Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 ) is responsible for coronavirus disease 2019 (COVID-19), a disease that had not been previously described and for which clinicians need to rapidly adapt their daily practice. The novelty of SARS-CoV-2 produced significant gaps in harmonization of definitions, data collection, and outcome reporting to identify patients who would benefit from potential interventions.
Methods: We describe a multicenter collaboration to develop a comprehensive data collection tool for the evaluation and management of COVID-19 in hospitalized patients. The proposed tool was developed by a multidisciplinary working group of infectious disease physicians, intensivists, and infectious diseases/antimicrobial stewardship pharmacists. The working group regularly reviewed literature to select important patient characteristics, diagnostics, and outcomes for inclusion. The data collection tool consisted of spreadsheets developed to collect data from the electronic medical record and track the clinical course after treatments.
Results: Data collection focused on demographics and exposure epidemiology, prior medical history and medications, signs and symptoms, diagnostic test results, interventions, clinical outcomes, and complications. During the pilot validation phase, there was <10% missing data for most domains and components. Team members noted improved efficiency and decision making by using the tool during interdisciplinary rounds.
Conclusions: We present the development of a COVID-19 data collection tool and propose its use to effectively assemble harmonized data of hospitalized individuals with COVID-19. This tool can be used by clinicians, researchers, and quality improvement healthcare teams. It has the potential to facilitate interdisciplinary rounds, provide comparisons across different hospitalized populations, and adapt to emerging challenges posed by the pandemic.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7454902 | PMC |
http://dx.doi.org/10.1093/ofid/ofaa320 | DOI Listing |
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