SY03 – Addressing Social Determinants Impacting LOS and Readmissions
Patients with social determinants in addition to somatic conditions are at greater risk for poor outcomes and excess hospital utilizations. Identifying and addressing these social determinants can help hospitals and health systems achieve far better patient outcomes, while also combatting excess length of stay (LOS) and avoidable readmissions. Healthcare multidisciplinary teams try to tackle these issues, but many still lack the actionable insight needed for noticeable and sustained results. This session will review how Baylor Scott & White is using advanced technologies to better facilitate discharge planning, reduce chart review time and lower excess length of stay. Using artificial intelligence, the hospital is able to better predict real-time capacity and improve patient throughput. We will also discuss how surfacing patient insights from EMR data, including the massive amounts of unstructured text, and sharing this data between hospitals and community-based organizations results in increased operational and clinical benefits, including lower readmissions.
1. Define the complex issues related to hospital length of stay and how that affects a myriad of outcomes.
2. Analyze approaches, including Natural Language Processing and predictive analytics, to reduce chart review time and optimize the discharge planning process
3. Describe how hospitals and health systems can partner with community-based organizations to improve readmission outcomes