Evidence map›Paper›PMID 25415559›Full record

ArticleMedical care2015

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

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

Open access · greenAbstract read
In one paragraph

Article in Medical care, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Prevalence and recognition of chronic kidney disease in Stockholm healthcare.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2016
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 3 countries.

Virginia Wang*Center for Health Services Research in Primary Care, Veterans Affairs Health Services Research & Development †Department of Medicine, Duke University School of Medicine ‡Duke Clinical Research Institute, Duke University Medical Center, Durham, NC §Department of Medicine, Division of Nephrology, Western University, London, ON, Canada.
Bradley G Hammill
Matthew L Maciejewski
Rasheeda K Hall
Lynn Van Scoyoc
Amit X Garg
Arsh K Jain
Uptal D Patel
Primary Health Care · QADuke University · USWestern University · CAClinical Research Institute · US

Funding

Barriers to Optimal Cardiovascular Medication Use in Diabetes and Renal DiseaseK23DK075929 · NIDDK · DUKE UNIVERSITY · PI PATEL, UPTAL D · 2006 to 2010
$677k
NIDDK NIH HHS K23 DK075929NIDDK NIH HHS K23DK075929-04W1
6 · The paper itself

Abstract

backgroundEarly 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

designRetrospective 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.

resultsRates 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.

conclusionsAutomated 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.

Indexed as

Glomerular Filtration RateUnited States Department of Veterans AffairsAdultAgedAged, 80 and overAutomationDocumentationEarly DiagnosisFemaleHumansMaleMiddle AgedPredictive Value of TestsRenal Insufficiency, ChronicRetrospective StudiesTime Factors

Identifiers

PMID25415559
PMCPMC4294944
OpenAlexW2315189339

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.