We leveraged the largely untapped resource of electronic health record data to address critical clinical and epidemiological questions about Coronavirus Disease 2019 (COVID-19). To do this, we formed an international consortium (4CE) of 96 hospitals across five countries (www.covidclinical.net). Contributors utilized the Informatics for Integrating Biology and the Bedside (i2b2) or Observational Medical Outcomes Partnership (OMOP) platforms to map to a common data model. The group focused on temporal changes in key laboratory test values. Harmonized data were analyzed locally and converted to a shared aggregate form for rapid analysis and visualization of regional differences and global commonalities. Data covered 27,584 COVID-19 cases with 187,802 laboratory tests. Case counts and laboratory trajectories were concordant with existing literature. Laboratory tests at the time of diagnosis showed hospital-level differences equivalent to country-level variation across the consortium partners. Despite the limitations of decentralized data generation, we established a framework to capture the trajectory of COVID-19 disease in patients and their response to interventions.

We leveraged the largely untapped resource of electronic health record data to address critical clinical and epidemiological questions about Coronavirus Disease 2019 . To do this, we formed an international consortium (4CE) of 96 hospitals across 5 countries (www.covidclinical.net). Contributors utilized the Informatics for Integrating Biology and the Bedside (i2b2) or Observational Medical Outcomes Partnership (OMOP) platforms to map to a common data model. The group focused on comorbidities and temporal changes in key laboratory test values. Harmonized data were analyzed locally and converted to a shared aggregate form for rapid analysis and visualization of regional differences and global commonalities. Data covered 27,584 COVID-19 cases with 187,802 laboratory tests. Case counts and laboratory trajectories were concordant with existing literature. Laboratory tests at the time of diagnosis showed hospital-level differences equivalent to country-level variation across the consortium partners. Despite the limitations of decentralized data generation, we established a framework to capture the trajectory of COVID-19 disease in patients and their response to interventions.

The ongoing spread of H5N1 avian influenza in Southeast Asia has raised concern about a worldwide influenza pandemic and has made clear the need to plan in advance for such an event. The federal government has stressed the importance of planning and, in particular, has asked hospitals and public health agencies to develop plans to care for patients outside of traditional healthcare settings. These alternative or acute care centers (ACCs) would be opened when hospitals, emergency departments (EDs), and clinics are overwhelmed by an influenza pandemic. The University of Michigan Hospital System (UMHS), a large tertiary care center in southeast Michigan, has been developing a model for offsite care of patients during an influenza pandemic. This article summarizes our planning efforts and the lessons learned from 2 functional exercises over the past 3 years.