Improving Care Transitions with Predictive, Real-Time and Associative, In-Memory Analytics
Sponsored by QlikView and presented by Health Data Management.
The Patient Census Dashboard is one of the most popular BI solutions for performance improvement at Allina Health. This associative in-memory “data discovery” BI application enables Care Managers across 11 hospitals at Allina Health to quickly identify those patients who have the highest predicted likelihood of readmitting, while they are still in the hospital.
This presentation will address rollout, acceptance and some early indications of impact. Included in the presentation will be a description of the general approach to BI at Allina Health and a walkthrough of each layer of the technical architecture of the Patient Census Dashboard specifically, including a high-level discussion of the predictive readmission risk model that Allina developed. As the first larger-scale foray into "near real time" data warehousing at Allina Health, you will hear the impact and understand EDW operational considerations. Generous time will be given to Q and A.
Listen in on this presentation to learn how to:
- Understand a general approach to enterprise Business Intelligence (BI) at Allina Health Conceptualize the technical architecture of the Patient Census Dashboard
- Be able to discuss the predictive readmission risk model that Allina developed
- Understand some of the operational considerations of "near real time" data warehousing
Attend On-Demand Webinar
Alle velden zijn verplicht
QlikTech International AB and its Affiliates
Scheelevägen 24-26, SE-223 63 Lund, Sweden