New Methodology Studied for P4P

A group of researchers has found that using lab data for pay-for-performance program methodology can be up to 67 times more important than other models that rely on billing information. The researchers--from Cardinal Health, Dublin, Ohio, the Center for Outcomes Research at the Children's Hospital of Philadelphia and the University of Pennsylvania, School of Medicine--analyzed lab information to create six disease-based models to predict in-hospital mortality that adjusted for severity of illness. The diseases were ischemic stroke, hemorrhagic stroke, pneumonia, myocardial infarction, heart failure and septicemia. The data was derived from 194,903 admissions at the hospital between 2000 and 2003. The researchers then compared their findings with previous P4P data on 629,490 admissions across 195 hospitals that used methodology based on billing and administrative data. They published their findings, titled Using Automated Clinical Data for Risk Adjustment: Development and Validation of Six Disease-Specific Mortality Predictive Models for Pay-for-Performance, in the August 2007 issue of "Medical Care" the official journal of the medical care section of the American Public Health Association. For more information, go to www.cardinal.com