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Predictive Analytics

3 Ways Predictive Analytics is Advancing the Healthcare Industry

Topic: 3 Ways Predictive Analytics is Advancing the Healthcare Industry

As the healthcare industry has increasingly aimed to deliver proactive, quality care, predictive analytics models have emerged as viable tools for improving outcomes and cutting costs.

From mapping the spread of infectious diseases, to forecasting the potential impact of certain conditions, predictive analytics tools can help organizations stay one step ahead in an unpredictable industry.

Researchers and provider organizations are applying predictive analytics techniques to improve practices across the care continuum, leading to more informed decision-making and better patient care.


Throughout the COVID-19 pandemic, predictive analytics models have played a major role in helping healthcare leaders track and prepare for the spread of the virus.

Researchers at the University of Texas Health Science Center at Houston (UTHealth) recently developed a new COVID-19 tracking tool that leverages predictive modeling to help mitigate the impact of the virus.

“We created this interactive public health dashboard because we wanted to help our fellow Texans. By understanding future trends of this virus, it can help aid in the effective management of local resources,” said José-Miguel Yamal, PhD, an associate professor of biostatistics and data science at UTHealth School of Public Health in Houston and one of the project’s lead developers.

The interactive tool is freely available to the community to inform public health decision-making across the state. In addition to the figures for the daily number of confirmed cases throughout the state, the tool provides charts that show the measure of contagiousness of each COVID-19-positive individual in the region.

“The dashboard identifies the current hot spots, predicts future spread both at the state and county level, and houses relevant public health resources. It can effectively inform decision-makers across Texas to help mitigate the spread of COVID-19,” said Shreela Sharma, PhD, a member of the research team and professor of epidemiology, human genetics, and environmental sciences at UTHealth School of Public Health in Houston.

A team at CommonSpirit Health has also leveraged predictive analytics tools to help public health officials better prepare for the spread of COVID-19. The organization used de-identified cell phone data, public health information, and data from its own care sites to build predictive models and gain insight into COVID-19 dips and surges.

“We started looking at the first peaks of the virus, and there were enough cases for us to do some modeling and prediction. Now, just three months later, we’re looking at the same virus as people are getting back together and the contact rate is going up. And we’re trying to manage this resurgence in our markets,” Joseph Colorafi, MD, System VP of Clinical Data Science for CommonSpirit Health, told HealthITAnalytics.

Topic Discussed: 3 Ways Predictive Analytics is Advancing the Healthcare Industry

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