As nations loosen stay-at-home orders and businesses reopen, protecting vulnerable populations and the public at large from the COVID-19 virus is paramount. To help fuel better decisions, analytics company SAS debuts new tools to empower providers, data scientists, and citizens alike — free for public use. The applications democratize powerful analytics to boost preparedness and mitigation efforts with real-time pandemic data.

Many important inpatient and outpatient services were suspended during the pandemic response. SAS and Cleveland Clinic are making optimization models publicly available on GitHub for data scientists. Based on inputs from hospitals, the models can be used to identify optimal restarting plans.

Healthcare organizations may use the models to balance economics and efficient use of resources and the quality of clinical care. Using the models, a hospital may consider medical facilities, services lines (such as orthopedics), and sub-services (such as sports injuries and joint) compared with shared resource constraints, like COVID-19 test kits, ventilators, shared beds, operating rooms and more.

SAS Viya integrates AI and analytics for faster decision-making process

SAS announces $1B investment in artificial intelligence

Also, hospitals and clinics may use the models to prepare for new waves of COVID-19 (or other resource stresses) by understanding critical resource utilization (such as ICU beds and ventilators) within elective services and how to keep some of those resources available while maintaining healthy hospital economics.

Designed for data and analytics professionals, COVID-19 Epidemiological Scenario Analysis is an extension of the collaboration between SAS and the Cleveland Clinic, helping hospitals plan current and future needs with predictive modeling. A new user-driven interface now enables the analytics community to run the same public models that are also available on GitHub.

AI

The new analysis environment uses AI-enabled SAS Health on SAS® Viya® to project the impact of a disease outbreak on the population through various user-driven scenarios, following the population flow through an epidemic’s four stages: susceptibility, exposure, infection, and recovery. The scenario results help governments, health care organizations and equipment manufacturers better understand medical resource needs (like hospital and ICU beds and ECMO and ventilator utilization).

Within the environment, users enter statistics about COVID-19 in their population and then run scenarios to project infection peak, the number of individuals by stage, disease contagiousness, the effect of mitigation strategies, and more. Users can also adjust projections for the region (e.g., population, social distancing interventions), disease characteristics (e.g., incubation, recovery), and hospital-specific parameters (e.g., admission, ICU, length of stay) and download scenario projections for further analysis.

Vulnerable Populations Dashboard helps identify and protect those at risk

Infection prevention is critical as stay-at-home measures relax, especially among individuals at significant risk for severe illness, including adults 65 years and older and people of any age with underlying medical conditions. Continuing to invest in free, publicly available resources to create a better, safer world, a new analytical resource from SAS brings together data from multiple public health sources to visualize these vulnerable populations within each US local community.

Dashboard

To mobilize the citizen scientist, the Novel Coronavirus Vulnerable Populations Dashboard uses SAS Visual Analytics on Viya and the SAS Visual Analytics SDK to allow users of any experience (or none at all) to probe data from their region to understand community-specific risks and make better-informed decisions.

Users can drill down into visualizations and pinpoint areas with high volumes of at-risk individuals. They can see Medicare nursing home providers by state and, in many instances, by county and dive into various population segments, including seniors and populations with chronic conditions and comorbidities. Additionally, they can access data – sourced from the Centers for Disease Control and American Community Survey – via the free Data Discovery Environment to further explore data through predictive models, forecasts, and reports.

SAS invites the analytics community and the general public to play a part in combating the pandemic and safeguarding their communities. To learn more about how SAS is using analytics to help empower partners, customers, and the community, visit the COVID-19 Data Analytics Resource Hub.