Evidence map›Paper›PMID 35544440›Full record

ArticleJMIR public health and surveillance2022

A Standard-Based Citywide Health Information Exchange for Public Health in Response to COVID-19: Development Study.

Bala Hota, Paul Casey, Anne F McIntyre, Jawad Khan, Shafiq Rab, Aneesh Chopra, Omar Lateef, Jennifer E Layden

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2022. 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

8 authors.

Bala HotaTendo Systems, Inc, Hinsdale, IL, United States.ORCID 0000-0003-4389-1109
Paul CaseyRush University Medical Center, Chicago, IL, United States.ORCID 0000-0002-8638-0432
Anne F McIntyreCenters for Disease Control and Prevention, Atlanta, GA, United States.ORCID 0000-0001-6611-9002
Jawad KhanWellforce, Burlington, MA, United States.ORCID 0000-0002-9692-9476
Shafiq RabWellforce, Burlington, MA, United States.ORCID 0000-0002-8855-7254
Aneesh ChopraCareJourney, Washington, DC, United States.ORCID 0000-0002-9634-2093
Omar LateefRush University Medical Center, Chicago, IL, United States.ORCID 0000-0002-5116-932X
Jennifer E LaydenCenters for Disease Control and Prevention, Atlanta, GA, United States.ORCID 0000-0002-1264-2348

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDisease surveillance is a critical function of public health, provides essential information about the disease burden and the clinical and epidemiologic parameters of disease, and is an important element of effective and timely case and contact tracing. The COVID-19 pandemic demonstrates the essential role of disease surveillance in preserving public health. In theory, the standard data formats and exchange methods provided by electronic health record (EHR) meaningful use should enable rapid health care data exchange in the setting of disruptive health care events, such as a pandemic. In reality, access to data remains challenging and, even if available, often lacks conformity to regulated standards.

objectiveWe sought to use regulated interoperability standards already in production to generate awareness of regional bed capacity and enhance the capture of epidemiological risk factors and clinical variables among patients tested for SARS-CoV-2. We described the technical and operational components, governance model, and timelines required to implement the public health order that mandated electronic reporting of data from EHRs among hospitals in the Chicago jurisdiction. We also evaluated the data sources, infrastructure requirements, and the completeness of data supplied to the platform and the capacity to link these sources.

methodsFollowing a public health order mandating data submission by all acute care hospitals in Chicago, we developed the technical infrastructure to combine multiple data feeds from those EHR systems-a regional data hub to enhance public health surveillance. A cloud-based environment was created that received ELR, consolidated clinical data architecture, and bed capacity data feeds from sites. Data governance was planned from the project initiation to aid in consensus and principles for data use. We measured the completeness of each feed and the match rate between feeds.

resultsData from 88,906 persons from CCDA records among 14 facilities and 408,741 persons from ELR records among 88 facilities were submitted. Most (n=448,380, 90.1%) records could be matched between CCDA and ELR feeds. Data fields absent from ELR feeds included travel histories, clinical symptoms, and comorbidities. Less than 5% of CCDA data fields were empty. Merging CCDA with ELR data improved race, ethnicity, comorbidity, and hospitalization information data availability.

conclusionsWe described the development of a citywide public health data hub for the surveillance of SARS-CoV-2 infection. We were able to assess the completeness of existing ELR feeds, augment those feeds with CCDA documents, establish secure transfer methods for data exchange, develop a cloud-based architecture to enable secure data storage and analytics, and produce dashboards for monitoring of capacity and the disease burden. We consider this public health and clinical data registry as an informative example of the power of common standards across EHRs and a potential template for future use of standards to improve public health surveillance.

Indexed as

COVID-19Health Information ExchangeHumansPandemicsPublic HealthSARS-CoV-2acute care hospitalCOVID-19data governancedata hubdisease surveillanceelectronic health recordepidemiologyhealth datainformaticspandemicpublic healthsurveillance

Identifiers

PMID35544440
PMCPMC9518711

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.