Evidence map›Paper›PMID 26828957›Full record

ArticleJournal of biomedical informatics2016

The geographic distribution of cardiovascular health in the stroke prevention in healthcare delivery environments (SPHERE) study.

Caryn Roth, Philip R O Payne, Rory C Weier, Abigail B Shoben, Erica N Fletcher, Albert M Lai, Marjorie M Kelley, Jesse J Plascak, Randi E Foraker

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of biomedical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. 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

9 authors.

Caryn RothDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.
Philip R O PayneDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.
Rory C WeierComprehensive Cancer Center, James Cancer Hospital and Solove Research Institute, The Ohio State University, Columbus, OH, USA; Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH, USA.
Abigail B ShobenDivision of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, USA.
Erica N FletcherDivision of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH, USA.
Albert M LaiDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.
Marjorie M KelleyDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.
Jesse J PlascakDepartment of Health Services, School of Public Health, University of Washington, Seattle, WA, USA.
Randi E ForakerDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA; Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH, USA. Electronic address: rforaker@cph.osu.edu.

Funding

The Ohio State University Center for clinical and Translational ScienceUL1TR001070 · NCATS · OHIO STATE UNIVERSITY · PI JACKSON, REBECCA D · 2013 to 2017
$22.6M
Biobehavioral Cancer Prevention and Control Training ProgramR25CA092408 · NCI · UNIVERSITY OF WASHINGTON · PI PATRICK, DONALD LEE · 2001 to 2015
$7.1M
NCATS NIH HHS UL1 TR001070NCATS NIH HHS UL1TR001070NCI NIH HHS R25 CA092408NCI NIH HHS R25CA092408
6 · The paper itself

Abstract

backgroundCommunity-level factors have been clearly linked to health outcomes, but are challenging to incorporate into medical practice. Increasing use of electronic health records (EHRs) makes patient-level data available for researchers in a systematic and accessible way, but these data remain siloed from community-level data relevant to health. PURPOSE: This study sought to link community and EHR data from an older female patient cohort participating in an ongoing intervention at the Ohio State University Wexner Medical Center to associate community-level data with patient-level cardiovascular health (CVH) as well as to assess the utility of this EHR integration methodology. MATERIALS AND

methodsCVH was characterized among patients using available EHR data collected May through July of 2013. EHR data for 153 patients were linked to United States census-tract level data to explore feasibility and insights gained from combining these disparate data sources. Analyses were conducted in 2014.

resultsUsing the linked data, weekly per capita expenditure on fruits and vegetables was found to be significantly associated with CVH at the p<0.05 level and three other community-level attributes (median income, average household size, and unemployment rate) were associated with CVH at the p<0.10 level.

conclusionsThis work paves the way for future integration of community and EHR-based data into patient care as a novel methodology to gain insight into multi-level factors that affect CVH and other health outcomes. Further, our findings demonstrate the specific architectural and functional challenges associated with integrating decision support technologies and geographic information to support tailored and patient-centered decision making therein.

Indexed as

Cardiovascular SystemDelivery of Health CareElectronic Health RecordsHealth StatusInformation Storage and RetrievalAgedCohort StudiesFemaleGeographic Information SystemsHumansOhioResidence CharacteristicsSocioeconomic FactorsApplied clinical informaticsCardiovascular healthData integrationElectronic health recordsGeographic information systems

Identifiers

PMID26828957
PMCPMC4836963

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.