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.

Identification of dementia: agreement among national survey data, medicare claims, and death certificates.

OBJECTIVE: To estimate the proportion of seniors with dementia from three independent data sources and their agreement. DATA SOURCES: The longitudinal Asset and Health Dynamics among the Oldest Old (AHEAD) study (n=7,974), Medicare claims, and death certificate data. STUDY DESIGN: Estimates of the proportion of individuals with dementia from: (1) self- or proxy-reported cognitive status measures from surveys, (2) Medicare claims, and (3) death certificates. Agreement using Cohen's kappa; multivariate logistic regression. PRINCIPAL FINDINGS: The proportion varied substantially among the data sources. Agreement was poor (kappa: 0.14-0.46 depending upon comparison assessed); the individuals identified had relatively modest overlap. CONCLUSIONS: Estimates of dementia occurrence based on cognitive status measures from three independent data sources were not interchangeable. Further validation of these sources is needed. Caution should be used if policy is based on only one data source.