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This Learning Lab serves to empower analysts and analytics managers to seek and to apply external sources of social determinant data, including consumer reports and census data, to refine patient stratification approaches and to better model chronic disease management. The goal is to identify patients at rising risk for chronic disease progression or readmissions and to apply better messaging of educational materials and more refined targeting of case-management interventions.
Live Learning Lab: Integrating Social Determinant Data to Mitigate Rising Clinical Risk
Speaker: Jason E. Gillikin, BA CPHQ
Jason Gillikin leads Gillikin & Associates, a healthcare quality consultancy focused on analytics capability, population health management and Quality culture. His academic background includes degrees in moral philosophy and quantitative political science. He's a former board member of the Michigan Association for Healthcare Quality and currently serves on the NAHQ board of directors. Jason frequently speaks on the subject of health data analytics at various state associations and co-led the teams that developed NAHQ's Health Data Analytics competency and NAHQ's revised Code of Ethics. He's been a CPHQ since 2006 and affiliated clinical faculty in Medical and Bioinformatics at Grand Valley State University since 2014
Learning Objectives:
- Recognize the complexities of acquiring and staging external sources of social-determinant data.
- Apply best-practice approaches to integrating and curating external sources of social-determinant data.
- Develop segmentation approaches that inform the delivery of care or opportunities for structural improvement in care.
- Create messages to patients that speak to their presumed socioeconomic cohort.
- Communicate complex or nuanced findings to senior leaders and clinicians that may conflict with pre-existing biases.
Credit
CPHQ CE:1.0
Publisher
NAHQ