As healthcare continues to incorporate Care Management into everyday care for chronic conditions, Health Systems are recognizing the importance of addressing social determinants and utilizing the community health ecosystem and as a consequence working more closely with Community Based Organizations (CBOs) such as Meals on Wheels, foodbanks, homeless shelters, etc. Hospitals and health systems can partner with community-based organizations to improve readmission outcomes.

This session will summarize the complex issues related to hospital length of stay and discharge planning and how that affects a myriad of outcomes, as well as discuss approaches, including Natural Language Processing (NLP) and predictive analytics to optimize discharge planning process.

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Mary Piepenbrink, RN, BSN, MBA

Mary Piepenbrink is a Senior VP at Pieces Technologies, a Dallas-based technology company that provides AI, analytics and case management solutions to hospitals and community organizations. Mary has a nursing background and 20 years of work in healthcare informatics. Prior to joining Pieces, Mary was an Associate Partner at IBM where she led large IT projects for healthcare. Mary served on IBM Health Corps, a pro bono Whole Person Care assignment in Washington DC. She also worked on healthcare projects in the UK, Canada, and the Middle East. Mary’s passion is delivering solutions that support caregivers within their normal workflow, while driving significant operational benefits for the healthcare systems and the communities they serve. Mary works with the NC Harm Reduction Coalition as a board member, educator, and volunteer. She is an avid sailor, but when on land loves just hanging with the family’s two rescue boxers