ASN's Mission

To create a world without kidney diseases, the ASN Alliance for Kidney Health elevates care by educating and informing, driving breakthroughs and innovation, and advocating for policies that create transformative changes in kidney medicine throughout the world.

learn more

Contact ASN

1401 H St, NW, Ste 900, Washington, DC 20005

email@asn-online.org

202-640-4660

The Latest on X

Kidney Week

ASN / Education & Meetings / Kidney Week /

Please note that you are viewing an archived section from 2019 and some content may be unavailable. To unlock all content for 2019, please visit the archives.

Abstract: TH-PO397

CKD Prevalence in the US Military Health System (MHS) by Laboratory vs. ICD-9 Coding

Session Information

Category: CKD (Non-Dialysis)

  • 2101 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Authors

  • Oliver, James D., Walter Reed National Military Medical Center, Bethesda, Maryland, United States
  • Nee, Robert, Walter Reed National Military Medical Center, Bethesda, Maryland, United States
  • Grunwald, Lindsay, Henry M. Jackson Foundation, Bethesda, Maryland, United States
  • Banaag, Amanda, Henry M. Jackson Foundation, Bethesda, Maryland, United States
  • Pavkov, Meda E., Centers for Disease Control and Prevention, Atlanta, Georgia, United States
  • Burrows, Nilka Rios, Centers for Disease Control and Prevention, Atlanta, Georgia, United States
  • Koehlmoos, Tracey L., Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States
  • Marks, Eric S., Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States
Background

Epidemiological analysis of CKD is limited by variable definitions of CKD and accuracy of the diagnosis in the medical record. We report here on CKD prevalence by laboratory and coding data in the MHS Data Repository (MDR), a large database for a universal system of coverage of US active-duty military, retirees, and family members, with demographics similar to that of the US general population.

Methods

Patient data for age ≥ 18 from Fiscal Year (FY) 2006-15 were extracted from the MDR. CKD diagnosis was based on either ICD-9 codes or from labs (CKD-EPI eGFR < 60 mL/min/1.73m2, uPCR ≥ 0.15 g/g, or uACR ≥ 30 mg/g). Code+ was defined as ≥ 1 inpatient or ≥ 2 outpatient CKD codes during the FY. Two definitions of Lab+ were used: 2Lab+ (gold standard) was defined as the most recent labs in the FY being persistently abnormal over ≥ 3 months. 1Lab+ was defined as any abnormal lab during the FY. Code+ and 1Lab+ were compared to 2Lab+ by sensitivity/specificity, chi-square, Cohen’s kappa, and McNemar’s test.

Results

For FY2015, data from 3,360,305 patients were analyzed (mean age = 37.6±15.6). 969,873 (28.9%) had labs. Among patients with labs, 2Lab+CKD prevalence was 2.5% overall and increased to 9.7% for age ≥ 60. 1Lab+CKD prevalence was 9.9% overall and increased to 31.5% for age ≥ 60. Code+CKD prevalence was 2.8% overall and 4.8% in patients with labs. Only 54.8% of 2Lab+ were also Code+. 1Lab had a Positive Predictive Value (PPV) = 0.25 and a Negative Predictive Value (NPV) = 1.0 for 2Lab (Table). Code had a PPV = 0.28 and a NPV = 0.99 for 2Lab. For age ≥ 60, PPVs were higher for both 1Lab+ (0.31) and Code+ (0.47).

Conclusion

Based on ICD-9 codes, provider awareness of CKD in the MHS is low. Use of a single lab value significantly overestimates CKD prevalence and has a poor PPV compared to repeat measures. The views expressed in this abstract are those of the authors and do not reflect the official policy of the Departments of Army/Navy/Air Force, Department of Defense, Department of Health and Human Services, or the US Government.

Funding

  • Other U.S. Government Support