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.

EHR data may be used to establish an efficient approach for large-scale surveillance for childhood diabetes by type, although some manual effort is still needed.

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Introduction Chemical exposures daily pose a significant threat to life. Rapid assessment by first responders/emergency nurses is required to reduce death and disability. Currently, no informatics tools for Irritant Gas Syndrome Agents (IGSA) exposures exist to process victims efficiently, continuously monitor for latent signs/symptoms, or make triage recommendations. This study describes the first step to developing emergency department informatics tools for chemical incidents: validation of signs/symptoms that characterize an IGSA syndrome. Methods Data abstracted from 146 patients treated for chlorine exposure in one emergency department during a 2005 train derailment and 152 patients not exposed (comparison group) were mapped to 93 possible signs/symptoms within two tools (i.e., WISER and CHEMM-IST) designed to assist emergency responders/emergency nurses with managing hazardous material exposures. Inferential statistics (Chi Square/Fisher’s exact test) and diagnostics tests were used to examine mapped signs/symptoms of those exposed/not exposed to chlorine. Results Three clusters of signs/symptoms are statistically associated with an IGSA syndrome (p<0.01): Respiratory: shortness of breath, wheezing, coughing, choking Chest discomfort: tightness, pain, burning Eye, nose and/or throat: pain, irritation, burning The syndrome requires the presence of signs/symptoms from at least two of these clusters. The latency period must also be considered for exposed/potentially exposed individuals. Discussion This study uses actual patient data from a chemical incident to characterize and validate signs/symptoms of an IGSA Syndrome. Validating signs/symptoms is the first step in developing new emergency department informatics tools with the potential to revolutionize the process by which emergency nurses manage triage victims of chemical incidents.