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COVID-19 Outcome Prediction and Monitoring Solution for Military Hospitals in South Korea: Development and Evaluation of an Application

Authors
 JoonNyung Heo  ;  Ji Ae Park  ;  Deokjae Han  ;  Hyung-Jun Kim  ;  Daeun Ahn  ;  Beomman Ha  ;  Woong Seog  ;  Yu Rang Park 
Citation
 JOURNAL OF MEDICAL INTERNET RESEARCH, Vol.20(11) : e22131, 2020-11 
Journal Title
 JOURNAL OF MEDICAL INTERNET RESEARCH 
ISSN
 1439-4456 
Issue Date
2020-11
MeSH
Adult ; Betacoronavirus ; COVID-19 ; Coronavirus Infections / diagnosis* ; Coronavirus Infections / epidemiology ; Female ; Hospitalization / statistics & numerical data ; Hospitals, Military* ; Humans ; Male ; Pandemics ; Patients ; Physicians ; Pneumonia, Viral / diagnosis* ; Pneumonia, Viral / epidemiology ; Prognosis ; Proportional Hazards Models ; ROC Curve ; Republic of Korea / epidemiology ; Risk Assessment* ; SARS-CoV-2 ; Software Design* ; Surveys and Questionnaires
Keywords
COVID-19 ; app ; military medicine ; modeling ; monitoring ; outcome ; patient management ; prediction ; prediction model ; proportional hazards models ; usability
Abstract
Background: COVID-19 has officially been declared as a pandemic, and the spread of the virus is placing sustained demands on public health systems. There are speculations that the COVID-19 mortality differences between regions are due to the disparities in the availability of medical resources. Therefore, the selection of patients for diagnosis and treatment is essential in this situation. Military personnel are especially at risk for infectious diseases; thus, patient selection with an evidence-based prognostic model is critical for them. Objective: This study aims to assess the usability of a novel platform used in the military hospitals in Korea to gather data and deploy patient selection solutions for COVID-19. Methods: The platform's structure was developed to provide users with prediction results and to use the data to enhance the prediction models. Two applications were developed: a patient's application and a physician's application. The primary outcome was requiring an oxygen supplement. The outcome prediction model was developed with patients from four centers. A Cox proportional hazards model was developed. The outcome of the model for the patient's application was the length of time from the date of hospitalization to the date of the first oxygen supplement use. The demographic characteristics, past history, patient symptoms, social history, and body temperature were considered as risk factors. A usability study with the Post-Study System Usability Questionnaire (PSSUQ) was conducted on the physician's application on 50 physicians. Results: The patient's application and physician's application were deployed on the web for wider availability. A total of 246 patients from four centers were used to develop the outcome prediction model. A small percentage (n=18, 7.32%) of the patients needed professional care. The variables included in the developed prediction model were age; body temperature; predisease physical status; history of cardiovascular disease; hypertension; visit to a region with an outbreak; and symptoms of chills, feverishness, dyspnea, and lethargy. The overall C statistic was 0.963 (95% CI 0.936-0.99), and the time-dependent area under the receiver operating characteristic curve ranged from 0.976 at day 3 to 0.979 at day 9. The usability of the physician's application was good, with an overall average of the responses to the PSSUQ being 2.2 (SD 1.1). Conclusions: The platform introduced in this study enables evidence-based patient selection in an effortless and timely manner, which is critical in the military. With a well-designed user experience and an accurate prediction model, this platform may help save lives and contain the spread of the novel virus, COVID-19.
Files in This Item:
T202005390.pdf Download
DOI
10.2196/22131
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
Yonsei Authors
Park, Yu Rang(박유랑) ORCID logo https://orcid.org/0000-0002-4210-2094
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/181314
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