Evidence map›Paper›PMID 32618999›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2020

Rapid development of visualization dashboards to enhance situation awareness of COVID-19 telehealth initiatives at a multihospital healthcare system.

Ram A Dixit, Stephen Hurst, Katharine T Adams, Christian Boxley, Kristi Lysen-Hendershot, Sonita S Bennett, Ethan Booker, Raj M Ratwani

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

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

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  8. Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022
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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

8 authors.

Ram A DixitMedStar Health National Center for Human Factors in Healthcare, Washington, DC, USA.
Stephen HurstMedStar Simulation Training and Education Lab, Washington, DC, USA.
Katharine T AdamsMedStar Health National Center for Human Factors in Healthcare, Washington, DC, USA.
Christian BoxleyMedStar Health National Center for Human Factors in Healthcare, Washington, DC, USA.
Kristi Lysen-HendershotMedStar Telehealth Innovation Center, Washington, DC, USA.
Sonita S BennettMedStar Health National Center for Human Factors in Healthcare, Washington, DC, USA.
Ethan BookerMedStar Telehealth Innovation Center, Washington, DC, USA.
Raj M RatwaniMedStar Health National Center for Human Factors in Healthcare, Washington, DC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has led to the rapid expansion of telehealth services as healthcare organizations aim to mitigate community transmission while providing safe patient care. As technology adoption rapidly increases, operational telehealth teams must maintain awareness of critical information, such as patient volumes and wait times, patient and provider experience, and telehealth platform performance. Using a model of situation awareness as a conceptual foundation and a user-centered design approach we describe our process for rapidly developing and disseminating dashboard visualizations to support telehealth operations. We used a 5-step process to gain domain knowledge, identify user needs, identify data sources, design and develop visualizations, and iteratively refine these visualizations. Through this process we identified 3 distinct stakeholder groups and designed and developed visualization dashboards to meet their needs. Feedback from users demonstrated the dashboard's support situation awareness and informed important operational decisions. Lessons learned are shared to provide other organizations with insights from our process.

Indexed as

Coronavirus InfectionsData DisplayData VisualizationPandemicsPneumonia, ViralTelemedicineBetacoronavirusCOVID-19HumansMid-Atlantic RegionMulti-Institutional SystemsOrganizational Case StudiesSARS-CoV-2User-Computer Interface

Identifiers

PMID32618999
PMCPMC7337800

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.