Format

Send to

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

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

Author information

1
Department of Medicine, University of Western Ontario, London, Canada.

Abstract

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.

PMID:
21184918
DOI:
10.1053/j.ajkd.2010.08.031
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center