Evidence map›Paper›PMID 33062736›Full record

ArticleJournal of education and health promotion2020

Coronavirus disease 2019 (COVID-19) surveillance system: Development of COVID-19 minimum data set and interoperable reporting framework.

Mostafa Shanbehzadeh, Hadi Kazemi-Arpanahi, Komeil Mazhab-Jafari, Hamideh Haghiri

Abstract read
In one paragraph

Article in Journal of education and health promotion, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

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

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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

4 authors.

Mostafa ShanbehzadehDepartment of Health Information Technology, School of Paramedical, Ilam University of Medical Sciences, Ilam, Iran.
Hadi Kazemi-ArpanahiDepartment of Health Information Technology, Abadan Faculty of Medical Sciences, Abadan, Iran.
Komeil Mazhab-JafariDepartment of Laboratory Sciences, Abadan Faculty of Medical Sciences, Abadan, Iran.
Hamideh HaghiriDepartment of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe 2019 coronavirus disease (COVID-19) is a major global health concern. Joint efforts for effective surveillance of COVID-19 require immediate transmission of reliable data. In this regard, a standardized and interoperable reporting framework is essential in a consistent and timely manner. Thus, this research aimed at to determine data requirements towards interoperability. MATERIALS AND

methodsIn this cross-sectional and descriptive study, a combination of literature study and expert consensus approach was used to design COVID-19 Minimum Data Set (MDS). A MDS checklist was extracted and validated. The definitive data elements of the MDS were determined by applying the Delphi technique. Then, the existing messaging and data standard templates (Health Level Seven-Clinical Document Architecture [HL7-CDA] and SNOMED-CT) were used to design the surveillance interoperable framework.

resultsThe proposed MDS was divided into administrative and clinical sections with three and eight data classes and 29 and 40 data fields, respectively. Then, for each data field, structured data values along with SNOMED-CT codes were defined and structured according HL7-CDA standard. DISCUSSION AND

conclusionThe absence of effective and integrated system for COVID-19 surveillance can delay critical public health measures, leading to increased disease prevalence and mortality. The heterogeneity of reporting templates and lack of uniform data sets hamper the optimal information exchange among multiple systems. Thus, developing a unified and interoperable reporting framework is more effective to prompt reaction to the COVID-19 outbreak.

Indexed as

coronavirus disease 2019COVID-19minimum data setsemantic interoperabilitysurveillance system

Identifiers

PMID33062736
PMCPMC7530432

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.