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Columbia Open Health Data for COVID-19 Research: Database Analysis
Junghwan Lee1, Jae Hyun Kim1, Cong Liu1
1Columbia University, New York, NY, United States.
This study introduces COHD-COVID, a new database of COVID-19 patient clinical data. It offers valuable insights into disease characteristics and aids researchers in combating the pandemic.
Area of Science:
- Medical Informatics
- Epidemiology
- Public Health
Background:
- COVID-19 has caused a global health crisis, necessitating extensive research.
- Clinical data is crucial for understanding patient characteristics and combating the pandemic.
- Limited availability of public COVID-19 clinical data hinders research efforts.
Purpose of the Study:
- To establish the Columbia Open Health Data for COVID-19 Research (COHD-COVID) database.
- To provide shareable clinical data, including concept prevalence, co-occurrence, and symptom prevalence for COVID-19 patients.
- To offer comparator data for hospitalized influenza and general patient cohorts.
Main Methods:
- Utilized electronic health records from NewYork-Presbyterian/Columbia University Irving Medical Center.
- Extracted condition, drug, and procedure concepts from patient visits.
- Applied Poisson randomization to perturbed concept counts for patient privacy.
- Calculated concept prevalence, co-occurrence, and symptom prevalence.
Main Results:
- Confirmed known COVID-19 clinical characteristics (e.g., acute lower respiratory tract infection, cough) through prevalence and ratio analyses.
- Identified high prevalence and prevalence ratios for COVID-19 characteristics compared to influenza and general hospitalized cohorts.
- Revealed potential concept associations, such as acute lower respiratory tract infection with COVID-19 and acetaminophen.
- Symptom prevalence analysis highlighted higher rates of fever, cough, and dyspnea in COVID-19 patients.
Conclusions:
- Introduced COHD-COVID, a publicly accessible database of clinical data for COVID-19, influenza, and general hospitalized patients.
- COHD-COVID provides researchers and clinicians with quantitative measures of COVID-19 clinical features.
- The database is expected to enhance understanding and aid in combating the COVID-19 pandemic.
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