Validating GFR Information via Data Mining and Practical Aspects of Embedding GFR Data in the LIS/HIS

December 7, 2004

Jay Jones, PhD, DABCC, Director of Chemistry and Regional Laboratories, Geisinger Health System (Danville, PA)

Recently, the National Kidney Foundation (NKF) advised that “estimates of [glomerular filtration rate] are the best overall indices of the level of kidney function,” and that “clinical laboratories should report an estimate of GFR using a prediction equation, in addition to reporting the serum creatinine measurement.”

These recommendations appear in the latest iteration of NKF’s Kidney Disease Outcomes Quality Initiative (K/DOQI) Clinical Practice Guidelines for Chronic Kidney Disease: Evaluation, Classification, and Stratification, which offers a “road map” for diagnosis and care of patients with chronic kidney disease and has been adopted as “best medical practice” by countless health care systems.

But how best to use this data in a clinical setting? This month’s Expert Access presentation will offer some suggestions for making the most of laboratory investigations of kidney function, including:
* Practical aspects of embedding and reporting estimated glomerular filtration rate (est GFR) in the lab information system (LIS)
* Data mining creatinine from the LIS database to validate distributions of estimated GFR
* Eight months experience in reporting est GFR with each serum creatinine performed
* Importance of creatinine method employed when considering LIS reporting of est GFR
* Simplified lab data mining technique to help validate present and future population-based evidence based medicine (EBM)

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