Impact of automated reporting of estimated glomerular filtration rate in the veterans health administration.

BACKGROUND: Early detection and treatment of chronic kidney disease (CKD) is important for slowing progression to renal failure and preventing cardiovascular events, but CKD is often not recognized and patients are referred to nephrologists too late for timely management. Automated laboratory reporting of estimated glomerular filtration rate (eGFR) has been introduced in many health systems to improve CKD recognition, but its impact on large, US-based health systems remains unclear. RESEARCH DESIGN: Retrospective time-series study examined change in renal care services and CKD recognition across VA health care system facilities in 2000-2009. Hierarchical generalized linear models were used to estimate immediate and long-term impacts of eGFR reporting across facilities on monthly rates of outpatient CKD diagnoses, utilization of CKD diagnostic tests (urine microalbumin and kidney ultrasound), and outpatient nephrology visits. RESULTS: Rates of CKD recognition through diagnoses in patient medical records changed an average of 11.4 additional diagnosed patients per 10,000 in the general outpatient population per month, with sustained long-term increases in CKD diagnoses (P<0.001). Diagnostic microalbumin and kidney ultrasound testing increased significantly, with long-term increases in microalbumin testing (P<0.001) and short-term increases in kidney ultrasound (P=0.01-0.04) rates across the VHA. There was no significant change in nephrology consultation rates. CONCLUSIONS: Automated eGFR reporting was associated with moderate system-level improvements in documentation of CKD diagnoses and use of diagnostic tests, but had no impact on nephrology consultation. To effectively reduce the large burden of disease and its associated complications, further strategies are needed to identify and provide timely treatment to those with CKD.

Duke Scholars

Author Virginia Wang Population Health Sciences

Author Bradley Gordon Hammill Population Health Sciences

Author Matthew Leonard Maciejewski Population Health Sciences

Author Rasheeda Hall Medicine, Nephrology

Author Uptal Dinesh Patel Medicine, Nephrology