Evidence map›Paper›PMID 32636558›Full record

ArticleMissouri medicine

Assessing Impact of Show-Me ECHO on the Health of Missourians: Two Examples.

Mirna Becevic, Tracy Greever-Rice, Emmanuelle Wallach, Lincoln R Sheets, Kara Braudis, Benjamin Francisco, Kimberly Hoffman, Karen E Edison

Abstract read
In one paragraph

Article in Missouri medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Mirna BecevicAssistant Professor, Department of Dermatology, Lead Evaluator, Show-Me ECHO/Missouri Telehealth Network, University of Missouri-Columbia School of Medicine, Columbia.
Tracy Greever-RiceDirector, Center for Health Policy, Assistant Research Professor, University of Missouri-Columbia, Columbia, Missouri.
Emmanuelle WallachEvaluation Coordinator, Show-Me ECHO/Missouri Telehealth Network, University of Missouri-Columbia School of Medicine, Columbia.
Lincoln R SheetsAssistant Research Professor, Department of Health Management and Informatics, Associate Director of Data and Evaluation, Show-Me ECHO/Missouri Telehealth Network, University of Missouri-Columbia School of Medicine, Columbia.
Kara BraudisAssistant Professor, Department of Dermatology, University of Missouri-Columbia School of Medicine, Columbia.
Benjamin FranciscoTeaching Professor, Pulmonary Medicine, Program Director, Asthma ready® Communities, University of Missouri-Columbia School of Medicine, Columbia.
Kimberly HoffmanProfessor Emerita, Family and Community Medicine, University of Missouri-Columbia School of Medicine, Columbia.
Karen E EdisonMSMA member since 1991, is Professor Emerita of Dermatology, Senior Medical Director, Show-Me ECHO/Missouri Telehealth Network, University of Missouri-Columbia School of Medicine, Columbia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Show Me ECHO is a model for interprofessional collaboration that utilizes telehealth technologies to share evidence-based medical knowledge to improve patient outcomes and minimize variation in care for underserved populations. To measure ECHO outcomes, Show Me ECHO develops both an evaluation of clinical outcomes for patients as well as assessing learner outcomes on the Kirkpatrick Typology of Evaluation. This paper describes evaluation models for Dermatology and Childhood Asthma ECHOs.

Indexed as

Cooperative BehaviorInterprofessional RelationsDermatologyHumansOutcome Assessment, Health CareTelemedicine

Identifiers

PMID32636558
PMCPMC7302023

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.