The key objective of this course is to consider new ways for the diagnosis of patient treatment since not all patients respond to a drug in the same way and a one-size-fits-all approach to patient treatment may have very little effect or serious side-effects for patients. With new and advanced technology there is now a move towards using a data driven approach for diagnosing patient treatment. This course covers the benefits and challenges of Personalized Treatment Plans. It is also introduces how 'Predictive Analytics', 'Recommendation Engines' and 'Text Mining' may be used for building effective Personalized Treatment Plans. This course concludes with the Healthcare Information Privacy and Security Requirements for Personalized Patient Treatments.
What am I going to get from this course?
- Build a Personalized Treatment Plan using a 4-Step Process
- Evaluate the Effectiveness of a Personalized Treatment Plan by computing the percent effectiveness for Personalized Treatments versus Standard Treatments
- Understand the Use and Benefits of:
- Electronic Medical Records
- Decision Support Systems
- Predictive Analytics
- Recommendation Engines
- Text Mining