Risk Adjustment for Measuring Health Care Outcomes¶
Iezzoni, L. I. (2013). Risk Adjustment for Measuring Health Care Outcomes. Health Administration Press.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Mechanisms¶
- Case-Mix Risk Stratification Table
- Its strength is transparency: stratification is intuitive and auditable — anyone can see which bin a case fell in and how each unit did within it — and it localizes performance to specific strata instead of hiding it in one averaged number.
This sourceRisk stratification can reveal how provider performance differs across high- and low-risk patient strata rather than collapsing every patient into one overall comparison.
- Its strength is transparency: stratification is intuitive and auditable — anyone can see which bin a case fell in and how each unit did within it — and it localizes performance to specific strata instead of hiding it in one averaged number.
- Measurement Standardization
- Standardizing the wrong operational definition produces a metric that is beautifully consistent and measures the wrong thing
This sourceExplains that outcome comparisons should adjust for relevant differences in patient risk and case mix.
- Standardizing the wrong operational definition produces a metric that is beautifully consistent and measures the wrong thing
Verification¶
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Does it back the claim? Not recorded. Neither this nor any other of the 2 citations of this work carries a recorded support check.
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