Evidence map›Paper›PMID 31553434›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2019

Electronic medical record-based cohort selection and direct-to-patient, targeted recruitment: early efficacy and lessons learned.

Hailey N Miller, Kelly T Gleason, Stephen P Juraschek, Timothy B Plante, Cassie Lewis-Land, Bonnie Woods, Lawrence J Appel, Daniel E Ford, Cheryl R Dennison Himmelfarb

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 2 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

38 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Recruitment of Black Adults into Cardiovascular Disease Trials.Journal of the American Heart Association · 2021
    Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Clinical Research Informatics: a Decade-in-Review.Yearbook of medical informatics · 2024
    Review
  18. Article
  19. Article
  20. Implementation ofJournal of clinical and translational science · 2024
    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.

Hailey N MillerSchool of Nursing, Johns Hopkins University, Baltimore, Maryland, USA.
Kelly T GleasonSchool of Nursing, Johns Hopkins University, Baltimore, Maryland, USA.
Stephen P JuraschekDepartment of Medicine, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, Massachusetts, USA.
Timothy B PlanteDepartment of Medicine, Larner College of Medicine, University of Vermont, Burlington, Vermont, USA.
Cassie Lewis-LandInstitute for Clinical and Translational Research, Johns Hopkins University, Baltimore, Maryland, USA.
Bonnie WoodsInstitute for Clinical and Translational Research, Johns Hopkins University, Baltimore, Maryland, USA.
Lawrence J AppelWelch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Daniel E FordWelch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Cheryl R Dennison HimmelfarbSchool of Nursing, Johns Hopkins University, Baltimore, Maryland, USA.

Funding

Institute for Clinical and Translational ResearchUL1TR001079 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2013 to 2017
$60.1M
BEHAVIORAL RESEARCH IN HEART &VASCULAR DISEASET32HL007180 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI MARUTHUR, NISA M · 1985 to 2020
$11.4M
Vitamin D Supplements to Prevent Falls in Older Adults: A Dose-Response TrialU01AG047837 · NIA · JOHNS HOPKINS UNIVERSITY · PI APPEL, LAWRENCE JOHN · 2014 to 2019
$9.5M
Institutional Career Development CoreKL2TR003099 · NCATS · JOHNS HOPKINS UNIVERSITY · PI GEBO, KELLY A · 2019 to 2023
$7.9M
Hopkins Center to Promote resilience in persons and families living with multiple chronic conditions (the PROMOTE Center)P30NR018093 · NINR · JOHNS HOPKINS UNIVERSITY · PI DENNISON HIMMELFARB, CHERYL · 2018 to 2022
$3.1M
Interdisciplinary Training in Cardiovascular Health ResearchT32NR012704 · NINR · JOHNS HOPKINS UNIVERSITY · PI ALLEN, JERILYN K · 2011 to 2020
$1.8M
Vitamin D, Subclinical Cardiovascular Disease, and Orthostatic Hypotension in Older AdultsK23HL135273 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI JURASCHEK, STEPHEN P · 2017 to 2021
$1.1M
NCATS NIH HHS KL2 TR003099NCATS NIH HHS UL1 TR001079NHLBI NIH HHS K23 HL135273NHLBI NIH HHS T32 HL007180NIA NIH HHS U01 AG047837NINR NIH HHS P30 NR018093NINR NIH HHS T32 NR012704
6 · The paper itself

Abstract

objectiveThe study sought to characterize institution-wide participation in secure messaging (SM) at a large academic health network, describe our experience with electronic medical record (EMR)-based cohort selection, and discuss the potential roles of SM for research recruitment. MATERIALS AND

methodsStudy teams defined eligibility criteria to create a computable phenotype, structured EMR data, to identify and recruit participants. Patients with SM accounts matching this phenotype received recruitment messages. We compared demographic characteristics across SM users and the overall health system. We also tabulated SM activation and use, characteristics of individual studies, and efficacy of the recruitment methods.

resultsOf the 1 308 820 patients in the health network, 40% had active SM accounts. SM users had a greater proportion of white and non-Hispanic patients than nonactive SM users id. Among the studies included (n = 13), 77% recruited participants with a specific disease or condition. All studies used demographic criteria for their phenotype, while 46% (n = 6) used demographic, disease, and healthcare utilization criteria. The average SM response rate was 2.9%, with higher rates among condition-specific (3.4%) vs general health (1.4%) studies. Those studies with a more inclusive comprehensive phenotype had a higher response rate. DISCUSSION: Target population and EMR queries (computable phenotypes) affect recruitment efficacy and should be considered when designing an EMR-based recruitment strategy.

conclusionsSM guided by EMR-based cohort selection is a promising approach to identify and enroll research participants. Efforts to increase the number of active SM users and response rate should be implemented to enhance the effectiveness of this recruitment strategy.

Indexed as

Computer SecurityElectronic Health RecordsPatient PortalsPatient SelectionText MessagingAcademic Medical CentersClinical Trials as TopicData MiningHumanscohort selectiondirect messagingelectronic medical recordspatient portal messagingresearch recruitment

Identifiers

PMID31553434
PMCPMC6798572

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.