Teams working in this area will explore how various clinical interventions and healthcare services impact patient recovery. Ideas that teams might work on include: 
Leveraging Diagnosis Related Groups (DRG), and the frequency, sequencing, and intensity of interventions delivered by all of the disciplines to understand impact on outcomes; 2) Length of stay (LOS) evaluation related to number of days and progress on therapy interventions such as stability for Falls patients or ability to feed for Neonatal Intensive Care Unit (NICU) patients; 3) Identify the impact of missed care from one of more of the therapist clinicians, etc.

Teams will explore how large, complex datasets from multiple care teams can lead to new discoveries and predictive insights for improving patient outcomes. Dive into patient data to identify hidden patterns using advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques.

Teams will develop solutions to summarize, integrate, and visualize complex multidisciplinary data. This will both provide clinicians with a clearer picture of patient progress and future care needs, as well as enable patients to understand their hospital journey and manage post-discharge care.