Module 1
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.
By the end of this module, you will be able to:
- Explain what makes claims data uniquely complete and where it misleads
- Describe why EHR data is clinically rich but blind beyond its own walls
- Identify why ADT feeds carry the highest operational value of any data source
- Claims Data Claims are the backbone of value-based analytics. This lesson covers what they are, how they are structured, and the quirks that trip up analysts. About 5 min
- Clinical and EHR Data Clinical data is everything claims are not: rich, current, and clinically true. This lesson covers its structure and its defining limitation. About 5 min
- Social and Other Data Beyond claims and clinical data lie the feeds that add context and trigger action. This lesson covers social data, ADT alerts, and supplemental sources. About 4 min
Module quiz
Answer all questions to see your score.
1. What makes claims data uniquely valuable for population analytics?
Claims follow the patient across all settings, the whole-population visibility no single organization's records provide, at the cost of lag and clinical thinness.
2. What is the defining limitation of EHR data for population management?
The EHR is deep and narrow where claims are broad and shallow; neither alone shows the whole patient, so they must be combined.
3. Which feed is the highest operational value for triggering timely action?
ADT alerts trigger transitional-care work while the window is still open, the single most actionable feed in population health.