1. Project on Risk Adjustment and SES in Performance Measurement
Karen Pace, PhD, MSN
National Quality Forum
SNP Leadership Forum October 11, 2013

2. NQF Project on Risk Adjustment and SES
Project Page - Risk Adjustment and SES
This project seeks to develop a set of recommendations on the inclusion of socioeconomic status (SES) and other factors such as race and ethnicity in risk adjustment for outcome and resource use performance measures.
Nominations for Expert Panel due by 10/22/13
In-person meeting January 15-16, 2014
Expected completion June 2014

3. NQF Background/Context
NQF endorses performance measures for accountability applications including public reporting in addition to improvement –criteria apply to all applications
NQF Measure Evaluation Criteria require risk adjustment or stratification for outcome and resource use performance measures (or analysis to justify no adjustment)
NQF guidance indicates that factors related to disparities in care (e.g., race, ethnicity, SES) not be included in risk adjustment, rather performance measures should be stratified by those factors when indicated
Increasing concern and controversy related to including SES and other demographic factors in risk adjustment for performance measures

4. Risk Adjustment for Performance Measures
The goal is to “level the playing field” so that differences in outcome performance measure scores are not driven by differences in severity of patient conditions
Risk factors (variables) included in the risk model should be present before care begins so not confounded with quality of care provided (e.g., complications that occur during care)
Association with an outcome is one criterion for inclusion, but not the only criterion (e.g., staff skill/experience may be associated with an outcome, but not included in risk model)
Risk model performance metrics will not be comparable to models that try to explain everything that contributes to the outcome being measured

5. Case mix or Risk Adjustment
Process of controlling for patient factors that could influence patient outcomes or resource use – should be present before care begins
Shaughnessy & Crisler, 1995 5

6. Accounting for Different Levels of Risk for Experiencing an Outcome
Stratification by risk category
Control for variation in risk/case mix (in statistical risk adjustment models)
Logistic regression for dichotomous outcomes
Multiple regression for continuous outcomes

7. Key Issues Conceptual and empirical relationships
SES, race/ethnicity, health status captured in risk models
Methodological
Patient level, provider level, or community level adjustment
Data
Availability of standardized data on race, ethnicity, SES
Performance measurement vs. policy response
Identifying differences in performance related to serving disadvantaged population and potential penalties that may result
Potentially competing values or priorities

8. Different Perspectives
At least two divergent views on adjusting for differences in SES, race, and ethnicity:
obscures potential problems in equitable care and outcomes
essential for fair comparisons among providers of healthcare services

9. Some Questions to Consider During this Work
Following are just a few of the questions we might address
Do all providers who care for disadvantaged populations have poorer scores on performance measures than providers serving other populations?
If lower SES results in lower health status, is that already captured in variables on prior conditions/comorbidities?
Although providers cannot modify a patient’s SES, are there care practices that can and should be modified based on a patient’s SES?
For accountability purposes, how should fair comparisons be made?
Discussion – other questions???

10. How to be Involved Nominate self or others for Expert Panel by 10/22
Attend webinars and meetings
Comment on draft report
Follow progress by:
Obtaining NQF account and following on dashboard
Signing up for listserv Risk Adjustment and SES