The huge amount of data produced by the pandemic has given researchers and providers the ability to examine patterns, monitor patient demographics, and begin to rectify long-standing healthcare industry problems. In the midst of a healthcare crisis, having the ability to forecast potential incidents is crucial, and predictive analytics tools will help healthcare organisations do just that.
FORECASTING DISEASE SEVERITY, RISK
A predictive analytics model based on three clinical features was recently developed by a team from Mount Sinai: age, minimum oxygen saturation, and type of patient experience. The findings have shown that these three characteristics will reliably identify patients with COVID-19 as likely to live or die.
“The application of machine learning methods to data from a broad cohort of COVID-19 patients resulted in the discovery of precise and parsimonious mortality prediction models,” the researchers said.
These data-driven results, after thorough replication in other datasets and health systems, might help clinicians better identify and prioritise the treatment of patients at the greatest risk of death.’
PLANNING FOR HOSPITAL CONSTRAINTS, DEMANDS
With the rapid spread of COVID-19, many hospitals and healthcare systems have faced the risk of unexpected patient volume spikes, resulting in scarce resources and an increased workforce burden.
Organizations have introduced statistical instruments that can assist in allocating resources in order to better prepare for these future spikes.
MAPPING THE SPREAD OF THE VIRUS
Getting an idea of which places will be most affected will allow public health authorities and providers to get ahead of negative outcomes in a situation as uncertain as a global health crisis.
Researchers can identify patterns and trends in various locations using analytics tools that can notify recommendations for social distancing and other interventions.
A team from Binghamton University, New York State University, recently developed multiple models of predictive analytics to analyse trends and patterns in COVID-19 around the world.