Evidence map›Paper›PMID 28536094›Full record

ArticleJMIR research protocols2017

Using Beta-Version mHealth Technology for Team-Based Care Management to Support Stroke Prevention: An Assessment of Utility and Challenges.

Magaly Ramirez, Shinyi Wu, Gery Ryan, Amytis Towfighi, Barbara G Vickrey

Abstract read
In one paragraph

Article in JMIR research protocols, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Article
  6. Article
  7. 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

5 authors.

Magaly RamirezFielding School of Public Health, Department of Health Policy and Management, University of California, Los Angeles, Los Angeles, CA, United States.ORCID http://orcid.org/0000-0001-5063-1028
Shinyi WuSuzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA, United States.ORCID http://orcid.org/0000-0002-6624-3385
Gery RyanRAND Corporation, Santa Monica, CA, United States.ORCID http://orcid.org/0000-0002-9256-9469
Amytis TowfighiKeck School of Medicine, Department of Neurology, University of Southern California, Los Angeles, CA, United States.ORCID http://orcid.org/0000-0002-9565-6787
Barbara G VickreyDepartment of Neurology, Icahn School of Medicine, Mount Sinai, New York, NY, United States.ORCID http://orcid.org/0000-0003-1878-1936

Funding

Secondary Stroke prevention by Uniting Community and Chronic care model teams Early to End Disparities: the SUCCEED TrialU54NS081764 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BROWN, ARLEEN F. · 2012 to 2016
$11.3M
NINDS NIH HHS U54 NS081764
6 · The paper itself

Abstract

backgroundBeta versions of health information technology tools are needed in service delivery models with health care and community partnerships to confirm the key components and to assess the performance of the tools and their impact on users. We developed a care management technology (CMT) for use by community health workers (CHWs) and care managers (CMs) working collaboratively to improve risk factor control among recent stroke survivors. The CMT was expected to enhance the efficiency and effectiveness of the CHW-CM team.

objectiveThe primary objective was to describe the Secondary Stroke Prevention by Uniting Community and Chronic Care Model Teams Early to End Disparities (SUCCEED) CMT and investigate CM and CHW perceptions of the CMT's usefulness and challenges for team-based care management.

methodsWe conducted qualitative interviews with all users of the beta-version SUCCEED CMT, namely two CMs and three CHWs. They were asked to demonstrate and describe their perceptions of the CMT's ease of use and usefulness for completing predefined key care management activities. They were also probed about their general perceptions of the CMT's information quality, ease of use, usefulness, and impact on CM and CHW roles. Interview transcripts were coded using a priori codes. Coded excerpts were grouped into broader themes and then related in a conceptual model of how the CMT facilitated care management. We also conducted a survey with 14 patients to obtain their perspective on CHW tablet use during CHW-patient interactions.

resultsCare managers and community health workers expressed that the CMT helped them keep track of patient interactions and plan their work. It guided CMs in developing and sharing care plans with CHWs. For CHWs, the CMT enabled electronic collection of clinical assessment data, provided decision support, and provided remote access to patients' risk factor values. Long loading times and downtimes due to outages were the most significant challenges encountered. Additional issues included extensive use of free-text responses and manual data transfer from the electronic medical record. Despite these challenges, patients overall did not perceive the tablet as interfering with CHW-patient interactions.

conclusionsOur findings suggest useful functionalities of CMTs supporting health care and community partners in collaborative chronic care management. However, usability issues need to be addressed during the development process. The SUCCEED CMT is an initial step toward the development of effective health information technology tools to support collaborative, team-based models of care and will need to be modified as the evidence base grows. Future research should assess the CMT's effects on team performance.

Indexed as

community health workershealth care information systemsmobile applicationsmobile devicespatient care managementpatient care teamstroke

Identifiers

PMID28536094
PMCPMC5461415

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.