Evidence map›Paper›PMID 34328789›Full record

SynthesisJCO clinical cancer informatics2021

Leveraging Health Information Technology to Collect Family Cancer History: A Systematic Review and Meta-Analysis.

Xuan Li, Ryan M Kahn, Noelani Wing, Zhen Ni Zhou, Andreas Ian Lackner, Hannah Krinsky, Nora Badiner, Rhea Fogla, Isabel Wolfe, Hannah Bergeron and 8 more

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in JCO clinical cancer informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–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

7 citing papers in PubMed.

  1. Trial
  2. Article
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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

18 authors.

Xuan LiDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.ORCID 0000-0002-6955-0559
Ryan M KahnDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.ORCID 0000-0002-5596-6238
Noelani WingDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.
Zhen Ni ZhouDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.
Andreas Ian LacknerDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.ORCID 0000-0002-8034-0181
Hannah KrinskyDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.
Nora BadinerDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.ORCID 0000-0003-0779-028X
Rhea FoglaDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.
Isabel WolfeDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.
Hannah BergeronDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.ORCID 0000-0003-2993-1127
Becky Baltich NelsonDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.ORCID 0000-0002-3890-1184
Charlene ThomasDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.
Paul J ChristosDivision of Biostatistics, Department of Population Health Sciences, Weill Cornell Medicine, New York, NY.
Ravi N SharafDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.
Evelyn CantilloDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.
Kevin HolcombDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.ORCID 0000-0002-6916-5271
Eloise Chapman-DavisDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.
Melissa K FreyDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY.ORCID 0000-0002-6705-1211

Funding

Disparities in COVID Disease Severity and Outcomes in New York CityUL1TR002384 · NCATS · WEILL MEDICAL COLL OF CORNELL UNIV · PI JULIANNE L IMPERATO-MCGINLEY · 2017 to 2026
$86.2M
Institutional Career Development CoreKL2TR002385 · NCATS · WEILL MEDICAL COLL OF CORNELL UNIV · PI YUAN-SHAN ZHU · 2017 to 2026
$13.3M
Gene Dependent Cancer Risk and Optimal Cancer Prevention Strategies in Lynch SyndromeK07CA216326 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI SHARAF, RAVI · 2018 to 2021
$675k
NCATS NIH HHS KL2 TR002385NCATS NIH HHS UL1 TR002384NCI NIH HHS K07 CA216326
6 · The paper itself

Abstract

purposeCollection of family cancer histories (FCHs) can identify individuals at risk for familial cancer syndromes. The aim of this study is to evaluate the literature on existing strategies whereby providers use information technology to assemble FCH.

methodsA systematic search of online databases (Ovid MEDLINE, Cochrane, and Embase) between 1980 and 2020 was performed. Statistical heterogeneity was assessed through the chi-square test (ie, Cochrane Q test) and the inconsistency statistic (I

resultsThe comprehensive search produced 4,005 publications. Twenty-eight studies met inclusion criteria. Twenty-seven information technology tools were evaluated. Eighteen out of 28 studies were electronic surveys administered before visits (18, 64.3%). Five studies administered tablet surveys in offices (5, 17.8%). Four studies collected electronic survey via kiosk before visits (4, 14.3%), and one study used animated virtual counselor during visits (1, 3.6%). Among the studies that use an FCH tool, the pooled estimate of the overall completion rate was 86% (CI, 72% to 96%), 84% (CI, 65% to 97%) for electronic surveys before visits, 89% (CI, 0.74 to 0.98) for tablet surveys, and 85% (CI, 0.66 to 0.98) for surveys via kiosk. Mean time required for completion was 31.0 minutes (CI, 26.1 to 35.9), and the pooled estimate of proportions of participants referred to genetic testing was 12% (CI, 4% to 23%).

conclusionOur review found that electronic FCH collection can be completed successfully by patients in a time-efficient manner with high rates of satisfaction.

Indexed as

Medical InformaticsNeoplasmsHumans

Identifiers

PMID34328789
PMCPMC8812651

What OpenQuestion holds

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Registered trials

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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.