Related Experiment Video
Updated: Jun 26, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Prospective Validation of a Simple Risk Score to Predict Hospitalization during the Omicron Phase of COVID-19
Mark H Ebell1, Roya Hamadani2, Autumn Kieber-Emmons2
1From the Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA (MHE); University of South Florida Morsani College of Medicine and Lehigh Valley Health Network, Allentown, PA (RH, AKE). ebell@uga.edu.
Introduction:
We previously developed a simple risk score with 3 items (age, patient report of dyspnea, and any relevant comorbidity), and in this report validate it in a prospective sample of patients, stratified by vaccination status.
Methods:
Data were abstracted from a structured electronic health record of primary care and urgent care 8 patients with COVID-19 in the Lehigh Valley Health Network from 11/21/2021 and 10/31/2022 9 (Omicron variant). Our previously derived risk score was calculated for each of 19,456 patients, 10 and the likelihood of hospitalization was determined. Area under the ROC curve was calculated.
Results:
We were able to place 13,239 patients (68%) in a low-risk group with only a 0.16% risk of 13 hospitalization. The moderate risk group with 5622 patients had a 2.2% risk of hospitalization 14 and might benefit from close outpatient follow-up, whereas the high-risk group with only 574 15 patients (2.9% of all patients) had an 8.9% risk of hospitalization and may require further 16 evaluation. Area under the curve was 0.844.
Discussion:
We prospectively validated a simple risk score for primary and urgent care patients with COVID1919 that can support outpatient triage decisions around COVID-19.
Related Concept Videos
Relative Risk
Receiver Operating Characteristic Plot
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
Hazard Ratio
For example, in a clinical trial...

