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
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.
METHODS. (1) Acquire and stage external sources of consumer data.
(2) Integrate social-determinant data into existing data structures.
(3) Develop segmentation strategy.
(4) Develop predictive models.
(5) Socialize findings, especially counterintuitive ones.
Obstacles included
(1) Navigating HIPAA.
(2) RFPs and license agreements with data brokers.
(3) Cleansing data sources.
(4) Accepting an inability in some cases to drill to an individual.
The approach we took mirrors best practices in industries other than health care. Health care has been very slow to adopt the data-management approaches of retail, finance and related industries.
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.