Literature DB >> 22684427

Chronic kidney disease identification in a high-risk urban population: does automated eGFR reporting make a difference?

Laura C Plantinga1, Delphine S Tuot, Vanessa Grubbs, Chi-yuan Hsu, Neil R Powe.   

Abstract

Whether automated estimated glomerular filtration rate (eGFR) reporting for patients is associated with improved provider recognition of chronic kidney disease (CKD), as measured by diagnostic coding of CKD in those with laboratory evidence of the disease, has not been explored in a poor, ethnically diverse, high-risk urban patient population. A retrospective cohort of 237 adult patients (≥ 20 years) with incident CKD (≥ 1 eGFR ≥ 60 ml/min/1.73 m(2), followed by ≥ 2 eGFRs <60 ml/min/1.73 m(2) ≥ 3 months apart)-pre- or post automated eGFR reporting-was identified within the San Francisco Department of Public Health Community Health Network (January 2005-July 2009). Patients were considered coded if any ICD-9-CM diagnostic codes for CKD (585.x), other kidney disease (580.x-581.x, 586.x), or diabetes (250.4) or hypertension (403.x, 404.x) CKD were present in the medical record within 6 months of incident CKD. Multivariable logistic regression was used to obtain adjusted odds ratios (ORs) for CKD coding. We found that, pre-eGFR reporting, 42.5 % of incident CKD patients were coded for CKD. Female gender, increased age, and non-Black race were associated with lower serum creatinine and lower prevalence of coding but comparable eGFR. Prevalence of coding was not statistically significantly higher overall (49.6 %, P = 0.27) or in subgroups after the institution of automated eGFR reporting. However, gaps in coding by age and gender were narrowed post-eGFR, even after adjustment for sociodemographic and clinical characteristics: 47.9 % of those <65 and 30.3 % of those ≥ 65 were coded pre-eGFR, compared to 49.0 % and 52.0 % post-eGFR (OR = 0.43 and 1.16); similarly, 53.2 % of males and 25.4 % of females were coded pre-eGFR compared to 52.8 % and 44.0 % post-eGFR (OR 0.28 vs. 0.64). Blacks were more likely to be coded in the post-eGFR period: OR = 1.08 and 1.43 (P (interaction) > 0.05). Automated eGFR reporting may help improve CKD recognition, but it is not sufficient to resolve under identification of CKD by safety net providers.

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Year:  2012        PMID: 22684427      PMCID: PMC3531349          DOI: 10.1007/s11524-012-9726-2

Source DB:  PubMed          Journal:  J Urban Health        ISSN: 1099-3460            Impact factor:   3.671


  19 in total

Review 1.  Validation of CKD and related conditions in existing data sets: A systematic review.

Authors:  Morgan E Grams; Laura C Plantinga; Elizabeth Hedgeman; Rajiv Saran; Gary L Myers; Desmond E Williams; Neil R Powe
Journal:  Am J Kidney Dis       Date:  2010-08-06       Impact factor: 8.860

2.  Poverty and racial disparities in kidney disease: the REGARDS study.

Authors:  William M McClellan; Britt B Newsome; Leslie A McClure; George Howard; Nataliya Volkova; Paul Audhya; David G Warnock
Journal:  Am J Nephrol       Date:  2010-05-31       Impact factor: 3.754

3.  Hypovitaminosis D, neighborhood poverty, and progression of chronic kidney disease in disadvantaged populations.

Authors:  R Mehrotra; K Norris
Journal:  Clin Nephrol       Date:  2010-11       Impact factor: 0.975

4.  Perspectives on eGFR reporting from the interface between primary and secondary care.

Authors:  Chee Kay Cheung; Sunil Bhandari
Journal:  Clin J Am Soc Nephrol       Date:  2009-02       Impact factor: 8.237

5.  Association of socioeconomic status and CKD among African Americans: the Jackson Heart Study.

Authors:  Marino A Bruce; Bettina M Beech; Errol D Crook; Mario Sims; Sharon B Wyatt; Michael F Flessner; Herman A Taylor; David R Williams; Ermeg L Akylbekova; T Alp Ikizler
Journal:  Am J Kidney Dis       Date:  2010-04-08       Impact factor: 8.860

6.  Chronic kidney disease in the urban poor.

Authors:  Yoshio N Hall; Andy I Choi; Glenn M Chertow; Andrew B Bindman
Journal:  Clin J Am Soc Nephrol       Date:  2010-03-03       Impact factor: 8.237

7.  Poverty, race, and CKD in a racially and socioeconomically diverse urban population.

Authors:  Deidra C Crews; Raquel F Charles; Michele K Evans; Alan B Zonderman; Neil R Powe
Journal:  Am J Kidney Dis       Date:  2010-03-06       Impact factor: 8.860

8.  Nephrology visits and health care resource use before and after reporting estimated glomerular filtration rate.

Authors:  Brenda R Hemmelgarn; Jianguo Zhang; Braden J Manns; Matthew T James; Robert R Quinn; Pietro Ravani; Scott W Klarenbach; Bruce F Culleton; Richard Krause; Laurel Thorlacius; Arsh K Jain; Marcello Tonelli
Journal:  JAMA       Date:  2010-03-24       Impact factor: 56.272

Review 9.  Impact of estimated GFR reporting on patients, clinicians, and health-care systems: a systematic review.

Authors:  Yoan K Kagoma; Matthew A Weir; Arthur V Iansavichus; Brenda R Hemmelgarn; Ayub Akbari; Uptal D Patel; Amit X Garg; Arsh K Jain
Journal:  Am J Kidney Dis       Date:  2010-12-13       Impact factor: 8.860

10.  A new equation to estimate glomerular filtration rate.

Authors:  Andrew S Levey; Lesley A Stevens; Christopher H Schmid; Yaping Lucy Zhang; Alejandro F Castro; Harold I Feldman; John W Kusek; Paul Eggers; Frederick Van Lente; Tom Greene; Josef Coresh
Journal:  Ann Intern Med       Date:  2009-05-05       Impact factor: 25.391

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  3 in total

1.  Chronic kidney disease in an electronic health record problem list: quality of care, ESRD, and mortality.

Authors:  Stacey E Jolly; Sankar D Navaneethan; Jesse D Schold; Susana Arrigain; John W Sharp; Anil K Jain; Martin J Schreiber; James F Simon; Joseph V Nally
Journal:  Am J Nephrol       Date:  2014-04-01       Impact factor: 3.754

2.  Chronic kidney disease (CKD) treatment burden among low-income primary care patients.

Authors:  Linda S Kahn; Bonnie M Vest; Nethra Madurai; Ranjit Singh; Trevor R M York; Charlotte W Cipparone; Sarah Reilly; Khalid S Malik; Chester H Fox
Journal:  Chronic Illn       Date:  2014-11-21

Review 3.  Chronic kidney disease care in the US safety net.

Authors:  Delphine S Tuot; Vanessa Grubbs
Journal:  Adv Chronic Kidney Dis       Date:  2015-01       Impact factor: 3.620

  3 in total

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