Title |
Implementation of automated reporting of estimated glomerular filtration rate among Veterans Affairs laboratories: a retrospective study
|
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Published in |
BMC Medical Informatics and Decision Making, July 2012
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DOI | 10.1186/1472-6947-12-69 |
Pubmed ID | |
Authors |
Rasheeda K Hall, Virginia Wang, George L Jackson, Bradley G Hammill, Matthew L Maciejewski, Elizabeth M Yano, Laura P Svetkey, Uptal D Patel |
Abstract |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
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India | 2 | 67% |
United States | 1 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 3 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 37 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Postgraduate | 6 | 16% |
Student > Master | 4 | 11% |
Student > Ph. D. Student | 4 | 11% |
Other | 3 | 8% |
Librarian | 2 | 5% |
Other | 7 | 19% |
Unknown | 11 | 30% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 8 | 22% |
Nursing and Health Professions | 7 | 19% |
Business, Management and Accounting | 1 | 3% |
Unspecified | 1 | 3% |
Economics, Econometrics and Finance | 1 | 3% |
Other | 3 | 8% |
Unknown | 16 | 43% |