Original Investigation
Pathogenesis and Treatment of Kidney Disease
Validity of Administrative Database Coding for Kidney Disease: A Systematic Review

https://doi.org/10.1053/j.ajkd.2010.08.031Get rights and content

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.

Section snippets

Methods

We conducted this review according to a detailed protocol, and reporting follows published research guidelines (Preferred Reporting Items for Systematic Reviews and Meta-analyses [PRISMA]5; protocol detailed in6).

Study Selection

We screened 19,317 citations, reviewed 722 full-text articles, and identified 25 articles that met eligibility for review.18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42 We present reasons for study exclusion in Fig 1. One study was considered for inclusion; however, because of unresolved discrepancies with the data resulting in the inability to calculate all necessary validity measures, the study was not included.43 Concordance between the 2

Discussion

Renal research using administrative data has increased dramatically since 1990. A simple PubMed search using the terms “database” and “kidney” identified 14 studies published in 1990 compared with 501 in 2008. Administrative data are useful and advance knowledge if they provide accurate and reliable estimates about the conditions under study. To consider this issue, we conducted a comprehensive global review of 25 studies, quantifying the accuracy of codes for 2 renal conditions, AKI and CKD.

Acknowledgements

We thank Dr Peter Blake, Dr Muhammad Mamdani, Mr Michael Paterson, and Dr Amardeep Thind for help and support.

Support: Research grant support was provided by the Canadian Institutes of Health Research (CIHR). Ms Vlasschaert was supported by a Canada Graduate Scholarship from the National Science and Engineering Research Council of Canada and a Schulich Graduate Scholarship from the University of Western Ontario. Dr Hackam was supported by a Clinician Scientist Award from the University of

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    Copyright © 2010 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.