Evidence map›Paper›PMID 26951588›Full record

Trial reportAnnals of family medicine2016

Electronic Consultations to Improve the Primary Care-Specialty Care Interface for Cardiology in the Medically Underserved: A Cluster-Randomized Controlled Trial.

J Nwando Olayiwola, Daren Anderson, Nicole Jepeal, Robert Aseltine, Christopher Pickett, Jun Yan, Ianita Zlateva

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Annals of family medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 7 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

51 citing papers in PubMed, 7 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. A Bibliometric Analysis and Visualization of Decision Support Systems for Healthcare Referral Strategies.International journal of environmental research and public health · 2022
    Pooled it
  4. Pooled it
  5. Electronic consultations (E-consults) and their outcomes: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2020
    Pooled it
  6. Guideline
  7. Pooled it
  8. Trial
  9. Trial
  10. Trial
  11. Article
  12. Article
  13. Article
  14. Reaching the Frail Elderly for the Diagnosis and Management of Atrial Fibrillation-REAFEL.International journal of environmental research and public health · 2023
    Article
  15. Article
  16. Article
  17. Article
  18. Formalizing the curbside: digitally enhancing access to specialty care.Proceedings (Baylor University. Medical Center) · 2023
    Article
  19. Article
  20. Review
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

7 authors.

J Nwando OlayiwolaCenter for Excellence in Primary Care, San Francisco General Hospital, San Francisco, California Department of Family and Community Medicine, University of California San Francisco, San Francisco, California OlayiwolaJ@fcm.ucsf.edu.
Daren AndersonWeitzman Institute, Community Health Center, Inc, Middletown, Connecticut.
Nicole JepealRollins School of Public Health, Emory University, Atlanta, Georgia.
Robert AseltineDivision of Behavioral Sciences and Community Health, University of Connecticut Health Center, Farmington, Connecticut.
Christopher PickettPat and Jim Calhoun Cardiology Center, University of Connecticut Health Center, Farmington, Connecticut.
Jun YanDepartment of Statistics, University of Connecticut, Storrs, Connecticut.
Ianita ZlatevaWeitzman Institute, Community Health Center, Inc, Middletown, Connecticut.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeCommunication between specialists and primary care clinicians is suboptimal, and access to referrals is often limited, which can lead to lower quality, inefficiency, and errors. An electronic consultation (e-consultation) is an asynchronous, non-face-to-face consultation between a primary care clinician and a specialist using a secure electronic communication platform. The purpose of this study was to conduct a randomized controlled trial of e-consultations to test its efficacy and effectiveness in reducing wait times and improving access to specialty care.

methodsPrimary care clinicians were randomized into a control (9 traditional) or an intervention (17 e-consultation) arm for referrals to cardiologists. Primary care clinicians were recruited from 12 practice sites in a community health center in Connecticut with mainly medically underserved patients. Two end points were analyzed with a Cox proportional hazards model where the hazard of either a visit or an e-consultation was linked to study arm, sex, race, and age.

resultsThirty-six primary care clinicians participated in the study, referring 590 patients. In total, 69% of e-consultations were resolved without a visit to a cardiologist. After adjusting for covariates, median days to a review for an electronic consultation vs a visit for control patients were 5 and 24, respectively. A review of 6-month follow-up data found fewer cardiac-related emergency department visits for the intervention group.

conclusionE-consultation referrals improved access to and timeliness of care for an underserved population, reduced overall specialty utilization, and streamlined specialty referrals without any increase in adverse cardiovascular outcomes. e-consultations are a potential solution for improving access to specialty care.

Indexed as

CardiologyCommunicationMedically Underserved AreaRemote ConsultationAdultConnecticutFemaleHealth Services AccessibilityHumansMaleMiddle AgedPrimary Health CareProportional Hazards ModelsSingle-Blind MethodSpecialization

Identifiers

PMID26951588
PMCPMC4781516

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.