ArticleJournal of medical Internet research2022
Distinguishing Admissions Specifically for COVID-19 From Incidental SARS-CoV-2 Admissions: National Retrospective Electronic Health Record Study.
Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
36 citing papers in PubMed, 57 citations in OpenAlex.
- Incidence Rates of COVID-19-Associated Hospitalization and Risk Factors for Severe Disease Among American Indian and Alaska Native Persons in the Southwest USA and Alaska.Journal of racial and ethnic health disparities · 2026Observational
- Severe, primary, and incidental COVID-19 in hospitalised children, South Africa: 2020-2023.Journal of global health · 2026Article
- Unsupervised Coverage Sampling to Enhance Clinical Chart Review Coverage for Computable Phenotype Development: Simulation and Empirical Study.JMIR medical informatics · 2025Article
- A case-crossover analysis of short-term PMCommunications medicine · 2025Article
- Schizophrenia, Bipolar, or Major Depressive Disorder and Postacute Sequelae of COVID-19.JAMA network open · 2025Article
- Estimating the Number of Primary vs Incidental COVID-19 Hospitalizations in Santa Clara County.Open forum infectious diseases · 2025Article
- Utilization of Antiviral Treatment for Hospitalized Patients With Mild-to-moderate COVID-19 at High Risk for Disease Progression.Journal of community hospital internal medicine perspectives · 2025Article
- Reusing routine electronic health record data for nationwide COVID-19 surveillance in nursing homes: barriers, facilitators, and lessons learned.BMC medical informatics and decision making · 2024Article
- Misattribution Bias of COVID-19 Hospitalizations in Alberta Using an Admission Algorithm.Journal of the Association of Medical Microbiology and Infectious Disease Canada = Journal officiel de l'Association pour la microbiologie medicale et l'infectiologie Canada · 2024Article
- Mass Spectrometry-Based Metabolomics Reveals a Salivary Signature for Low-Severity COVID-19.International journal of molecular sciences · 2024Article
- Trends in COVID-19-Attributable Hospitalizations Among Adults With Laboratory-Confirmed SARS-CoV-2-COVID-NET, June 2020 to September 2023.Influenza and other respiratory viruses · 2024Article
- Refining the hospitalization rate: A mixed methods approach to differentiate primary COVID-19 from incidental cases.Infection prevention in practice · 2024Article
- Article
- Differentiating patients admitted primarily due to coronavirus disease 2019 (COVID-19) from those admitted with incidentally detected severe acute respiratory syndrome corona-virus type 2 (SARS-CoV-2) at hospital admission: A cohort analysis of German hospital records.Infection control and hospital epidemiology · 2024Article
- Remdesivir is Associated with Reduced Mortality in Patients Hospitalized for COVID-19 Not Requiring Supplemental Oxygen.Open forum infectious diseases · 2024Article
- Neurological diagnoses in hospitalized COVID-19 patients associated with adverse outcomes: A multinational cohort study.PLOS digital health · 2024Article
- Article
- Trends in SARS-CoV-2-related pediatric hospitalizations reported to the Canadian Nosocomial Infection Surveillance Program, March 2020 to December 2022.Antimicrobial stewardship & healthcare epidemiology : ASHE · 2024Article
- US Real-World Effectiveness Study of Nirmatrelvir/Ritonavir in Preventing Hospitalization of High-Risk COVID-19 Patients.Current therapeutic research, clinical and experimental · 2024Article
- Database derived from an electronic medical record-based surveillance network of US emergency department patients with acute respiratory illness.BMC medical informatics and decision making · 2023Article
Corrections and comments
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Authors and funding
22 authors at 9 institutions in 3 countries.
Funding
Abstract
backgroundAdmissions are generally classified as COVID-19 hospitalizations if the patient has a positive SARS-CoV-2 polymerase chain reaction (PCR) test. However, because 35% of SARS-CoV-2 infections are asymptomatic, patients admitted for unrelated indications with an incidentally positive test could be misclassified as a COVID-19 hospitalization. Electronic health record (EHR)-based studies have been unable to distinguish between a hospitalization specifically for COVID-19 versus an incidental SARS-CoV-2 hospitalization. Although the need to improve classification of COVID-19 versus incidental SARS-CoV-2 is well understood, the magnitude of the problems has only been characterized in small, single-center studies. Furthermore, there have been no peer-reviewed studies evaluating methods for improving classification.
objectiveThe aims of this study are to, first, quantify the frequency of incidental hospitalizations over the first 15 months of the pandemic in multiple hospital systems in the United States and, second, to apply electronic phenotyping techniques to automatically improve COVID-19 hospitalization classification.
methodsFrom a retrospective EHR-based cohort in 4 US health care systems in Massachusetts, Pennsylvania, and Illinois, a random sample of 1123 SARS-CoV-2 PCR-positive patients hospitalized from March 2020 to August 2021 was manually chart-reviewed and classified as "admitted with COVID-19" (incidental) versus specifically admitted for COVID-19 ("for COVID-19"). EHR-based phenotyping was used to find feature sets to filter out incidental admissions.
resultsEHR-based phenotyped feature sets filtered out incidental admissions, which occurred in an average of 26% of hospitalizations (although this varied widely over time, from 0% to 75%). The top site-specific feature sets had 79%-99% specificity with 62%-75% sensitivity, while the best-performing across-site feature sets had 71%-94% specificity with 69%-81% sensitivity.
conclusionsA large proportion of SARS-CoV-2 PCR-positive admissions were incidental. Straightforward EHR-based phenotypes differentiated admissions, which is important to assure accurate public health reporting and research.
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