Scholay

学术搜索 · AI 审稿 · LaTeX 协作

Ensuring trust in COVID-19 data

作者:Daniel Antwi-Amoabeng, B. Beutler, Gurpreet S Chahal, S. Mahboob, Nageshwara Gullapalli, R. Tedja, F. MADHANI-LOVELY, C. Rowan · 发表于:Medicine · 年份:2021 · DOI:10.1097/md.0000000000026972 · 被引用次数:4749 · 研究领域:Medicine

Abstract There are no standardized methods for collecting and reporting coronavirus disease-2019 (COVID-19) data. We aimed to compare the proportion of patients admitted for COVID-19-related symptoms and those admitted for other reasons who incidentally tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Retrospective cohort study Data were sampled twice weekly between March 26 and June 6, 2020 from a “COVID-19 dashboard,” a system-wide administrative database that includes the number of hospitalized patients with a positive SARS-CoV-2 polymerase chain reaction test. Patient charts were subsequently reviewed and the principal reason for hospitalization abstracted. Data collected during a statewide lockdown revealed that 92 hospitalized patients had positive SARS-CoV-2 test results. Among these individuals, 4.3% were hospitalized for reasons other than COVID-19-related symptoms but were incidentally found to be SARS-CoV-2-positive. After the lockdown was suspended, the total inpatient census of SARS-CoV-2-positive patients increased to 128, 20.3% of whom were hospitalized for non-COVID-19-related complaints. In the absence of a statewide lockdown, there was a significant increase in the proportion of patients admitted for non-COVID-19-related complaints who were incidentally found to be SARS-CoV-2-positive. In order to ensure data integrity, coding should distinguish between patients with COVID-19-related symptoms and asymptomatic patients carryin...