Utilization of an Electronic Health Record Integrated Risk Score to Predict Hospitalization Among COVID-19 Patients
| Autor: | Mark A. Nyman, Thulasee Jose, Ivana T. Croghan, Mark A. Parkulo, Charles D. Burger, Darrell R. Schroeder, Ryan T. Hurt, John C. O’Horo |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Journal of Primary Care & Community Health, Vol 13 (2022) |
| Druh dokumentu: | article |
| ISSN: | 2150-1327 21501319 |
| DOI: | 10.1177/21501319211069748 |
| Popis: | Objective: To evaluate the performance of an Electronic Health Record (EHR) integrated risk score for COVID-19 positive outpatients to predict 30-day risk of hospitalization. Patients and Methods: A retrospective observational study of 67 470 patients with COVID-19 confirmed by polymerase chain reaction (PCR) test between March 12, 2020 and February 8, 2021. Risk scores were calculated based on data in the chart at the time of the incident infection. Results: The Mayo Clinic COVID-19 risk score consisted of 13 components included age, sex, chronic lung disease, congenital heart disease, congestive heart failure, coronary artery disease, diabetes mellitus, end stage liver disease, end stage renal disease, hypertension, immune compromised, nursing home resident, and pregnant. Univariate analysis showed all components, except pregnancy, have significant ( P |
| Databáze: | Directory of Open Access Journals |
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