Validity of administrative database coding for kidney disease: a systematic review

Am J Kidney Dis. 2011 Jan;57(1):29-43. doi: 10.1053/j.ajkd.2010.08.031.


Background: Information in health administrative databases increasingly guides renal care and policy.

Study design: Systematic review of observational studies.

Setting & population: Studies describing the validity of codes for acute kidney injury (AKI) and chronic kidney disease (CKD) in administrative databases operating in any jurisdiction.

Selection criteria: After searching 13 medical databases, we included observational studies published from database inception though June 2009 that validated renal diagnostic and procedural codes for AKI or CKD against a reference standard.

Index tests: Renal diagnostic or procedural administrative data codes.

Reference tests: Patient chart review, laboratory values, or data from a high-quality patient registry.

Results: 25 studies of 13 databases in 4 countries were included. Validation of diagnostic and procedural codes for AKI was present in 9 studies, and validation for CKD was present in 19 studies. Sensitivity varied across studies and generally was poor (AKI median, 29%; range, 15%-81%; CKD median, 41%; range, 3%-88%). Positive predictive values often were reasonable, but results also were variable (AKI median, 67%; range, 15%-96%; CKD median, 78%; range, 29%-100%). Defining AKI and CKD by only the use of dialysis generally resulted in better code validity. The study characteristic associated with sensitivity in multivariable meta-regression was whether the reference standard used laboratory values (P < 0.001); sensitivity was 39% lower when laboratory values were used (95% CI, 23%-56%).

Limitations: Missing data in primary studies limited some of the analyses that could be done.

Conclusions: Administrative database analyses have utility, but must be conducted and interpreted judiciously to avoid bias arising from poor code validity.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review
  • Systematic Review
  • Validation Study

MeSH terms

  • Australia
  • Canada
  • Clinical Coding*
  • Databases, Factual*
  • Health Services Research
  • Humans
  • Kidney Diseases / classification*
  • Sensitivity and Specificity
  • Spain
  • United States