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Exploitation of Healthcare Databases in Anesthesiology and Surgical Care for Comparing Comorbidity Indexes in Cholecystectomized Patients

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Big Data in Complex Systems

Part of the book series: Studies in Big Data ((SBD,volume 9))

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Abstract

Objective: Charlson comorbidity index (CCI) and Elixhauser comorbidity index (ECI) have been used as prognostic tools in surgical and medical research. We compared their ability to predict in-hospital mortality among cholecystectomized patients using a Spanish large database of 87 hospitals during the period 2008-2010.

Methods: The electronic healthcare database Minimal Basic Data Set (MBDS) contain information of diseases, conditions, procedures and demographic data of patients attended in hospital setting. We used available information to calculate CCI and ECI, and analyzed their relation to in-hospital mortality.

Results: The models including age, gender, tobacco use disorders, hospital size and CCI or ECI were predictive of in-hospital mortality among cholecystectomized patients, when measured in terms of adjusted Odds Ratios and 95% confidence limits. There was a dose-effect relationship between score of prognostic indexes and risk of death. Area under the curve for ROC predictive models for in-hospital mortality were 0.8717 for CCI and 0.8771 for ECI, but differences were not statistically significant (p> 10− 6).

Conclusion: Both CCI and ECI were predictive of in-hospital mortality among cholecystectomized patients in a large sample of Spanish patients after controlling for age, gender, group of hospital and tobacco use disorders. The availability of more hospitals databases through Big Data can strengthen the external validity of these results if we control several threats of internal validity such as biases and missing values.

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Authors and Affiliations

  1. Department of Preventive Medicine and Public Health, University of Seville, Seville, Spain

    Luís Béjar-Prado & Julio López-Méndez

  2. Unit of Anesthesiology and Pain Therapy, Hospital Universitario Virgen Macarena, Seville, Spain

    Enrique Gili-Ortiz

  3. Unit of Preventive Medicine, Surveillance and Health Promotion, Hospital Universitario Virgen Macarena, Seville, Spain

    Julio López-Méndez

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  1. Luís Béjar-Prado
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Correspondence to Luís Béjar-Prado .

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Editors and Affiliations

  1. Cairo University, Cairo, Egypt

    Aboul Ella Hassanien

  2. Faculty of Computers and Information, Benha University, Benha, Egypt

    Ahmad Taher Azar

  3. Faculty of Elec. Eng. & Comp. Sci., Department of Computer Science, VSB-Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Vaclav Snasael

  4. Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  5. School of Information Technology, Deakin University, Victoria, Australia

    Jemal H. Abawajy

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Béjar-Prado, L., Gili-Ortiz, E., López-Méndez, J. (2015). Exploitation of Healthcare Databases in Anesthesiology and Surgical Care for Comparing Comorbidity Indexes in Cholecystectomized Patients. In: Hassanien, A., Azar, A., Snasael, V., Kacprzyk, J., Abawajy, J. (eds) Big Data in Complex Systems. Studies in Big Data, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-319-11056-1_9

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