Highlights
A methodology for obtaining EHR-derived datasets for COVID-19 research is proposed.
It allowed effective reuse of EHRs in a tertiary Hospital during COVID-19 pandemic.
ISARIC-WHO COVID-19 CRF was obtained for 4,489 patients with high coverage.
Detailed Clinical Models provides the flexibility needed to expand the concept model.
ISO 13606, SNOMED CT and LOINC standards were used for modeling and standardization.
, a cumulative total of over 23 million cases of coronavirus disease 2019 (COVID-19) infections and 800,000 related deaths has been reported [1]. Although most infected people present with mild-tomoderate symptoms, about one-third require hospitalization [2] (Last accessed 27 Aug 2020). Identification of valid prognostic factors for patients with COVID-19 might be helpful in the early diagnosis of "high-risk" individuals [3]. Some demographic and clinical variablesnotably age, male sex, smoking or comorbidities such as cardiovascular disease, obesity or diabeteshave been associated with a worse prognosis [4]. By contrast, while some potential blood biomarkers (e.g., lactate dehydrogenase [LDH], C-reactive protein, coagulation parameters or lymphopenia) are emerging [4, 5], the evidence remains scarce and validation using advanced analyses in different cohorts is needed. The use of artificial intelligence (e.g., artificial neural network [ANN]) as a form of predictive analysis could help in this regard, and its combination with standard observation at triage might help to correctly identify those patients at a higher risk [6]. We have studied the prognostic value (in terms of survival) of potential "early" routine biochemistry and hematological biomarkers in patients with COVID-19. This is a retrospective study of all admitted patients diagnosed with COVID-19 (by polymerase chain reaction) in a large public Hospital of Madrid, Spain (Hospital 12 de Octubre) from February 28 to March 30. The protocol was approved by the Ethics Committee of the aforementioned institution (reference #20/222) and adhered to the Declaration of Helsinki. The predictive value (i.e., odds of dying in the hospital versus discharge) of routine serum biochemistry (Cobas 8000 platform; Roche Diagnostics, Risch-Rotkreuz, Switzerland) and hematological parameters (DxH 900 hematology analyzer, Beckman Coulter, Alejandro Santos-Lozano and Fernando Calvo-Boyero contributed equally to this work.
Reuse of Electronic Health Records (EHRs) for specific diseases such as COVID-19 requires data to be recorded and persisted according to international standards. Since the beginning of the COVID-19 pandemic, Hospital Universitario 12 de Octubre (H12O) evolved its EHRs: it identified, modeled and standardized the concepts related to this new disease in an agile, flexible and staged way. Thus, data from more than 200,000 COVID-19 cases were extracted, transformed, and loaded into an i2b2 repository. This effort allowed H12O to share data with worldwide networks such as the TriNetX platform and the 4CE Consortium.
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