Effective population health initiatives are challenging to implement for a variety of reasons. Care teams are already overburdened, and healthcare data is challenging to aggregate and analyze. These factors make it difficult to accurately identify patients who are high-risk or have rising risk for poor outcomes and provide appropriate intervention. To manage patient populations effectively and efficiently, healthcare organizations must be able to automate predictive risk stratification based on claims data, clinical data, and social determinants of health. When care teams know which patients need the most help, which patients have rising risk, and which patients are healthy, they can focus their valuable time where it’s needed most. In this webinar, Dr. Welch shares best practice strategies for utilizing analytics that empower change with actionable workflows, like patient engagement, to ensure that clinically integrated entities can manage high-risk populations appropriately, while also caring for those with rising risk, and engaging with healthy populations mapped to the right targeted interventions.
2. Agenda
Introduction
The Care Team Burnout Challenges
Risk Stratification Best Practices and Models
High-Value Data Inputs
Measuring Outcomes
Review and Questions
Poll Q: How often have you been asked to answer these two questions?
- Never
- 1-2 times/quarter
- 2-3 times/quarter
- More than 2-3 times/quarter
ChristianaCare investigated the effectiveness of text-based mobile messaging and in-home fasting blood sugar (FBS) in the detection of type 2 diabetes compared to traditional 2hr OGTT. ChristianaCare partnered with Twistle to provide smartphone-based patient engagement; patients used glucometers and lancets that they were also using during pregnancy. Preconfigured communication pathways delivered time-based, HIPAA-compliant education and reminders, and captured FBS data using easy-to-complete forms. Patients received appropriate automated text replies and if warranted, data was escalated to clinical staff for additional intervention. Participants could also engage with clinical staff asynchronously to address questions or issues.-----------
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