Big data and artificial intelligence are currently two of the most important and trending pieces for innovation and predictive analytics in healthcare, leading the digital healthcare transformation. Keralty organization is already working on developing an intelligent big data analytic platform based on machine learning and data integration principles. We discuss how this platform is the new pillar for the organization to improve population health management, value-based care, and new upcoming challenges in healthcare. The benefits of using this new data platform for community and population health include better healthcare outcomes, improvement of clinical operations, reducing costs of care, and generation of accurate medical information. Several machine learning algorithms implemented by the authors can use the large standardized datasets integrated into the platform to improve the effectiveness of public health interventions, improving diagnosis, and clinical decision support. The data integrated into the platform come from Electronic Health Records (EHR), Hospital Information Systems (HIS), Radiology Information Systems (RIS), and Laboratory Information Systems (LIS), as well as data generated by public health platforms, mobile data, social media, and clinical web portals. This massive volume of data is integrated using big data techniques for storage, retrieval, processing, and transformation. This paper presents the design of a digital health platform in a healthcare organization in Colombia to integrate operational, clinical, and business data repositories with advanced analytics to improve the decision-making process for population health management.

Purpose: The purpose of this ecological study was to understand the impact of the density of African American (AA) communities on coronavirus disease 2019 (COVID-19) prevalence and death rate within the three most populous counties in each U.S. state and territory (n=152). Methods: An ecological design was employed for the study. The top three most populous counties of each U.S. state and territory were included in analyses for a final sample size of n=152 counties. Confirmed COVID-19 cases and deaths that were accumulated between January 22, 2020 and April 12, 2020 in each of the three most populous counties in each U.S. state and territory were included. Linear regression was used to determine the association between AA density and COVID-19 prevalence (defined as the percentage of cases for the county population), and death rate (defined as number of deaths per 100,000 population). The models were adjusted for median age and poverty. Results: There was a direct association between AA density and COVID-19 prevalence; COVID-19 prevalence increased 5% for every 1% increase in county AA density (p<0.01). There was also an association between county AA density and COVID-19 deaths; the death rate increased 2 per 100,000 for every percentage increase in county AA density (p=0.02). Conclusion: These findings indicate that communities with a high AA density have been disproportionately burdened with COVID-19. To help develop effective interventions and programs that address this disparity, further study is needed to understand social determinants of health driving inequities for this community.

Importance The novel Coronavirus Disease 2019 (COVID-19), declared a pandemic in March 2020, may present with disproportionately higher rates in underrepresented racial/ethnic minority populations in the United States, including African American communities who have traditionally been over-represented in negative health outcomes. Study Objective To understand the impact of the density of African American communities (defined as the percentage of African Americans in a county) on COVID-19 prevalence and death rate within the three most populous counties in each U.S. state and territory (n=152). Design An ecological study using linear regression was employed for the study. Setting The top three most populous counties of each U.S. state and territory were included in analyses for a final sample size of n=152 counties. Participants Confirmed COVID-19 cases and deaths that were accumulated between January 22, 2020 and April 12, 2020 in each of the three most populous counties in each U.S. state and territory were included. Main outcome measures Linear regression was used to determine the association between African American density and COVID-19 prevalence (defined as the percentage of cases for the county population), and death rate (defined as number of deaths per 100,000 population). The models were adjusted for median age and poverty. Results There was a direct association between African American density and COVID-19 prevalence; COVID-19 prevalence increased 5% for every 1% increase in county AA density (p<.01). There was also an association between county AA density and COVID-19 deaths, such; the death rate increased 2 per 100,000 for every percentage increase in county AA density (p=.02). Conclusion These study findings indicate that communities with a high African American density have been disproportionately burdened with COVID-19. Further study is needed to indicate if this burden is related to environmental factors or individual factors such as types of employment or comorbidities that members of these community have. Question What is the impact of the density of African American communities (defined as the percentage of African Americans in a county) on COVID-19 prevalence and death rate by U.S. counties. Findings This ecological study including the three most populous counties in each U.S. state and territory, found that COVID-19 prevalence increased 5% for every percentage increase in county African American density, and that the death rate increased 2 per hundred thousand for every percentage increase in county African American density. Both were statistically significant increases. Meaning These study findings indicate that communities with a high African American density have been disproportionately burdened with COVID-19.