Evidence map›Paper›PMID 33044944›Full record

ArticleJournal of participatory medicine2020

Supporting the Implementation of Connected Care Technologies in the Veterans Health Administration: Cross-Sectional Survey Findings from the Veterans Engagement with Technology Collaborative (VET-C) Cohort.

Bella Etingen, Daniel J Amante, Rachael N Martinez, Bridget M Smith, Stephanie L Shimada, Lorilei Richardson, Angela Patterson, Thomas K Houston, Kathleen L Frisbee, Timothy P Hogan

Abstract read
In one paragraph

Article in Journal of participatory medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

10 authors.

Bella Etingen *eHealth Partnered Evaluation Initiative, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, United States.ORCID https://orcid.org/0000-0003-1325-9073
Daniel J AmanteDivision of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, United States.ORCID https://orcid.org/0000-0003-1488-9624
Rachael N MartinezeHealth Partnered Evaluation Initiative, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-1406-7041
Bridget M SmitheHealth Partnered Evaluation Initiative, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-3301-8843
Stephanie L ShimadaeHealth Partnered Evaluation Initiative, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-6517-5122
Lorilei RichardsoneHealth Partnered Evaluation Initiative, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-9816-1333
Angela PattersonDivision of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, United States.ORCID https://orcid.org/0000-0002-4857-4105
Thomas K HoustoneHealth Partnered Evaluation Initiative, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-2909-4018
Kathleen L FrisbeeOffice of Connected Care, Veterans Health Administration, US Department of Veterans Affairs, Washington, DC, United States.ORCID https://orcid.org/0000-0002-0194-4009
Timothy P HoganeHealth Partnered Evaluation Initiative, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-6888-0927

Funding

University of Massachusetts Center for Clinical and Translational ScienceKL2TR001455 · NCATS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI KIEFE, CATARINA I. · 2015 to 2024
$5.0M
NCATS NIH HHS KL2 TR001455
6 · The paper itself

Abstract

backgroundWidespread adoption, use, and integration of patient-facing technologies into the workflow of health care systems has been slow, thus limiting the realization of their potential. A growing body of work has focused on how best to promote adoption and use of these technologies and measure their impacts on processes of care and outcomes. This body of work currently suffers from limitations (eg, cross-sectional analyses, limited patient-generated data linked with clinical records) and would benefit from institutional infrastructure to enhance available data and integrate the voice of the patient into implementation and evaluation efforts.

objectiveThe Veterans Health Administration (VHA) has launched an initiative called the Veterans Engagement with Technology Collaborative cohort to directly address these challenges. This paper reports the process by which the cohort was developed and describes the baseline data being collected from cohort members. The overarching goal of the Veterans Engagement with Technology Collaborative cohort is to directly engage veterans in the evaluation of new VHA patient-facing technologies and in so doing, to create new infrastructure to support related quality improvement and evaluation activities.

methodsInclusion criteria for veterans to be eligible for membership in the cohort included being an active user of VHA health care services, having a mobile phone, and being an established user of existing VHA patient-facing technologies as represented by use of the secure messaging feature of VHA's patient portal. Between 2017 and 2018, we recruited veterans who met these criteria and administered a survey to them over the telephone.

resultsThe majority of participants (N=2727) were male (2268/2727, 83.2%), White (2226/2727, 81.6%), living in their own apartment or house (2519/2696, 93.4%), and had completed some college (1176/2701, 43.5%) or an advanced degree (1178/2701, 43.6%). Cohort members were 59.9 years old, on average. The majority self-reported their health status as being good (1055/2725, 38.7%) or very good (524/2725, 19.2%). Most cohort members owned a personal computer (2609/2725, 95.7%), tablet computer (1616/2716, 59.5%), and/or smartphone (2438/2722, 89.6%).

conclusionsThe Veterans Engagement with Technology Collaborative cohort is an example of a VHA learning health care system initiative designed to support the data-driven implementation of patient-facing technologies into practice and measurement of their impacts. With this initiative, VHA is building capacity for future, rapid, rigorous evaluation and quality improvement efforts to enhance understanding of the adoption, use, and impact of patient-facing technologies.

Indexed as

eHealthmobile healthpatient engagementtelehealthveterans

Identifiers

PMID33044944
PMCPMC7557445

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.