Reference no: EM133171067

A few years ago Aurora Hospital was trying to figure out a way to integrate their 30,000 caregivers, 15 hospitals, 160 clinics and related home health facilities. The figured the best way to start was to mine the data of all those patients and from that data figure out how to make healthcare more streamlined, more cost-effective, more value based and most importantly better for patient outcomes. They came up with the predictive analytic program and ran a heart failure and COPD pilot that segmented the sickest patients predicted who was at biggest risk for being repeat patients then designed an alternative multidisciplines plan in an attempt to reverse the likelihood of hospital admission.

What this model does is it looks at those really high risk patients and says let's reach out to them proactively, lets get their medications covered, following the right diet, exercise programs and catch the early warning signs. It worked after one year, Aurora saw a reduction in admissions of heart failure patients by 60% and all caused admissions by 20%. By this it helps patients by providing better outcomes for the patients and also freed up new time and space for new patients to be seen. The results were so good congress asked the hospital to come speak before them.

1. Which of the predictive analytics models  (Regression, Times Series, Mixed) is most appropriate in healthcare context? Provide the rationale for your choice.
2. How the use of predictive analytics in healthcare improve patients experience. Select one experience element and elaborate.
3. How the use of predictive analytics in healthcare improve care provider performance? Select one performance and elaborate.