REDUCE HOSPITAL READMISSIONS
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AAJ TECHNOLOGIES CONVENED A PANEL OF HEALTHCARE INDUSTRY BI AND ANALYTICS EXPERTS TO SHARE THEIR ADVICE. THIS EBOOK PROVIDES MAJOR INSIGHTS FROM THAT PANEL.
PART 1 – Michele Russell, CEO, Russell Consulting Group: Michele explores what you need to know before you begin implementing your readmissions reduction initiatives.
Key takeaways you can expect from Michele:
- Navigating the concerns over HIPAA privacy and security along with risk mitigation regarding Big Data
- Storage concerns – where will the data live? How do we address accessibility, speed, and redundancy?
- In-sourcing vs Outsourcing pros and cons
PART 2 – Andrew Satz, Co-Founder, Data Scientist, and Futurist, Metrix Labs. Andrew shares detailed information on how data analytics can be used to predict when a patient will readmit.
Topics (and examples) include:
- How data can be used to segment the patient population into groups
- How to use outcomes to predict which patients are more likely to readmit
- Examples of how we can use data science to determine what keeps patients from readmitting
PART 3 – Kevin Oppenheimer, Principal/Owner KGO Consulting Group
- Forecasting 30-day hospital readmissions on a proactive basis
- How to build a dashboard that will help you forecast healthcare outcomes
PART 4 – Ed Kirchmier, VP Global Delivery, AAJ Technologies
Case Study: A Care Transition System (CTS) to Reduce Hospital Readmissions
This case study illustrates How AAJ Technologies Created A Care Transition System (CTS) To Dramatically Reduce Hospital Readmissions.
AAJ’s solution addressed key care transition elements:
- Medication management.
- Physician follow-up.
- Home & community-based services.
- Disease education and self-management.
Also discussed will be the results of implementing this CTS: How in addition to reduced hospital readmissions, the client also saw increased patient satisfaction and reduced manual labor.
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