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Open Access Research article

Implementation of automated reporting of estimated glomerular filtration rate among Veterans Affairs laboratories: a retrospective study

Rasheeda K Hall12, Virginia Wang12, George L Jackson12, Bradley G Hammill2, Matthew L Maciejewski12, Elizabeth M Yano34, Laura P Svetkey25 and Uptal D Patel126*

Author Affiliations

1 Center for Health Services Research in Primary Care, Veterans Affairs Health Services Research & Development, Durham, NC, USA

2 Department of Medicine, Duke University School of Medicine, Durham, NC, USA

3 Center for the Study of Healthcare Provider Behavior, Veterans Affairs Health Services Research & Development, Sepulveda, CA, USA

4 Department of Health Services, University of California at Los Angeles, Los Angeles, CA, USA

5 Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, USA

6 Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA

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BMC Medical Informatics and Decision Making 2012, 12:69  doi:10.1186/1472-6947-12-69

Published: 12 July 2012

Abstract

Background

Automated reporting of estimated glomerular filtration rate (eGFR) is a recent advance in laboratory information technology (IT) that generates a measure of kidney function with chemistry laboratory results to aid early detection of chronic kidney disease (CKD). Because accurate diagnosis of CKD is critical to optimal medical decision-making, several clinical practice guidelines have recommended the use of automated eGFR reporting. Since its introduction, automated eGFR reporting has not been uniformly implemented by U. S. laboratories despite the growing prevalence of CKD. CKD is highly prevalent within the Veterans Health Administration (VHA), and implementation of automated eGFR reporting within this integrated healthcare system has the potential to improve care. In July 2004, the VHA adopted automated eGFR reporting through a system-wide mandate for software implementation by individual VHA laboratories. This study examines the timing of software implementation by individual VHA laboratories and factors associated with implementation.

Methods

We performed a retrospective observational study of laboratories in VHA facilities from July 2004 to September 2009. Using laboratory data, we identified the status of implementation of automated eGFR reporting for each facility and the time to actual implementation from the date the VHA adopted its policy for automated eGFR reporting. Using survey and administrative data, we assessed facility organizational characteristics associated with implementation of automated eGFR reporting via bivariate analyses.

Results

Of 104 VHA laboratories, 88% implemented automated eGFR reporting in existing laboratory IT systems by the end of the study period. Time to initial implementation ranged from 0.2 to 4.0 years with a median of 1.8 years. All VHA facilities with on-site dialysis units implemented the eGFR software (52%, p<0.001). Other organizational characteristics were not statistically significant.

Conclusions

The VHA did not have uniform implementation of automated eGFR reporting across its facilities. Facility-level organizational characteristics were not associated with implementation, and this suggests that decisions for implementation of this software are not related to facility-level quality improvement measures. Additional studies on implementation of laboratory IT, such as automated eGFR reporting, could identify factors that are related to more timely implementation and lead to better healthcare delivery.