Predictive analytics models using big data go beyond just predicting buying behaviors or showing Yellowstone fanatics what TV series they should binge next. Healthcare professionals are using the vast amount of data they have collected over the years to understand the history and current illness of a patient to provide an accurate diagnosis. Not only are doctors able to use the models to diagnose patients, they are also able to find the root cause of a disease to help stop the spread of negative health effects. Today more than ever, predictive analytics is saving countless lives during the pandemic. Doctors and scientists are using big data to forecast when the next surge of Covid-19 cases will come. Professional’s at The National Minority Quality Forum (NMQF) have created the Covid-19 Index, “a predictive analytics tool that will help leaders prepare for future surges of coronavirus.” (Health IT Analytics) The index combines historical data beginning in March 2020 with datasets from private and public sources. This dataset allows leaders from all industries to sort by ZIP code, state, county, metropolitan statistical areas, and congressional and state legislative districts.
Access to the Covid-19 Index models allows businesses, government officials, and healthcare organizations to better plan for the future. For example, executives at Walmart can use the index to map out which store locations are located in areas with trends that forecast covid surges. With this information, they can focus their mitigation efforts or implement strict guidelines at these locations prior to the outbreak. In times of public health concern, it is important for companies to show they are proactively looking out for the health of the communities they are located. With the predictive analytics models offered by the Covid-19 Index, there should be no excuse for companies to fall behind the proverbial eight-ball when it comes to public safety. Companies that show they are able to adapt quickly will avoid any major hits to their bottom-line as consumers are able to trust their brand.
More importantly, healthcare organizations can use predictive analytics tools to allocate resources and avoid poor outcomes. According to Health IT Analytics, organizations are using these tools to predict future covid trends in three ways: forecasting disease severity/risk, planning for hospital constraints and demands, and mapping the spread of the virus. Mount Sinai hospital created a model that classified patients on their likelihood to live or die as a result of contracting Covid-19. The forecast was based on three clinical features: age, minimum oxygen saturation, and type of patient encounter. Another model was created to forecast patient volume, bed capacity, ventilator availability, and other metrics to assist hospitals in allocating their resources and optimizing their care for Covid-19 patients.
HealthITAnalytics. (2021, April 6). Predictive Analytics Tool Forecasts Future COVID-19 Surges. HealthITAnalytics. https://healthitanalytics.com/news/predictive-analytics-tool-forecasts-future-covid-19-surges#:~:text=The%20predictive%20analytics%20tool%20can
HealthITAnalytics. (2020, September 25). 3 Ways Healthcare is Using Predictive Analytics to Combat COVID-19. HealthITAnalytics. https://healthitanalytics.com/news/3-ways-healthcare-is-using-predictive-analytics-to-combat-covid-19
COVID-19 Index. (n.d.). Covid.nmqf.us. Retrieved February 15, 2022, from https://covid.nmqf.us/?populationFilter=0
7 Real-world Use Cases of Predictive Analytics | SAP Blogs. (n.d.). Blogs.sap.com. Retrieved February 15, 2022, from https://blogs.sap.com/2021/07/09/7-real-world-use-cases-of-predictive-analytics/#:~:text=Companies%20like%20Amazon%20and%20Netflix