Evidence map›Paper›PMID 37724311›Full record

ArticleClinical epidemiology2023

Transforming the Information System for Research in Primary Care (SIDIAP) in Catalonia to the OMOP Common Data Model and Its Use for COVID-19 Research.

Berta Raventós, Sergio Fernández-Bertolín, María Aragón, Erica A Voss, Clair Blacketer, Leonardo Méndez-Boo, Martina Recalde, Elena Roel, Andrea Pistillo, Carlen Reyes and 5 more

Abstract read
In one paragraph

Article in Clinical epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

15 authors.

Berta Raventós *Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.ORCID 0000-0002-4668-2970
Sergio Fernández-Bertolín *Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.
María AragónFundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.ORCID 0000-0002-5990-6953
Erica A VossJanssen Pharmaceutical Research and Development, Titusville, NJ, USA.ORCID 0000-0002-0651-0613
Clair BlacketerJanssen Pharmaceutical Research and Development, Titusville, NJ, USA.
Leonardo Méndez-BooSistemes d'Informació dels Serveis d'Atenció Primària (SISAP), Institut Català de la Salut, Barcelona, Spain.ORCID 0000-0002-9215-4378
Martina RecaldeFundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.
Elena RoelFundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.
Andrea PistilloFundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.ORCID 0000-0002-4467-0220
Carlen ReyesFundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.
Sebastiaan van SandijkOdysseus Data Services s.r.o., Prague, Czech Republic.
Lars HalvorsenedenceHealth NV, Kontich, Belgium.ORCID 0009-0006-6779-1136
Peter R RijnbeekDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Edward BurnFundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.ORCID 0000-0002-9286-1128
Talita Duarte-SallesFundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The primary aim of this work was to convert the Information System for Research in Primary Care (SIDIAP) from Catalonia, Spain, to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). Our second aim was to provide a descriptive analysis of COVID-19-related outcomes among the general population. Patients and Methods: We mapped patient-level data from SIDIAP to the OMOP CDM and we performed more than 3,400 data quality checks to assess its readiness for research. We established a general population cohort as of the 1st March 2020 and identified outpatient COVID-19 diagnoses or tested positive for, hospitalised with, admitted to intensive care units (ICU) with, died with, or vaccinated against COVID-19 up to 30th June 2022. Results: After verifying the high quality of the transformed dataset, we included 5,870,274 individuals in the general population cohort. Of those, 604,472 had either an outpatient COVID-19 diagnosis or positive test result, 58,991 had a hospitalisation, 5,642 had an ICU admission, and 11,233 died with COVID-19. A total of 4,584,515 received a COVID-19 vaccine. People who were hospitalised or died were more commonly older, male, and with more comorbidities. Those admitted to ICU with COVID-19 were generally younger and more often male than those hospitalised and those who died. Conclusion: We successfully transformed SIDIAP to the OMOP CDM. From this dataset, a general population cohort of 5.9 million individuals was identified and their COVID-19-related outcomes over time were described. The transformed SIDIAP database is a valuable resource that can enable distributed network research in COVID-19 and beyond.

Indexed as

common data modelelectronic health recordsmedical ontologiesOMOPsecondary data use

Identifiers

PMID37724311
PMCPMC10505380

What OpenQuestion holds

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LicenceCC BY-NC
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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.