The COVID-19 pandemic poses grave challenges to patients, healthcare providers, and policy-makers. Many of these challenges may be better addressed with timely stratification of patients into risk groups, based on their past and current medical characteristics. Most studies that characterized at-risk patients explored condition-specific patient cohorts or had limited access to patients’ medical history; thus, investigating related questions and, potentially, obtaining biased results.
Our research efforts focus on data from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive individuals from a large nationwide health organization to identify those who suffer from serious complications. We compare the prevalence of pre-existing conditions, extracted from electronic health records (EHRs), between COVID-19 patient cohorts with and without complications to identify the conditions that significantly increase the risk of disease complications in various age and sex strata.
