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Kidney function is reported using estimates of glomerularfiltration rate (eGFR). However, eGFR values are recorded without reference tothe creatinine (SCr) assays used to derive them, and newer assays wereintroduced at different time points across laboratories in UK. These changesmay cause systematic bias in eGFR reported in routinely collected data; eventhough laboratory reported eGFR values have a correction factor applied.  Design: An algorithm to detect changes in SCr which affect eGFR calculationmethod by comparing the mapping of SCr values on to eGFR values across atime-series of paired eGFR and SCr measurements.  Setting: Routinely collected primary care data from 20,000 people with therichest renal function data from the Quality Improvement in Chronic KidneyDisease (QICKD) trial.  Results: The algorithm identified a change in eGFR calculation method in 80(63%) of the 127 included practices. This change was identified in 4,736(23.7%) patient time series analysed. This change in calibration method wasfound to cause a significant step change in reported eGFR values producing asystematic bias. eGFR values could not be recalibrated by applying theModification of Diet in Renal Disease (MDRD) equation to the laboratoryreported SCr values.  Conclusions: This algorithm can identify laboratory changes in eGFRcalculation methods and changes in SCr assay. Failure to account for thesechanges may misconstrue renal function changes over time. Researchers usingroutine eGFR data should account for these effects.

Towards automated identification of changes in laboratory measurement of  renal function: implications for longitudinal research and observing trends  in glomerular filtration rate (GFR)