Course
Data and Analytics for Value-Based Care
The technical course for the people who build the plumbing: claims, clinical, and social data; interoperability and the federal rules; the analytics pipeline; risk models, total-cost and registry analytics; and getting insight into the workflow.
By the end of this course, you will be able to:
- Compare claims, clinical, social, and ADT data by what each can and cannot show
- Explain how FHIR, exchange networks, and federal rules move data across organizational walls
- Describe the pipeline, quality, and identity work that trustworthy analytics depends on
- Build the core analyses of risk stratification, cost decomposition, and care-gap registries
- Deliver insight into the workflow where action actually happens
The Data Landscape
The raw material of value-based analytics: claims data (complete but lagging), clinical data (rich but walled), and the social and ADT feeds that add context and trigger action.
Moving and Connecting Data
Why health data does not flow and how the field makes it: the interoperability problem, the FHIR standard and exchange networks, and the federal rules that increasingly compel sharing.
Building the Analytics Foundation
The unglamorous plumbing everything rests on: the ingestion-to-warehouse pipeline, the ongoing discipline of data quality and governance, and the identity and attribution layer beneath every metric.
The Core Analytics
What the analytics function actually computes: risk stratification and predictive models, total-cost-of-care and utilization analysis, and the registries and care gaps that become work queues.
From Analytics to Action
Making analytics matter: quality measurement as a data-engineering task, the last mile that gets insight into the workflow, and what makes an analytics function drive value rather than produce unused reports.