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What is predictive analytics?
Predictive analytics can help in this scenario through the analysis of the patients electronic health record to review past medical history and current medications to determine which scenario is more likely and where initial efforts should be placed.
John Edwards (2019) reports that predictive analytics is the data analysis aimed at making predictions about future outcomes based on historical data and analytics techniques.Most high priority emergency conditions have predictive factors such as age and previous medical history.Using this knowledge from research along with the data from the electronic health record can predict for the emergency room providers which condition is the most likely cause.
This type of program could also be used by healthcare leaders to predict future healthcare needs.Nurse leaders would use a program such as this to drive patient specific healthcare based on current symptom information combined with previous healthcare data.
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Predictive analytics is a well-studied field with a long track record of accomplishments in numerous organizations and sectors. One of the most talked-about areas in healthcare is predictive analytics and modeling. According to academics and information specialists, predictive analytics is the method of extracting useful information from data sets to identify patterns, trends, and future opportunities. It is essential to remember that predictive analytics does not predict the future; rather, it provides reasonable probabilities for the future. What-if scenarios and risk assessment are the primary foundations of predictive analytics (Jennifer, 2018). Predictive models are used to analyze historical and current data in the healthcare industry to support population health management, chronic disease management, hospital administration, improving patient care, providing efficiencies, achieving financial success, and achieving better health outcomes.
