Risk-Adjusted Mortality: Observed-to-Expected Ratios
Risk-adjusted mortality measures a hospital's actual death rate against the rate expected given its patient case mix — age, comorbidities, admission severity. The observed-to-expected (O/E) ratio is the canonical metric.
Why risk adjustment matters
Raw mortality rates penalize hospitals that treat the sickest patients. A regional tertiary center taking transfers from community hospitals will have a higher unadjusted mortality rate than a community hospital that transfers complex cases out. Risk adjustment levels the comparison by predicting the expected mortality rate given the case mix, then comparing observed to expected.
The O/E ratio
Observed-to-Expected ratio under 1.0 means the hospital performed better than expected given its case mix. Over 1.0 means worse. CMS uses risk-adjusted 30-day mortality rates for HF, AMI, PN, COPD, CABG, and stroke in the Hospital Value-Based Purchasing Program; SMR (Standardized Mortality Ratio) is the directly analogous measure in inpatient surveillance.
Where Vizier fits
Vizier computes risk-adjusted mortality from EHR-pulled encounter data using published CMS risk-adjustment models. The drill-down view shows which patient cohorts are driving variance from expected, distinguishing case-mix-driven mortality from process-of-care failures actually worth intervening on.