Validity of Administrative Database Coding for Kidney Disease: A Systematic Review
| Autor: | Meaghan S. Cuerden, Daniel G. Hackam, Amit X. Garg, Alison Mills, Shayna A.D. Bejaimal, Nabil Sultan, Meghan Vlasschaert, Matthew J. Oliver, Robert R. Quinn, Arthur V. Iansavichus |
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| Rok vydání: | 2011 |
| Předmět: |
Nephrology
Canada medicine.medical_specialty Databases Factual Population MEDLINE urologic and male genital diseases Sensitivity and Specificity Internal medicine Humans Medicine education education.field_of_study business.industry Australia Clinical Coding Acute kidney injury Health services research Missing data medicine.disease United States female genital diseases and pregnancy complications Surgery Spain Emergency medicine Kidney Diseases Observational study Health Services Research business Kidney disease |
| Zdroj: | American Journal of Kidney Diseases. 57:29-43 |
| ISSN: | 0272-6386 |
| DOI: | 10.1053/j.ajkd.2010.08.031 |
| Popis: | 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 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. |
| Databáze: | OpenAIRE |
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