Evidence map›Paper›PMID 26493242›Full record

ArticleClinical journal of the American Society of Nephrology : CJASN2015

Disparities in Electronic Health Record Patient Portal Use in Nephrology Clinics.

Manisha Jhamb, Kerri L Cavanaugh, Aihua Bian, Guanhua Chen, T Alp Ikizler, Mark L Unruh, Khaled Abdel-Kader

Abstract read
In one paragraph

Article in Clinical journal of the American Society of Nephrology : CJASN, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 5 pooled it
–field-weighted citation impact
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

52 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Manisha JhambRenal-Electrolyte Division, University of Pittsburgh, Pittsburgh, Pennsylvania;
Kerri L CavanaughVanderbilt Center for Kidney Disease, Nashville, Tennessee; Division of Nephrology and Hypertension and.
Aihua BianDepartment of Biostatistics, Vanderbilt University, Nashville, Tennessee; and.
Guanhua ChenDepartment of Biostatistics, Vanderbilt University, Nashville, Tennessee; and.
T Alp IkizlerVanderbilt Center for Kidney Disease, Nashville, Tennessee; Division of Nephrology and Hypertension and.
Mark L UnruhDivision of Nephrology, University of New Mexico, Albuquerque, New Mexico.
Khaled Abdel-KaderVanderbilt Center for Kidney Disease, Nashville, Tennessee; Division of Nephrology and Hypertension and khaled.abdel-kader@vanderbilt.edu.

Funding

UNM HSC Clinical and Translational Science CenterUL1TR001449 · NCATS · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI CAMPEN, MATTHEW J, PANDHI, NANCY · 2015 to 2024
$36.9M
Nutrition and Metabolism in Dialysis PatientsK24DK062849 · NIDDK · VANDERBILT UNIVERSITY · PI IKIZLER, TALAT ALP · 2003 to 2012
$1.6M
Developing, Validating, and Implementing a CKD Predictive Model (DELVECKD)K23DK090304 · NIDDK · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ABDEL-KADER, KHALED A · 2011 to 2015
$861k
NCATS NIH HHS UL1 TR001449NIDDK NIH HHS K23 DK090304NIDDK NIH HHS K23DK090304NIDDK NIH HHS K24 DK062849NIDDK NIH HHS K24DK62849
6 · The paper itself

Abstract

BACKGROUND AND

objectivesElectronic health record (EHR) patient portals allow individuals to access their medical information with the intent of patient empowerment. However, little is known about portal use in nephrology patients. We addressed this gap by characterizing adoption of an EHR portal, assessing secular trends, and examining the association of portal adoption and BP control (<140/90 mmHg). DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Patients seen between January 1, 2010, and December 31, 2012, at any of four university-affiliated nephrology offices who had at least one additional nephrology follow-up visit before June 30, 2013, were included. Sociodemographic characteristics, comorbidities, clinical measurements, and office visits were abstracted from the EHR. Neighborhood median household income was obtained from the American Community Survey 2012.

resultsOf 2803 patients, 1098 (39%) accessed the portal. Over 87% of users reviewed laboratory results, 85% reviewed their medical information (e.g., medical history), 85% reviewed or altered appointments, 77% reviewed medications, 65% requested medication refills, and 31% requested medical advice from their renal provider. In adjusted models, older age, African-American race (odds ratio [OR], 0.50; 95% confidence interval [95% CI], 0.39 to 0.64), Medicaid status (OR, 0.53; 95% CI, 0.36 to 0.77), and lower neighborhood median household income were associated with not accessing the portal. Portal adoption increased over time (2011 versus 2010: OR, 1.38 [95% CI, 1.09 to 1.75]; 2012 versus 2010: OR, 1.95 [95% CI, 1.44 to 2.64]). Portal adoption was correlated with BP control in patients with a diagnosis of hypertension; however, in the fully adjusted model this was somewhat attenuated and no longer statistically significant (OR, 1.11; 95% CI, 0.99 to 1.24).

conclusionWhile portal adoption appears to be increasing, greater attention is needed to understand why vulnerable populations do not access it. Future research should examine barriers to the use of e-health technologies in underserved patients with CKD, interventions to address them, and their potential to improve outcomes.

Indexed as

Electronic Health RecordsNephrologyAdultAgedAged, 80 and overFemaleHumansInternetMaleMiddle AgedRetrospective Studieschronic kidney diseaseelectronic health recordhealthcare disparitiespatient portalpersonalized health record

Identifiers

PMID26493242
PMCPMC4633780

What OpenQuestion holds

Textmetadata
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.