Evidence map›Paper›PMID 23065915›Full record

ReviewJournal of nephrology

Geographic information systems and chronic kidney disease: racial disparities, rural residence and forecasting.

Rudolph A Rodriguez, John R Hotchkiss, Ann M O'Hare

Abstract readReview
In one paragraph

Review in Journal of nephrology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

22 citing papers in PubMed, 55 citations in OpenAlex.

  1. Review
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  11. Neighborhood Socioeconomic Status and Identification of Patients With CKD Using Electronic Health Records.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2021
    Article
  12. Early detection of SARS-CoV-2 and other infections in solid organ transplant recipients and household members using wearable devices.Transplant international : official journal of the European Society for Organ Transplantation · 2021
    Review
  13. Review
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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

3 authors at 2 institutions in 1 country.

Rudolph A RodriguezUniversity of Washington, Seattle, USA. rudy.rodriguez@va.gov
John R Hotchkiss
Ann M O'Hare
University of Washington · USUniversity of Pittsburgh · US

Funding

Furthering scientific understanding of mechanisms underlying resilience to the effects of AD pathology by incorporating state of the art quantification of gliosis, inflammation, & synaptic toxicityU01AG006781 · NIA · UNIVERSITY OF WASHINGTON · PI CRANE, PAUL K, LARSON, ERIC B · 1986 to 2020
$39.3M
Targeting Nephrology Referral Among Elderly Patients with Chronic Kidney DiseaseK23AG028980 · NIA · UNIVERSITY OF WASHINGTON · PI O'HARE, ANN M. · 2006 to 2009
$756k
NIA NIH HHS K23 AG028980NIA NIH HHS U01 AG006781
6 · The paper itself

Abstract

The dynamics of health and health care provision in the United States vary substantially across regions, and there is substantial regional heterogeneity in population density, age distribution, disease prevalence, race and ethnicity, poverty and the ability to access care. Geocoding and geographic information systems (GIS) are important tools to link patient or population location to information regarding these characteristics. In this review, we provide an overview of basic GIS concepts and provide examples to illustrate how GIS techniques have been applied to the study of kidney disease, and in particular to understanding the interplay between race, poverty, rural residence and the planning of renal services for this population. The interplay of socioeconomic status and renal disease outcomes remains an important area for investigation and recent publications have explored this relationship utilizing GIS techniques to incorporate measures of socioeconomic status and racial composition of neighborhoods. In addition, there are many potential challenges in providing care to rural patients with chronic kidney disease including long travel times and sparse renal services such as transplant and dialysis centers. Geospatially fluent analytic approaches can also inform system level analyses of health care systems and these approaches can be applied to identify an optimal distribution of dialysis facilities. GIS analysis could help untangle the complex interplay between geography, socioeconomic status, and racial disparities in chronic kidney disease, and could inform policy decisions and resource allocation as the population ages and the prevalence of renal disease increases.

Indexed as

Geographic Information SystemsForecastingHealthcare DisparitiesHealth Services AccessibilityHealth Services Needs and DemandHumansRenal Insufficiency, ChronicRural Health ServicesSocioeconomic FactorsUnited States

Identifiers

PMID23065915
PMCPMC4047635
OpenAlexW1993914746

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.