Evidence map›Paper›PMID 29512060›Full record

ReviewJournal of genetic counseling2018

Review and Comparison of Electronic Patient-Facing Family Health History Tools.

Brandon M Welch, Kevin Wiley, Lance Pflieger, Rosaline Achiangia, Karen Baker, Chanita Hughes-Halbert, Heath Morrison, Joshua Schiffman, Megan Doerr

Abstract readComparative StudyReview
In one paragraph

Review in Journal of genetic counseling, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 3 pooled it
8.0field-weighted citation impact, top 2% 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

41 citing papers in PubMed, 3 syntheses or guidelines pooled it, 75 citations in OpenAlex.

  1. Family history tools for primary care: A systematic review.The European journal of general practice · 2022
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  20. PREDICTION OF HEREDITARY CANCERS USING NEURAL NETWORKS.The annals of applied statistics · 2022
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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

9 authors at 5 institutions in 1 country.

Brandon M WelchBiomedical Informatics Center, Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA. welchbm@musc.edu.ORCID 0000-0002-2214-9282
Kevin WileyRichard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA.
Lance PfliegerDepartment of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.
Rosaline AchiangiaBiomedical Informatics Center, Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
Karen BakerHollings Cancer Center, Medical University of South Carolina, Charleston, SC, USA.
Chanita Hughes-HalbertDepartment of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA.
Heath MorrisonItRunsInMyFamily.com, Inc., Charleston, SC, USA.
Joshua SchiffmanItRunsInMyFamily.com, Inc., Charleston, SC, USA.
Megan DoerrSage Bionetworks, Seattle, WA, USA.
Medical University of South Carolina · USUniversity of Utah · USIndiana University Indianapolis · USSage Bionetworks · USUniversity of Charleston · US

Funding

Translational Science Laboratory Shared ResourceP30CA138313 · NCI · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI Jian Ouyang · 2009 to 2026
$42.7M
UNIVERSITY OF UTAH MEDICAL INFORMATICS TRAININGT15LM007124 · NLM · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Karen Louise Eilbeck · 1997 to 2026
$22.0M
Improving cancer family history collection through social networking and artificial intelligenceK07CA211786 · NCI · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI WELCH, BRANDON M · 2016 to 2020
$867k
NCI NIH HHS K07 CA211786NCI NIH HHS P30 CA138313NLM NIH HHS T15 LM007124
6 · The paper itself

Abstract

Family health history (FHx) is one of the most important pieces of information available to help genetic counselors and other clinicians identify risk and prevent disease. Unfortunately, the collection of FHx from patients is often too time consuming to be done during a clinical visit. Fortunately, there are many electronic FHx tools designed to help patients gather and organize their own FHx information prior to a clinic visit. We conducted a review and analysis of electronic FHx tools to better understand what tools are available, to compare and contrast to each other, to highlight features of various tools, and to provide a foundation for future evaluation and comparisons across FHx tools. Through our analysis, we included and abstracted 17 patient-facing electronic FHx tools and explored these tools around four axes: organization information, family history collection and display, clinical data collected, and clinical workflow integration. We found a large number of differences among FHx tools, with no two the same. This paper provides a useful review for health care providers, researchers, and patient advocates interested in understanding the differences among the available patient-facing electronic FHx tools.

Indexed as

Electronic Health RecordsMedical History TakingFemaleHumansRisk FactorsFamily health historyFamily history toolsHealth ITPatient engagementPedigree

Identifiers

PMID29512060
PMCPMC5861014
OpenAlexW2791910581

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.