Background: The availability of accurate, reliable, and timely clinical data is crucial for clinicians, researchers, and policymakers so that they can respond effectively to emerging public health threats. This was typified by the recent SARS-CoV-2 pandemic and the critical knowledge and data gaps associated with novel Coronavirus 2019 disease (COVID-19).We sought to create an adaptive, living data mart containing detailed clinical, epidemiologic, and outcome data from COVID-19 patients in our healthcare system. If successful, the approach could then be used for any future outbreak or disease.

Methods: From 3/13/2020 onward, demographics, comorbidities, outpatient medications, along with 75 laboratory, 2 imaging, 19 therapeutic, and 4 outcome-related parameters, were manually extracted from the electronic medical record (EMR) of SARS-CoV-2 positive patients. These parameters were entered on a registry featuring calculation, graphing tools, pivot tables, and a macro programming language. Initially, two internal medicine residents populated the database, then professional data abstractors populated the registry. Clinical parameters were developed with input from infectious diseases and critical care physicians and using a modified COVID-19 worksheet from the U.S. Centers for Disease Control and Prevention (CDC). Registry contents were migrated to a browser-based, metadata-driven electronic data capture software platform. Eventually, we developed queries and used various business intelligence (BI) tools which enabled us to semi-automate data ingestion of 147 clinical and outcome parameters from the EMR, via a large U.S. hospital-based, service-level, all-payer database. Statistics were performed in R and Minitab.

Results: From March 13, 2020 to May 17, 2021, 549,691 SARS-CoV-2 test results on 236,144 distinct patients, along with location, admission status, and other epidemiologic details are stored on the cloud-based BI platform. From March 2020 until May 2021, extraction of clinical-epidemiologic parameter had to be performed manually. Of those, 543 have had >/=75 parameters fully entered in the registry. Ten clinical characteristics were significantly associated with the need for hospital admission. Only one characteristic was associated with a need for ICU admission. Use of supplemental oxygen, vasopressors and outpatient statin were associated with increased mortality.Initially, 0.5hrs -1.5 hours per patient chart (approximately 450-575 person hours) were required to manually extract the parameters and populate the registry. As of May 17, 2021, semi-automated data ingestion from the U.S. hospital all-payer database, employing user-defined queries, was implemented. That process can ingest and populate the registry with 147 clinical, epidemiologic, and outcome parameters at a rate of 2 hours per 100 patient charts.

Conclusion: A living COVID-19 registry represents a mechanism to facilitate optimal sharing of data between providers, consumers, health information networks, and health plans through technology-enabled, secure-access electronic health information. Our approach also involves a diversity of new roles in the field, such as using residents, staff, and the quality department, in addition to professional data extractors and the health informatics team.Initially, due to the overwhelming number of infections that continues to accelerate, and the labor/time intense nature of the project, only a small fraction of all patients with COVID-19 had all parameters entered in the registry. Therefore, this report also offers lessons learned and discusses sustainability issues, should others wish to establish a registry. It also highlights the registry's local and broader public health significance. Beginning in June 2021, whole-genome sequencing results such as lineages harboring important viral mutations, or variants of concern will be linked to the clinical meta-data.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580456PMC

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