Literature DB >> 25415559

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

Virginia Wang1, Bradley G Hammill, Matthew L Maciejewski, Rasheeda K Hall, Lynn Van Scoyoc, Amit X Garg, Arsh K Jain, Uptal D Patel.   

Abstract

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.

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Year:  2015        PMID: 25415559      PMCID: PMC4294944          DOI: 10.1097/MLR.0000000000000275

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  25 in total

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Authors: 
Journal:  Am J Kidney Dis       Date:  2002-02       Impact factor: 8.860

2.  Segmented regression analysis of interrupted time series studies in medication use research.

Authors:  A K Wagner; S B Soumerai; F Zhang; D Ross-Degnan
Journal:  J Clin Pharm Ther       Date:  2002-08       Impact factor: 2.512

3.  The deadly risk of late referral.

Authors:  Roel M Huisman
Journal:  Nephrol Dial Transplant       Date:  2004-09       Impact factor: 5.992

4.  Reporting of the estimated glomerular filtration rate was associated with increased use of angiotensin-converting enzyme inhibitors and angiotensin-II receptor blockers in CKD.

Authors:  Arsh K Jain; Meaghan S Cuerden; Ian McLeod; Brenda Hemmelgarn; Ayub Akbari; Marcello Tonelli; Rob R Quinn; Matt J Oliver; Amit X Garg
Journal:  Kidney Int       Date:  2012-03-21       Impact factor: 10.612

Review 5.  Validity of administrative database coding for kidney disease: a systematic review.

Authors:  Meghan E O Vlasschaert; Shayna A D Bejaimal; Daniel G Hackam; Robert Quinn; Meaghan S Cuerden; Matthew J Oliver; Arthur Iansavichus; Nabil Sultan; Alison Mills; Amit X Garg
Journal:  Am J Kidney Dis       Date:  2011-01       Impact factor: 8.860

Review 6.  Early detection of CKD: the benefits, limitations and effects on prognosis.

Authors:  Adeera Levin; Paul E Stevens
Journal:  Nat Rev Nephrol       Date:  2011-06-28       Impact factor: 28.314

7.  Failure of ICD-9-CM codes to identify patients with comorbid chronic kidney disease in diabetes.

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Review 8.  National kidney disease education program.

Authors:  Thomas H Hostetter; Mimi Lising
Journal:  J Am Soc Nephrol       Date:  2003-07       Impact factor: 10.121

9.  A population-based study of the incidence and outcomes of diagnosed chronic kidney disease.

Authors:  Nicholas Drey; Paul Roderick; Mark Mullee; Mary Rogerson
Journal:  Am J Kidney Dis       Date:  2003-10       Impact factor: 8.860

10.  The impact of automated eGFR reporting and education on nephrology service referrals.

Authors:  Euan Noble; David W Johnson; Nicholas Gray; Peter Hollett; Carmel M Hawley; Scott B Campbell; David W Mudge; Nicole M Isbel
Journal:  Nephrol Dial Transplant       Date:  2008-07-16       Impact factor: 5.992

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  4 in total

1.  Prevalence and recognition of chronic kidney disease in Stockholm healthcare.

Authors:  Alessandro Gasparini; Marie Evans; Josef Coresh; Morgan E Grams; Olof Norin; Abdul R Qureshi; Björn Runesson; Peter Barany; Johan Ärnlöv; Tomas Jernberg; Björn Wettermark; Carl G Elinder; Juan-Jesüs Carrero
Journal:  Nephrol Dial Transplant       Date:  2016-10-13       Impact factor: 5.992

2.  Early recognition of multiple sclerosis using natural language processing of the electronic health record.

Authors:  Herbert S Chase; Lindsey R Mitrani; Gabriel G Lu; Dominick J Fulgieri
Journal:  BMC Med Inform Decis Mak       Date:  2017-02-28       Impact factor: 2.796

3.  Effect of nephrology referrals and multidisciplinary care programs on renal replacement and medical costs on patients with advanced chronic kidney disease: A retrospective cohort study.

Authors:  Jui-Hsin Chen; Yi-Wen Chiu; Shang-Jyh Hwang; Jer-Chia Tsai; Hon-Yi Shi; Ming-Yen Lin
Journal:  Medicine (Baltimore)       Date:  2019-08       Impact factor: 1.817

4.  Chronic kidney disease recognition amongst physicians and advanced practice providers.

Authors:  Carlos R Franco Palacios; Rudiona Hoxhaj; Pankaj Goyal
Journal:  Ren Fail       Date:  2021-12       Impact factor: 2.606

  4 in total

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