Course
Evaluating Value-Based Care
How to read the evidence critically: counterfactuals and comparison groups, the traps that fool people (regression to the mean, selection, benchmark assumptions), gross versus net savings, and what the CMMI track record actually shows.
By the end of this course, you will be able to:
- Identify the counterfactual behind any claimed savings, and judge whether it is credible
- Explain how comparison groups and difference-in-differences isolate a program's real effect
- Detect regression to the mean, selection effects, and assumption-driven benchmarks in a study
- Distinguish gross from net savings, and read statistical significance alongside magnitude
- Summarize what the CMMI track record does and does not show
The Evaluation Problem
Why measuring whether a program worked is genuinely hard: the counterfactual, confounding, and what 'worked' even means.
Comparison Groups
The heart of causal evaluation: why before-and-after misleads, how to build a valid comparison, and why value-based models rarely randomize.
The Traps
The specific biases that fool smart people: regression to the mean, selection effects, and assumption-driven benchmarks.
Reading the Numbers
Interpreting results honestly: gross versus net savings, statistical significance and magnitude, and whether a result generalizes.
Evidence in Context
Putting it together: what the CMMI track record actually shows, the certification bar for expansion, and a checklist for reading any evaluation.