Evidence map›Paper›PMID 41726456›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2024

An Interactive Information Visualization System for Temporal Queries in a Large-scale COVID-19 EHR Dataset (COVID-SPHERE): development and qualitative evaluation.

Yan Huang, Shiqiang Tao, Wei-Chun Chou, Licong Cui, Guo-Qiang Zhang, Xiaojin Li

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Yan HuangMcGovern Medical School.
Shiqiang TaoMcGovern Medical School.
Wei-Chun ChouMcGovern Medical School.
Licong CuiMcWilliams School of Biomedical Informatics.
Guo-Qiang ZhangMcGovern Medical School.
Xiaojin LiMcGovern Medical School.

Funding

SCH: Neurophysiological AI-Ready Data ResourceR01NS126690 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHANG, GUO-QIANG · 2022 to 2025
$1.2M
Biomedical Terminology Quality Assurance for Enhancing Clinical Queries over Electronic Health RecordsR01LM013335 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI CUI, LICONG · 2020 to 2021
$663k
NINDS NIH HHS R01 NS126690NLM NIH HHS R01 LM013335
6 · The paper itself

Abstract

COVID-SPHERE is a self-service web application designed to advance clinical research informatics by facilitating secondary use of Electronic Health Records (EHR) for COVID-19 research. The system employs a flexible EHR concept framework that defines hierarchical concepts and ontologies, enabling clinical researchers to build complex temporal queries through an intuitive, single-click interface without requiring database expertise. Our method dynamically generates MongoDB queries in real-time and offers interactive, faceted visualizations to analyze longitudinal patient activities and integrated health records, supporting both individual patient analysis and population-level research. Hosted on a server managing over 5 TB of data encompassing 30 billion health records spanning 15 years from more than 8.8 million patients, this work demonstrated its generalizability by supporting multiple published research studies investigating various COVID related research topics on epidemiology, treatment outcomes, and long-term sequelae since November 2020. By simplifying the cohort discovery process, COVID-SPHERE reduces the informatics barriers between researchers and EHR data, enhancing the efficiency of clinical and translational research while promoting data-driven insights for COVID-19 surveillance and intervention. Its architecture is applicable to other large-scale clinical research data warehouses, offering a model for future public health informatics systems.

Indexed as

COVID-19Data VisualizationElectronic Health RecordsDashboard SystemsHumansSARS-CoV-2User-Computer Interface

Identifiers

PMID41726456
PMCPMC12919515

What OpenQuestion holds

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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.