THE CASE FOR CASE-MIX ADJUSTMENT IN PRACTICE PROFILING - WHEN GOOD APPLES LOOK BAD

Objective.-To assess the influence of patient characteristics on pract ice profiling. Using the example of specialty referrals by primary car e physicians, we evaluated the impact of adjusting for patient charact eristics (age/sex vs case mix) on the estimation of practice variation , the identification of outlier practices, and the evaluation of poten tial predictors of variation. Design and Setting.-We applied several m easurement strategies to a retrospective cohort of patients (N=37 830) within 52 physician practices in a large staff-model health maintenan ce organization during a 1-year period. Outcome Measures.-We calculate d unadjusted referral rates and adjusted standardized referral ratios for each physician. Using these, we determined coefficients of variati on and statistical ''outlier status.'' Results.-Adjustment for patient characteristics decreased the observed variation in referral profiles , with a decrease of more than 50% in the coefficient of variation. Th ree quarters of the physicians identified as statistical outliers with use of an age/sex-adjusted measure were no longer identified as such with use of a case-mix-adjusted measure. Several key predictors of una djusted referral rate (including physician age, practice tenure, site of practice, and extent of laboratory test ordering) dropped out of re gression models when the outcome variable was adjusted for patient cha racteristics. Conclusion.-Failure to adjust for case mix in physician practice profiles may lead to overestimates of variation and misidenti fication of outliers. To the extent that unadjusted practice profiles are used for decisions about education, sanctions, or employment, phys icians may be subject to inequitable decisions and actions. Misinforma tion about the causes and extent of practice variation may also lead t o misdirection of scarce resources for quality improvement efforts.