Evidence map›Paper›PMID 38546709›Full record

ArticleJMIR research protocols2024

Telehealth Evaluation in the United States: Protocol for a Scoping Review.

Yunxi Zhang, Yueh-Yun Lin, Lincy S Lal, Jennifer C Reneker, Elizabeth G Hinton, Saurabh Chandra, J Michael Swint

Abstract read
In one paragraph

Article in JMIR research protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

7 authors.

Yunxi ZhangDepartment of Data Science, John D Bower School of Population Health, University of Mississippi Medical Center, Jackson, MS, United States.ORCID https://orcid.org/0000-0002-2614-5246
Yueh-Yun LinCenter for Telehealth, University of Mississippi Medical Center, Jackson, MS, United States.ORCID https://orcid.org/0000-0001-9034-7718
Lincy S LalDepartment of Management, Policy and Community Health, The University of Texas School of Public Health, Houston, TX, United States.ORCID https://orcid.org/0000-0002-9123-2434
Jennifer C RenekerDepartment of Population Health Sciences, John D Bower School of Population Health, University of Mississippi Medical Center, Jackson, MS, United States.ORCID https://orcid.org/0000-0003-3617-5681
Elizabeth G HintonRowland Medical Library, University of Mississippi Medical Center, Jackson, MS, United States.ORCID https://orcid.org/0000-0002-3793-2683
Saurabh ChandraCenter for Telehealth, University of Mississippi Medical Center, Jackson, MS, United States.ORCID https://orcid.org/0009-0009-3996-3211
J Michael SwintDepartment of Management, Policy and Community Health, The University of Texas School of Public Health, Houston, TX, United States.ORCID https://orcid.org/0000-0003-4858-5741

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe rapid expansion of telehealth services, driven by the COVID-19 pandemic, necessitates systematic evaluation to guarantee the quality, effectiveness, and cost-effectiveness of telehealth services and programs in the United States. While numerous evaluation frameworks have emerged, crafted by various stakeholders, their comprehensiveness is limited, and the overall state of telehealth evaluation remains unclear.

objectiveThe overarching goal of this scoping review is to create a comprehensive overview of telehealth evaluation, incorporating perspectives from multiple stakeholder categories. Specifically, we aim to (1) map the existing landscape of telehealth evaluation, (2) identify key concepts for evaluation, (3) synthesize existing evaluation frameworks, and (4) identify measurements and assessments considered in the United States.

methodsWe will conduct this scoping review in accordance with the Joanna Briggs Institute (JBI) methodology for scoping reviews and in line with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). This scoping review will consider documents, including reviews, reports, and white papers, published since January 1, 2019. It will focus on evaluation frameworks and associated measurements of telehealth services and programs in the US health care system, developed by telehealth stakeholders, professional organizations, and authoritative sources, excluding those developed by individual researchers, to collect data that reflect the collective expertise and consensus of experts within the respective professional group.

resultsThe data extracted from selected documents will be synthesized using tools such as tables and figures. Visual aids like Venn diagrams will be used to illustrate the relationships between the evaluation frameworks from various sources. A narrative summary will be crafted to further describe how the results align with the review objectives, facilitating a comprehensive overview of the findings. This scoping review is expected to conclude by August 2024.

conclusionsBy addressing critical gaps in telehealth evaluation, this scoping review protocol lays the foundation for a comprehensive and multistakeholder assessment of telehealth services and programs. Its findings will inform policy makers, health care providers, researchers, and other stakeholders in advancing the quality, effectiveness, and cost-effectiveness of telehealth in the US health care system.

trial registrationOSF Registries osf.io/aytus; https://osf.io/aytus. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55209.

Indexed as

costeffectivenessevaluationframeworkhealthcare deliverymeasurementqualityscoping reviewtelehealthUnited States

Identifiers

PMID38546709
PMCPMC11009841

What OpenQuestion holds

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LicenceCC BY
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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.