Readmission Predictive Risk Model

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The Dickson Advanced Analytics (DA²) launched four pilot programs for the Carolinas HealthCare System (CHS) hospitals with the goals of predicting the health needs of the population they were serving, enhancing patient outcomes, and pushing for transformative solutions that dealt with pressing community health issues (Quelch & Rodriguez, 2015). Of the four pilot programs created (which also includes mapping underserved areas, advance illness management, and patient segmentation), I believe the launching of the Readmission Predictive Risk model has the most value potential for the CHS hospitals not only because it can prevent the chances of patient readmission after discharge but also impact the quality of care given to their patients and avoid

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