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Utilization of Electronic Medical Records to Build a Detection Model for Surveillance of Healthcare-Associated Urinary Tract Infections

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Abstract

In this study, we propose an approach to build a detection model for surveillance of healthcare-associated urinary tract infection (HA-UTI) based on the variables extracted from the electronic medical records (EMRs) in a 730-bed, tertiary-care teaching hospital in Taiwan. Firstly we mapped the CDC’s HA-UTI case definitions to a set of variables, and identified the variables whose values could be derived from the EMRs of the hospital automatically. Then with these variables we performed discriminant analysis (DA) on a training set of the EMRs to construct a discriminant function (DF) for the classification of a patient with or without HA-UTI. Finally, we evaluated the sensitivity, specificity, and overall accuracy of the function using a testing set of EMRs. In this study, six surveillance variables (fever, urine culture, blood culture, routine urinalysis, antibiotic use, and invasive devices) were identified whose values could be derived from the EMRs of the hospital. The sensitivity, specificity and overall accuracy of the built DF were 100 %, 94.61 %, and 94.65 %, respectively. Since most hospitals may adopt their EMRs piece-by-piece to meet their functional requirements, the variables that are available in the EMRs may differ. Our approach can build a detection model with these variables to achieve a high sensitivity, specificity and accuracy for automatically detecting suspected HA-UTI cases. Therefore, our approach on one hand can reduce the efforts in building the model; on the other hand, can facilitate adoption of EMRs for HAI surveillance and control.

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Acknowledgments

We thank the infection control team members at TMUWF for their support. We also thank Mr. James Andrew Worley for manuscript editing.

Financial Support

This research was partially supported by National Science Council (NSC) of Taiwan under the grant numbers NSC 97-2221-E-038-010 and NSC 98-2221-E-038-009-MY3.

Conflicts of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, 250 WuXing Street, Taipei, 110, Taiwan

    Yu-Sheng Lo & Chien-Tsai Liu

  2. Division of Internal Medicine, Department of Infection Control, Wan Fang Hospital, Taipei Medical University, 111 Sec 3, Hsing-Long Rd, Taipei, 116, Taiwan

    Wen-Sen Lee

  3. Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, 250 WuXing Street, Taipei, 110, Taiwan

    Wen-Sen Lee

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  1. Yu-Sheng Lo
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Correspondence to Chien-Tsai Liu.

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Lo, YS., Lee, WS. & Liu, CT. Utilization of Electronic Medical Records to Build a Detection Model for Surveillance of Healthcare-Associated Urinary Tract Infections. J Med Syst 37, 9923 (2013). https://doi.org/10.1007/s10916-012-9923-2

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  • DOI: https://doi.org/10.1007/s10916-012-9923-2

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