Speakers

Kassie Ryan, RN, MSN

Improvement Specialist, Health Catalyst at Allina Health

Kassie is a nurse informaticist with experience in bedside nursing, healthcare order set and alert build, and quality improvement in regulatory and safety. She holds a BSN in Nursing and an MSN in Nursing Informatics.

Kassie’s current focus is leading quality improvement projects at Allina Health in areas of regulatory, clinical quality, and safety.

Speaker Sessions

Detecting, Monitoring, and Preventing Patient Safety Events

More than 21 percent of people in the US report experiencing [DK1] a medical error in their own care, and 33 percent report an error in the medical care of a relative or friend.  Current manual regulatory reporting approaches find less than 5 percent of all-cause harm using data at least 30-days old and require extensive time and resources. Allina Health, an integrated healthcare delivery system, was looking to improve the safety of the patients cared for at its facilities. Allina is now on the path to automate patient safety surveillance through the use of triggers and to develop embedded clinical workflow algorithms, enabling interventions before harm occurs.  In this session, Allina will share its patient safety journey learnings, including developing a culture of safety, improving processes and communications, and gaining analytics insights. Learn how they have effectively used their learnings with three different patient safety challenges.

Predictive Analytics: Making Patients Safer Through Event Reporting and Prediction

More than 21% of people in the US report experiencing a medical error in their own care, and 33% report an error in the medical care of a relative or friend.  With the effectiveness of artificial intelligence and predictive analytics growing in multiple industries, it is time to put it to work to make patients safe. Allina Health is determined to improve the safety of the patients cared for at its facilities by learning from past adverse events, identifying and addressing root causes, and automating the identification of triggers to indicate when a patient is in potential harm, or if harm may have occurred.     Allina is on the path to automate patient safety surveillance through the use of triggers and apply this knowledge to develop algorithms embedded in the workflow of clinicians to warn them of potential harm in a way that allows them to intervene before harm occurs.  In this session, Allina will share how it has effectively used this approach with three different patient safety challenges.

Apply to be an Analytics Walkabout Speaker

[gravityform id=1 title=false description=false ajax=true]