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arXiv · 2102.02697

Covid-19 risk factors: Statistical learning from German healthcare claims data

Roland Jucknewitz·Oliver Weidinger·Anja Schramm
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Abstract

We analyse prior risk factors for severe, critical or fatal courses of Covid-19 based on a retrospective cohort using claims data of the AOK Bayern. As our main methodological contribution, we avoid prior grouping and pre-selection of candidate risk factors. Instead, fine-grained hierarchical information from medical classification systems for diagnoses, pharmaceuticals and procedures are used, resulting in more than 33,000 covariates. Our approach has better predictive ability than well-specified morbidity groups but does not need prior subject-matter knowledge. The methodology and estimated coefficients are made available to decision makers to prioritize protective measures towards vulnerable subpopulations and to researchers who like to adjust for a large set of confounders in studies of individual risk factors.

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Roland Jucknewitz, Oliver Weidinger, Anja Schramm. 2021-02-04. Covid-19 risk factors: Statistical learning from German healthcare claims data. https://arxiv.org/abs/2102.02697

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