An Information-theoretical Approach to Classify Hospitals with Respect to Their Diagnostic Diversity using Shannon’s Entropy

Thomas Ostermann, Reinhard Schuster

2015

Abstract

In Germany hospital comparisons are part of health status reporting. This article presents the application of Shannon’s entropy measure for hospital comparisons using reported diagnostic data. We used Shannon’s entropy to measure the diagnostic diversity of a hospital department by means of reported ICD–9–codes. Entropy values were compared both with respect to the hospital status (i.e. primary, secondary, tertiary or specialized hospital) and specialisations (e.g. surgery, gynaecology). There were relevant differences in entropy values between the different types of hospitals. Primary hospitals differed from specialized hospitals (0.535 ± 0.09 vs. 0.504 ± 0.07). Furthermore, specialized departments like obstetrics or ophthalmology did generate lower entropy values than area-spanning departments like paediatrics or general internal medicine, having significantly higher values. In conclusion, we showed how entropy can be used as a measure for classifying hospitals. Besides of hospital comparisons, this approach can be implemented in all fields of health services research for measuring variability in nominal or ordinal data. The use of entropy as a measure for health services research and classification algorithms should be encouraged to learn more about this measure, which unreasonably has fallen into oblivion in health services research.

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Paper Citation


in Harvard Style

Ostermann T. and Schuster R. (2015). An Information-theoretical Approach to Classify Hospitals with Respect to Their Diagnostic Diversity using Shannon’s Entropy . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015) ISBN 978-989-758-068-0, pages 325-329. DOI: 10.5220/0005197103250329


in Bibtex Style

@conference{healthinf15,
author={Thomas Ostermann and Reinhard Schuster},
title={An Information-theoretical Approach to Classify Hospitals with Respect to Their Diagnostic Diversity using Shannon’s Entropy },
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015)},
year={2015},
pages={325-329},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005197103250329},
isbn={978-989-758-068-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015)
TI - An Information-theoretical Approach to Classify Hospitals with Respect to Their Diagnostic Diversity using Shannon’s Entropy
SN - 978-989-758-068-0
AU - Ostermann T.
AU - Schuster R.
PY - 2015
SP - 325
EP - 329
DO - 10.5220/0005197103250329