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Accurate Identification of Patients with Cirrhosis and Its Complications in the Electronic Health Record

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Abstract

Background

Cirrhosis represents a significant health burden; administrative data provide an important tool for research studies.

Aims

We aimed to understand the validity of current ICD-10 codes compared to previously used ICD-9 codes to identify patients with cirrhosis and its complications.

Methods

We identified 1981 patients presenting to MUSC between 2013 and 2019 with a diagnosis of cirrhosis. To validate the sensitivity of ICD codes, we reviewed the medical records of 200 patients for each associated ICD 9 and 10 codes. Sensitivity, specificity, and positive predictive value for each ICD code (individually or when combined) were calculated and univariate binary logistic models, for cirrhosis and its complications, predicted probabilities were used to calculate C-statistics.

Results

Single ICD 9 and 10 codes were similarly insensitive for detection of cirrhosis, with sensitivity ranging from 5 to 94%. However, ICD-9 code combinations (when used as either/or) had high sensitivity and specificity for the detection of cirrhosis, with the combination of either 571.5 (or 456.21) or 571.2 codes having a C-statistic of 0.975. Combinations of ICD-10 codes were only slightly less sensitive and specific than ICD-9 codes for detection of cirrhosis (K76.6, or K70.31, plus K74.60 or K74.69, and K70.30 had a C-statistic of 0.927).

Conclusions

ICD-9 and ICD-10 codes when used alone were inaccurate for identifying cirrhosis. ICD-10 and ICD-9 codes had similar performance characteristics. Combinations of ICD codes exhibited the greatest sensitivity and specificity for detection of cirrhosis, and thus should be used to accurately identify cirrhosis.

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Abbreviations

AUROC:

Area under the receiver operating characteristic

CT:

Computerized tomography

EHR:

Electronic health record

EGD:

Esophagogastroduodenoscopy

HCC:

Hepatocellular carcinoma

HRS:

Hepatorenal syndrome

ICD:

International Classification of Diseases

MRI:

Magnetic resonance imaging

MUSC:

Medical University of South Carolina

NPV:

Negative predictive value

OASIS:

Outcome and assessment information set.

PPV:

Positive predictive value

SPARC:

Services, pricing, and application for research centers

US:

Ultrasonography

VA:

Veterans Affairs

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Funding

This project was supported, in part, by the National Institutes of Health—the National Institute of Diabetes and Digestive and Kidney Disease (Grant Number P30 DK123704—the clinical component), the National Institute of General Medical Sciences (Grant Number P20 GM 130457—support to DCR), and the National Center for Advancing Translational Sciences of the (Grant Number UL1 TR001450—support to JSO and MG and bioinformatic data gathering).

Author information

Author notes

  1. Ali Khalifa and Jihad S. Obeid have contributed equally to this work.

Authors and Affiliations

  1. Digestive Disease Research Center, Medical University of South Carolina, Charleston, SC, USA

    Ali Khalifa & Don C. Rockey

  2. Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA

    Jihad S. Obeid & Mathew J. Gregoski

  3. Department of Internal Medicine, Medical University of South Carolina, 96 Jonathan Lucas Street, Suite 803, MSC 623, Charleston, SC, 29425, USA

    Don C. Rockey

Authors
  1. Ali Khalifa
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  2. Jihad S. Obeid
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  3. Mathew J. Gregoski
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  4. Don C. Rockey
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Contributions

AK contributed toward study concept and design; acquisition of data; analysis and interpretation of data; drafting of the manuscript; critical revision of the manuscript for important intellectual content. Email: khalifa@musc.edu. JO contributed toward study concept and design; acquisition of data; analysis and interpretation of data; drafting of the manuscript; critical revision of the manuscript for important intellectual content. Email: jobeid@musc.edu. MG contributed toward analysis and interpretation of data; statistical analysis; critical revision of the manuscript for important intellectual content. Email: gregoski@musc.edu. DR contributed toward study concept and design; acquisition of data; analysis and interpretation of data; drafting of the manuscript; critical revision of the manuscript for important intellectual content; supervisory efforts. E-mail: rockey@musc.edu.

Corresponding author

Correspondence to Don C. Rockey.

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The authors have no competing interests to disclose.

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Khalifa, A., Obeid, J.S., Gregoski, M.J. et al. Accurate Identification of Patients with Cirrhosis and Its Complications in the Electronic Health Record. Dig Dis Sci 68, 2360–2369 (2023). https://doi.org/10.1007/s10620-023-07876-7

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  • DOI: https://doi.org/10.1007/s10620-023-07876-7

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