Cleveland Clinic, a nonprofit multispecialty academic medical centre in the US, has joined hands with analytics company SAS to share Covid-19 predictive models to help hospitals around the world plan for current and future requirements.

 

These models help forecast bed and ventilator needs and predict impacts on critical supply chains, finance and staffing to optimize hospital preparedness before, during and after regional peaks.

 

In its fight against the novel coronavirus pandemic, the duo has created innovative models to help hospitals forecast patient volume, bed capacity, ventilator availability and more.

 

The models, which are freely available via GitHub, provide timely, reliable information for hospitals and health departments to optimize health care delivery for COVID-19 and other patients and to predict impacts on supply chain, finance and other critical areas.

 

Unlike some forecasts that focus on a projection based on a single set of assumptions, these analytic models were used to create worst-case, best-case and most-likely scenarios, and can adjust in real time as the situation and data change. For example, the models can factor in social distancing’s dampening effect on disease spread.

 

“These predictive models were developed jointly by two organizations that understand patient populations, data and modeling,” said Chris Donovan, executive director of Enterprise Information Management & Analytics at Cleveland Clinic. 

 

“We are sharing the models publicly so health systems and government agencies globally can use them in their own communities. Our hope is that others contribute their ideas and improvements to the models as well,” stated Donovan.

 

Cleveland Clinic said it is using the models to support its decision making. With this information, it can predict and plan for future demands on the health system, such as ICU beds, personal protective equipment and ventilators. 

 

After reviewing possible Covid-19 surge scenarios in the US generated by the models, Cleveland Clinic elected to activate a plan that prepared it for the worst-case scenario and has built a 1,000-bed surge hospital on its education campus for the virus patients who don’t need ICU care. 

 

The hospital system also used the models to inform decisions about organizing and activating new labor pools.

 

The GitHub link where the models are available has been visited more than 1,700 times in the past two weeks, resulting in more than 50 downloads.

 

“These models can help hospitals, health care facilities, state departments of health and government agencies forecast the impact of COVID-19 and prepare for the future,” said Steve Bennett, Ph.D., Director of SAS’ Global Government Practice.

 

 “The models can also assist more vulnerable, less developed health systems in the fight against COVID-19,” he added.-TradeArabia News Service