Outpatient encounter data for risk adjustment: strategic issues for Medicare and Medicaid.
Payers are increasingly using diagnostic data from outpatient encounter records to adjust the payment to health plans. Although much has been written about the ability of such data to predict health care costs, little has been written about the data itself--its quality and availability. Fee-for-service (FFS) data face several threats to their validity, including the possibility that they may seriously underreport diagnoses. Because the systems and incentives that yield FFS and managed care diagnosis data are quite different, they may not be comparable, depending on circumstances such as audit rules. The next generation of risk adjustment models should be designed around the capabilities and potentialities of plans' information systems.
Welch
W Pete
WP
Mid Atlantic Medical Services, Inc., Rockville, MD, USA.
D000043:Abstracting and Indexing; D000368:Aged; D000553:Ambulatory Care / Q000191:economics / Q000706:statistics & numerical data*; D002908:Chronic Disease / Q000145:classification / Q000191:economics; D003953:Diagnosis-Related Groups / Q000145:classification / Q000191:economics; D019468:Disease Management; D018588:Fee-for-Service Plans / Q000191:economics* / Q000706:statistics & numerical data; D006279:Health Maintenance Organizations / Q000191:economics* / Q000706:statistics & numerical data; D006801:Humans; D007256:Information Systems; D008484:Medicaid / Q000706:statistics & numerical data*; D008499:Medical Records; D016345:Medicare Part B / Q000706:statistics & numerical data*; D010934:Planning Techniques; D012051:Reimbursement Mechanisms; D020379:Risk Adjustment; D014481:United States