Open AccessThe validity of Dutch health claims data for identifying patients with chronic kidney disease: a hospital-based study in the Netherlands
Author(s) -
Ma J M van Oosten,
Richard Brohet,
S. J. J. Logtenberg,
Anneke Kramer,
L. D. Dikkeschei,
Marc H Hemmelder,
Henk J. G. Bilo,
Kitty J. Jager,
Vianda S. Stel
Publication year - 2020
Publication title -
clinical kidney journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.033
H-Index - 40
eISSN - 2048-8513
pISSN - 2048-8505
DOI - 10.1093/ckj/sfaa167
Subject(s) - kidney disease , medicine , renal function , confidence interval , creatinine , population , environmental health
Background Health claims data may be an efficient and easily accessible source to study chronic kidney disease (CKD) prevalence in a nationwide population. Our aim was to study Dutch claims data for their ability to identify CKD patients in different subgroups. Methods From a laboratory database, we selected 24 895 adults with at least one creatinine measurement in 2014 ordered at an outpatient clinic. Of these, 15 805 had ≥2 creatinine measurements at least 3 months apart and could be assessed for the chronicity criterion. We estimated the validity of a claim-based diagnosis of CKD and advanced CKD. The estimated glomerular filtration rate (eGFR)-based definitions for CKD (eGFR < 60 mL/min/1.73 m2) and advanced CKD (eGFR < 30 mL/min/1.73 m2) satisfying and not satisfying the chronicity criterion served as reference group. Analyses were stratified by age and sex. Results In general, sensitivity of claims data was highest in the population with the chronicity criterion as reference group. Sensitivity was higher in advanced CKD patients than in CKD patients {51% [95% confidence interval (CI) 47–56%] versus 27% [95% CI 25–28%]}. Furthermore, sensitivity was higher in young versus elderly patients. In patients with advanced CKD, sensitivity was 72% (95% CI 62–83%) for patients aged 20–59 years and 43% (95% CI 38–49%) in patients ≥75 years. The specificity of CKD and advanced CKD was ≥99%. Positive predictive values ranged from 72% to 99% and negative predictive values ranged from 40% to 100%. Conclusion When using health claims data for the estimation of CKD prevalence, it is important to take into account the characteristics of the population at hand. The younger the subjects and the more advanced the stage of CKD the higher the sensitivity of such data. Understanding which patients are selected using health claims data is crucial for a correct interpretation of study results.