Obtaining EHR-derived datasets for COVID-19 research within a short time: a flexible methodology based on Detailed Clinical Models

Abstract

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.

Use of EHRs in a Tertiary Hospital During COVID-19 Pandemic: A Multi-Purpose Approach Based on Standards

“…The methodology proposed is supported by previous studies on health information [8,10], and it is formed by two stages. First, new clinical concepts essential to cope with the pandemic situation were identified and standardized.…”

“…In this critical scenario, Electronic Health Records (EHRs) must provide an agile response to the needs of healthcare providers and researchers through a useful data exploitation [5]. To that end, representation and exchange of information with full meaning, known as semantic interoperability [6], is a goal to achieve for primary and secondary uses [7,8]. This allows having complete and coherent information regardless of where it was generated, with no errors due to loss of meaning or context [9].…”

Making EHRs Reusable: A Common Framework of Data Operations

“…This work was carried out at Hospital Universitario 12 de Octubre (H12O) in Madrid (Spain), as part of its research line on the effective reuse of EHRs [4,7,8].…”

“…Reusability is determined by how we manage the semantics of concepts and (meta)data in information systems. A first step is provided by Detailed Clinical Models (DCM), which allow implementing mechanisms for obtaining EHR-derived datasets for secondary use [4,5]. However, it is essential that the extraction, transformation and loading processes (ETLs) are based on homogeneous and formalized operations, in order to make them understandable, reproducible and auditable [6].…”

Novel informatics approaches to COVID-19 Research: From methods to applications

“… Methodological Review [7] Machine learning research towards combating COVID-19: Virus detection, spread prevention, and medical assistance Shahid, O. Methodological Review Clinical research and practice (13) [8] Making science computable: Developing code systems for statistics, study design, and risk of bias Alper, B. S. Special Communication [9] Obtaining EHR-derived datasets for COVID-19 research within a short time: a flexible methodology based on Detailed Clinical Models Pedrera-Jimenez, M. Original Research [10] Developing a sampling method and preliminary taxonomy for classifying COVID-19 public health guidance for healthcare organizations and the general public Taber, P. Original Research [11] Visual comprehension and orientation into the COVID-19 CIDO ontology Zheng, L. Original Research [12] Phenotyping coronavirus disease 2019 during a global health pandemic: Lessons learned from the characterization of an early cohort DeLozier, S. Special Communication [13] Extracting COVID-19 diagnoses and symptoms from clinical text: A new annotated corpus and neural event extraction framework Lybarger, K. Original Research [14] ELII: A novel inverted index for fast temporal query, with application to a large Covid-19 EHR dataset Huang, Y. Original Research [15] Creating and implementing a COVID-19 recruitment Data Mart Helmer, T. T. Special Communication [16] Critical carE Database for Advanced Research (CEDAR): An automated method to support intensive care units with electronic health record data Schenck, E. J.…”