Inaccuracy of ICD-9 Codes for Chronic Kidney Disease: A Study from Two Practice-based Research Networks (PBRNs)

Charlotte W Cipparone1, Matthew Withiam-Leitch2, Kim S Kimminau2

  • 1From the Primary Care Research Institute, Department of Family Medicine, University at Buffalo, Buffalo, NY (CWC, MW-L, CHF, RS, LK); and the Department of Family Medicine, University of Kansas Medical Center, Kansas City, KS (KSK). charlotte.cipparone@gmail.com.

Insights

Many patients with the chronic kidney disease (CKD) ICD-9 code lack clinical indicators for the disease. This highlights significant inaccuracies in CKD coding within electronic medical records.

Area of Science:

  • Medical Informatics
  • Nephrology
  • Health Services Research

Background:

  • Inaccurate International Classification of Diseases, Ninth Revision (ICD-9) coding leads to unreliable research data and potential patient mismanagement.
  • Misuse of ICD-9 codes, particularly for chronic kidney disease (CKD), was investigated due to patient reports contradicting their medical records.

Purpose of the Study:

  • To determine the prevalence of International Classification of Diseases, Ninth Revision (ICD-9) code misuse for chronic kidney disease (CKD) stage 3.
  • To assess the accuracy of ICD-9 code 585.x in reflecting actual CKD diagnoses in electronic medical records (EMRs).

Main Methods:

  • A retrospective chart review was conducted on 325 patients with the ICD-9 code for CKD stage 3 (585.3).
  • Data were extracted from electronic medical records across three primary care practices in Buffalo, New York, and Kansas City, Kansas.

Main Results:

  • Nearly half (47%) of patients with the CKD ICD-9 code lacked clinical indicators of the disease, according to Kidney Disease Outcomes Quality Initiative guidelines.
  • The prevalence of accurate CKD diagnosis among patients with the ICD-9 code 585.3 was significantly lower than indicated by the code itself.

Conclusions:

  • The ICD-9 code for CKD stage 3 (585.3) does not accurately represent disease prevalence in the studied population.
  • Inaccurate coding has clinical implications, potentially leading to unnecessary treatments and tests for patients.
  • This coding inaccuracy poses a significant challenge for research relying on EMR data for patient identification and recruitment.
Abstract

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