Keywords
COVID-19 ×
Table of contents
  1. 1. Clinical Trial
  2. 2. Routine Documentation
  3. 3. Registry/Cohort Study
  4. 4. Quality Assurance
  5. 5. Data Standard
  6. 6. Patient-Reported Outcome
  7. 7. Medical Specialty
Selected data models

You must log in to select data models for download or further analysis.

3 Search results.

GECCO - German Corona Consensus - Covid-19 Research-Dataset - Studieneinschluss/Einschlusskriterien

- 10/28/20 - 13 forms, 1 itemgroup, 3 items, 1 language
Itemgroup: Studieneinschluss/Einschlusskriterien
This version of the GECCO dataset is mainly based on https://art-decor.org/art-decor/decor-datasets--covid19f- on the "final" version published mid to end September 2020. A few items implicated by comments/descriptions of items on art-decor have been added: "Datum der letzten Impfung" (date of last vaccination for all listed vaccinations), "Schweregrad" (Severity of Kidney Diseases), "Ort" (Location of vacation in the last 14 days), "Befund bildgebender Verfahren im Rahmen von COVID-19" added separately for all types of imaging procedures listed, "Symptom Schweregrad" (Severity of Symptoms) for each symptom listed, and an "NCT-/EudraCT-Nummer" item for Study participation. Official German text from http://cocos.team/datasets.html: Zur Bewältigung der aktuellen Pandemie und der damit einhergehenden Behandlung von Patienten fördert das Bundesministerium für Bildung und Forschung (BMBF) ein nationales Netzwerk der Universitätsmedizin im Kampf gegen COVID-19. Unter anderem soll das Netzwerk die Daten der behandelten COVID-19 Patienten systematisch erfassen und bündeln. Die Forschenden sollen die Behandlung der COVID-19-Patienten standardisiert erheben, verfolgen und analysieren. Die hohe Bedrohungslage hat zu intensiver wissenschaftlicher Aktivität zu COVID-19 geführt, wozu zahlreiche regionale, nationale und internationale epidemiologische Erhebungen und Registerstudien zählen. Der Konsensusdatensatz gibt der Wissenschaft um COVID-19 eine gemeinsame Sprache und Arbeitsgrundlage. Inofficial translation: In order to cope with the current pandemic and the associated treatment of patients, the Federal Ministry of Education and Research (BMBF) is funding a national network of university medicine in the fight against COVID-19. Among other things, the network will systematically collect and bundle the data of the treated COVID-19 patients. The researchers are to collect, track and analyze the treatment of COVID-19 patients in a standardized way. The high threat level has led to intensive scientific activity on COVID-19, including numerous regional, national and international epidemiological surveys and register studies. The consensus data set provides a common language and working basis for the science around COVID-19. Additional source: https://simplifier.net/ForschungsnetzCovid-19/ResearchDatasetGECCO/~overview Not yet integrated: Items for "Data Absent Reason", "Certainty of Presence", "Uncertainty of Presence", and "Certainty of absence"; "therapeutic intention", "Medication Statement Status", "EventStatus"; longer versions of the ValueSets published separately from the variables in art-decor.

Krankheitsbeginn / Aufnahme

1 itemgroup, 1 item

Epidemiologische Faktoren

1 itemgroup, 1 item

Outcome bei Entlassung

1 itemgroup, 3 items

Komplikationen

1 itemgroup, 8 items
8 more forms meeting the search are available in the detailed view.

FFPAgainstCOVID - F.1

- 10/28/20 - 1 form, 1 itemgroup, 19 items, 1 language
Itemgroup: FragenPerson
Coronaplasma Project, at the University of Münster. Online Screening. To be eligible, the first three questions (age, health, weight) need to be answered with yes and the rest with no. Local ethics committee approval: AZ 2020-220-f-S

COVID-19 - Corona Anamnese

- 3/30/20 - 1 form, 4 itemgroups, 25 items, 1 language
Itemgroups: Symptome, Kontakt, Risikogebiet, Allgemeine Angaben
Strukturierte Datenerfassung bei Verdacht auf COVID-19 Infektion (Corona Anamnese) Als App verfügbar in den App-Stores von Apple und Google (App-Name "Meine Patientendaten", http://meine-patientendaten.de)