JMIR Publications

ABSTRACT

Background:

The novel coronavirus disease-2019 (COVID-19) has threatened the health of tens of millions of people all over the world. Massive research efforts have been made in response to the COVID-19 pandemic. Utilization of clinical data can accelerate these research efforts to fight against the pandemic since important characteristics of the patients are often found by examining the clinical data. Publicly accessible clinical data on COVID-19, however, remain limited despite the immediate need.

Objective:

To provide shareable clinical data to catalyze COVID-19 research, we present Columbia Open Health Data for COVID-19 Research (COHD-COVID), a publicly accessible database providing clinical concept prevalence, clinical concept co-occurrence, and clinical symptom prevalence for hospitalized COVID-19 patients. COHD-COVID also provides data on hospitalized influenza patients and general hospitalized patients as comparator cohorts.

Methods:

The data used in COHD-COVID were obtained from NewYork Presbyterian Hospital/Columbia University Irving Medical Center’s electronic health records database. Condition, drug, and procedure concepts were obtained from the visits of identified patients from the cohorts. Rare concepts were excluded and the true concept counts were perturbed using Poisson randomization to protect patient privacy. Concept prevalence, concept prevalence ratio, concept co-occurrence, and symptom prevalence were calculated using the obtained concepts.

Results:

Concept prevalence and concept prevalence ratio analyses showed clinical characteristics of COVID-19 cohorts, confirming well-known conditions of COVID-19 (e.g., acute lower respiratory tract infection and cough) recorded high prevalence and high prevalence ratio in the COVID-19 cohort compared to the hospitalized influenza cohort and general hospitalized cohort. Concept co-occurrence analyses showed potential associations between specific concepts. In case of acute lower respiratory tract infection in the COVID-19 cohort, it showed high co-occurrence ratio with COVID-19 related concepts and commonly used drugs (e.g., disease due to coronavirus and acetaminophen). Symptom prevalence analysis indicated symptom-level characteristics of the cohorts confirming that well-known symptoms of COVID-19 (e.g., fever, cough, and dyspnea) showed higher prevalence than the hospitalized influenza cohort and general hospitalized cohort.

Conclusions:

We present COHD-COVID, a publicly accessible database providing useful clinical data for hospitalized COVID-19 patients, hospitalized influenza patients, and general hospitalized patients. We expect COHD-COVID will provide researchers and clinicians quantitative measures of COVID-19 related clinical features to better understand and fight against the pandemic.