing a little increment of equivocal transmission with respect to year 2015.

Keywords

Entropy measures Emergency department triage Information theory 

References

  1. 1.
    Carpita, M., Ciavolino, E.: A generalized maximum entropy estimator to simple linear measurement error model with a composite indicator. Adv. Data Anal. Classif. 11(1), 139–158 (2016)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Ciavolino, E., Al-Nasser, A.: Comparing generalised maximum entropy and partial least squares methods for structural equation models. J. Nonparametric Stat. 21(8), 1017–1036 (2009)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Ciavolino, E., Calcagnì, A.: Generalized cross entropy method for analysing the servqual model. J. Appl. Stat. 42(3), 520–534 (2015)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Ciavolino, E., Carpita, M., Al-Nasser, A.: Modelling the quality of work in the italian social co-operatives combining NPCA-RSM and SEM-GME approaches. J. Appl. Stat. 42(1), 161–179 (2015)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Ciavolino, E., Dahlgaard, J.: Simultaneous equation model based on the generalized maximum entropy for studying the effect of management factors on enterprise performance. J. Appl. Stat. 36(7), 801–815 (2009)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Cover, T.M., Thomas, J.A.: Elements of Information Theory. Wiley-Interscience, Hoboken (2006)zbMATHGoogle Scholar
  7. 7.
    Golan, A., Judge, G.: Maximum Entropy Econometrics: Robust Estimation with Limited Data. Wiley, New York (1996)zbMATHGoogle Scholar
  8. 8.
    Grover, G., Dutta, R.: Survival analysis of acute myocardial infarction patients using non-parametric and parametric approaches. Electron. J. Appl. Stat. Anal. 2(1), 22–36 (2009)Google Scholar
  9. 9.
    Jayakumar, D.S., et al.: Heteroscedasticity in survey data and model selection based on weighted schwarz Bayesian information criteria. Electron. J. Appl. Stat. Anal. 7(2), 199–217 (2014)MathSciNetGoogle Scholar
  10. 10.
    Jaynes, E.: Information theory and statistical mechanics. Phys. Rev. 106(4), 620 (1957)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Jaynes, E.: Prior probabilities. IEEE Trans. Syst. Sci. Cybern. 4(3), 227–241 (1968)CrossRefGoogle Scholar
  12. 12.
    Jaynes, E.T.: Probability Theory: The Logic of Science. Cambridge University Press, Cambridge (2003)CrossRefGoogle Scholar
  13. 13.
    Papalia, R.B., Ciavolino, E.: Gme estimation of spatial structural equations models. J. Classif. 28(1), 126–141 (2011)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Shannon, C.: A mathematical theory of communications. Bell Syst. Tech. J. 27, 379–423 (1948)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Enrico Ciavolino
    • 1
    Email author
  • Corrado Crocetta
    • 2
  • Amjad D. Al-Nasser
    • 3
  1. 1.University of SalentoLecceItaly
  2. 2.University of FoggiaFoggiaItaly
  3. 3.Yarmouk UniversityIrbidJordan

Personalised recommendations