Analysis Of Data Quality/Completeness In Covid-19 Cases : Why A Digital Integrated Data Collection Is Also Necessary For Pandemic Control
Thieme. All rights reserved..
BACKGROUND: Epidemiological data on the corona pandemic collected in the public health sector in Germany have been less useful in estimating vaccine effectiveness and clinical outcomes compared to other countries.
METHODS: In this retrospective observational study, we examined the completeness of selected own data collected during the pandemic. Information on the important parameters of hospitalization, vaccination status and risk factors for severe course and death over different periods were considered and evaluated descriptively. The data are discussed in the extended context of required digital strategies in Germany.
RESULTS: From January 1, 2022 to June 30, 2022, we found 126,920 administrative procedures related to COVID-19. With regard to the data on hospitalization, in 19,749 cases, it was stated "No", in 1,990 cases "Yes" and in 105,181 cases (83+%) "Not collected" or "Not ascertainable". Concerning vaccinations, only a small proportion of procedures contained information on the type of vaccine (11.1+%), number of vaccinations (4.4+%) and date of the last vaccination (2.1+%). The completeness of data on chronic conditions/risk factors in COVID-19-related deaths decreased over four consecutive periods between 2020 and 2022 as case numbers increased.
CONCLUSION: Future strategies taking into account meaningfulness and completeness of data must comprise modern technical solutions with digital data collection on infections without putting the principle of data protection at risk.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2024 |
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Erschienen: |
2024 |
Enthalten in: |
Zur Gesamtaufnahme - year:2024 |
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Enthalten in: |
Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)) - (2024) vom: 10. Apr. |
Sprache: |
Deutsch |
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Weiterer Titel: |
Analyse zur Datenqualität/-vollständigkeit bei COVID-19-Fällen: Warum eine digitale integrierte Datenerfassung auch zur Pandemiebekämpfung notwendig ist |
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Beteiligte Personen: |
Lampl, Benedikt Mj [VerfasserIn] |
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Links: |
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Anmerkungen: |
Date Revised 10.04.2024 published: Print-Electronic Citation Status Publisher |
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doi: |
10.1055/a-2234-6894 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM370889304 |
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246 | 3 | 3 | |a Analyse zur Datenqualität/-vollständigkeit bei COVID-19-Fällen: Warum eine digitale integrierte Datenerfassung auch zur Pandemiebekämpfung notwendig ist |
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520 | |a Thieme. All rights reserved. | ||
520 | |a BACKGROUND: Epidemiological data on the corona pandemic collected in the public health sector in Germany have been less useful in estimating vaccine effectiveness and clinical outcomes compared to other countries | ||
520 | |a METHODS: In this retrospective observational study, we examined the completeness of selected own data collected during the pandemic. Information on the important parameters of hospitalization, vaccination status and risk factors for severe course and death over different periods were considered and evaluated descriptively. The data are discussed in the extended context of required digital strategies in Germany | ||
520 | |a RESULTS: From January 1, 2022 to June 30, 2022, we found 126,920 administrative procedures related to COVID-19. With regard to the data on hospitalization, in 19,749 cases, it was stated "No", in 1,990 cases "Yes" and in 105,181 cases (83+%) "Not collected" or "Not ascertainable". Concerning vaccinations, only a small proportion of procedures contained information on the type of vaccine (11.1+%), number of vaccinations (4.4+%) and date of the last vaccination (2.1+%). The completeness of data on chronic conditions/risk factors in COVID-19-related deaths decreased over four consecutive periods between 2020 and 2022 as case numbers increased | ||
520 | |a CONCLUSION: Future strategies taking into account meaningfulness and completeness of data must comprise modern technical solutions with digital data collection on infections without putting the principle of data protection at risk | ||
650 | 4 | |a English Abstract | |
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