Misailovski, M.; Koller, D.; Blaschke, S.; Berens, M.; Köster, A.M.; Strobl, R.; Berner, R.; Boor, P.; Eisenmann, M.; von Stillfried, S.; Krefting, D.; Krone, M.; Liese, J.; Meybohm, P.; Ulrich- Merzenich, G.; Zenker, S.; Scheithauer, S.; Grill, E. (2024): Refining the hospitalization rate: A mixed methods approach to differentiate primary COVID-19 from incidental cases. Infection Prevention in Practice, 6 (3): 100371. ISSN 25900889
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Abstract
Purpose
Until now, the Hospitalization Rate (HR) served as an indicator (among others) for the COVID-19 associated healthcare burden. To ensure that the HR accomplishes its full potential, hospitalizations caused by COVID-19 (primary cases) and hospitalizations of patients with incidental positive SARS-CoV-2 test results (incidental cases) must be differentiated. The aim of this study was to synthesize the existing evidence on differentiation criteria between hospitalizations of primary cases and incidental cases.
Methods
An online survey of the members of the German Network University Medicine (NUM) was conducted. Additionally, senior clinicians with expertise in COVID-19 care were invited for qualitative, semi-structured interviews. Furthermore, a rapid literature review was undertaken on publications between 03/2020 and 12/2022.
Results
In the online survey (n=30, response rate 56%), pneumonia and acute upper respiratory tract infections were the most indicative diagnoses for a primary case. In contrast, malignant neoplasms and acute myocardial infarctions were most likely to be associated with incidental cases. According to the experts (n=6), the diagnosis, ward, and type of admission (emergency or elective), low oxygen saturation, need for supplemental oxygen, and initiation of COVID-19 therapy point to a primary case. The literature review found that respiratory syndromes and symptoms, oxygen support, and elevated levels of inflammatory markers were associated with primary cases.
Conclusion
There are parameters for the differentiation of primary from incidental cases to improve the objective of the HR. Ultimately, an updated HR has the potential to serve as a more accurate indicator of the COVID-19 associated healthcare burden.
Doc-Type: | Article (LMU) |
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Organisational unit (Faculties): | 07 Medicine > Institute for Medical Information Processing, Biometry and Epidemiology |
DFG subject classification of scientific disciplines: | Life sciences |
Date Deposited: | 03. Sep 2024 14:28 |
Last Modified: | 03. Sep 2024 14:28 |
URI: | https://oa-fund.ub.uni-muenchen.de/id/eprint/1453 |
DFG: | Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 491502892 |